text stringlengths 1.23k 293k | tokens float64 290 66.5k | created stringdate 1-01-01 00:00:00 2024-12-01 00:00:00 | fields listlengths 1 6 |
|---|---|---|---|
Unsupervised Word Mapping Using Structural Similarities in Monolingual Embeddings
Most existing methods for automatic bilingual dictionary induction rely on prior alignments between the source and target languages, such as parallel corpora or seed dictionaries. For many language pairs, such supervised alignments are not readily available. We propose an unsupervised approach for learning a bilingual dictionary for a pair of languages given their independently-learned monolingual word embeddings. The proposed method exploits local and global structures in monolingual vector spaces to align them such that similar words are mapped to each other. We show empirically that the performance of bilingual correspondents that are learned using our proposed unsupervised method is comparable to that of using supervised bilingual correspondents from a seed dictionary.
Introduction
The working hypothesis in distributional semantics is that the meaning of a word can be inferred by its distribution, or co-occurrence, around other words. The validity of this hypothesis is most evident in the performance of distributed vector representations of words, i.e word embeddings, that are automatically induced from large text corpora (Bengio et al., 2003;Mikolov et al., 2013b). The qualitative nature of these embeddings can be demonstrated through empirical evidence of regularities that reflect certain semantic relationships. Words in the vector space are generally clustered by meaning, and the distances between words and clusters reflect semantic or syntactic relationships, which makes it possible to perform arithmetic on word vectors for analogical reasoning and semantic composition (Mikolov et al., 2013b). For example, in a vector space V where f = V (''f rance"), p = V (''paris"), and g = V (''germany"), the distance f − p reflects the country-capital relationship, and g + f − p results in a vector closest to V (''berlin"). Named entities and inflectional morphemes are particularly amenable to vector arithmetic, while derivational morphology, polysemy, and other nuanced semantic categories result in lower performance in analogy questions (Finley et al., 2017).
The extent of these semantic and syntactic regularities is difficult to assess intrinsically, and the performance in analogical reasoning can be partially attributed to the clustering of the words in question (Linzen, 2016). If meaning is encoded in the relative distances among word vectors, then the structure within vector spaces should be consistent across different languages given that the datasets used to build them express similar content. In (Rapp, 1995), a simulation study showed that similarity in word co-occurrence patterns within unrelated German and English texts is correlated with the number of corresponding word positions in the monolingual cooccurrence matrices. More recently, (Mikolov et al., 2013a) showed that a linear projection can be learned to transform word embeddings from one language into the vector space of another using a mediumsize seed dictionary, which demonstrates that the multilingual vector spaces are at least related by a linear transform. This makes it possible to align word embeddings of different languages in order to be directly comparable within the same seman-tic space. Such cross-lingual word embeddings can be used to expand dictionaries or to learn languageindependent classifiers.
A number of methods have been proposed recently for learning cross-lingual word embeddings with various degrees of supervision, ranging from word-level alignment using bilingual dictionaries (Ammar et al., 2016), sentence-level alignment using parallel corpora (Gouws et al., 2015;Klementiev et al., 2012), or document alignment using crosslingual topic models (Vulić and Moens, 2015;Vulić and Moens, 2012). Using such alignments, especially large parallel corpora or sizable dictionaries, high-quality bilingual embeddings can be obtained (Upadhyay et al., 2016). In addition, a number of methods have been proposed for expanding dictionaries using a small initial dictionary with as few as a hundred entries (Haghighi et al., 2008).
However, such alignments are not available for all languages and dialects, and while a small dictionary might be feasible to acquire, discovering word mappings with no prior knowledge whatsoever is valuable. Intuitively, if the monolingual corpora express similar aspects of the world, there should be enough structure within the vector space of each language to recover the mappings in a completely unsupervised manner. In this paper, we propose a novel approach for learning a transformation between monolingual word embeddings without the use of prior alignments. We show empirically that we can recover mappings with high accuracy in two language pairs: a close language pair, French-English; and a distant language pair, Arabic-English. The proposed method relies on the consistent regularities within monolingual vector spaces of different languages. We extract initial mappings using spectral embeddings that encode the local geometry around each word, and we use these tentative pairs to seed a greedy algorithm which minimizes the differences in global pair-wise distances among word vectors. The retrieved mappings are then used to fit a linear projection matrix to transform word embeddings from the source to the target language.
Related Work
Few models have been proposed for extracting dictionaries or learning bilingual embeddings without the use of any prior alignment. For languages that share orthographic similarities, lexical features such as the normalized edit distance between source and target words can be used to extract a seed lexicon for bootstrapping the bilingual dictionary induction process (Hauer et al., 2017). In (Diab and Finch, 2000), unsupervised mappings were extracted by preserving pairwise distances between word co-occurrence representations from two comparable corpora. The model was only evaluated mono-lingually, where two sections of a corpus were used for collecting co-occurrence statistics separately, and an iterative training algorithm was then used to retrieve the mapping of English words to themselves. Only punctuation marks were used to seed the learning and high accuracy results were reported. However, the method was not evaluated cross-lingually. We observed experimentally that punctuation marks-and function words in general-are insufficient to map words cross-lingually since they have different distributional profiles in different languages due to their predominant syntactic role.
Another unsupervised approach has been recently proposed using adversarial autoencoders (Barone, 2016) where a transformation is learned without a seed by matching the distribution of the source word embeddings with the target distribution. Preliminary investigation showed some correct mappings but the results were not comparable to supervised methods. Recents efforts using carefully-tuned adversarial methods report encouraging results comparable to supervised methods (Zhang et al., 2017;Conneau et al., 2017). In (Kiela et al., 2015), bilingual lexicon induction is achieved by matching visual features extracted from images that correspond to each word using a convolutional neural network. The imagebased approach performs particularly well for words that express concrete rather than abstract concepts, and provides a convenient alternative to linguistic supervision when corresponding images are available.
The unsupervised mapping problem arises in other contexts where an optimal alignment between two isomorphic point sets is sought. In image registration and shape recognition, various efficient methods can be used to find an optimal alignment between two sets of low-dimensional points that correspond to images with various degrees of deformation (Myronenko and Song, 2010;Chi et al., 2008). In manifold learning, two sets of related high-dimensional points are projected into a shared lower dimensional space where the points can be compared and mapped to one other, such as the alignment of isomorphic protein structures (Wang and Mahadevan, 2009) and cross-lingual document alignment with unsupervised topic models (Diaz and Metzler, 2007;Wang and Mahadevan, 2008).
Skip-gram Word Embeddings with Subword Features
In the skip-gram model presented in (Mikolov et al., 2013b), a feed-forward neural network is trained to maximize the probability of all words within a fixed window around a given word. Formally, given a word w in a vocabulary W , the objective of the skip-gram model is to maximize the following loglikelihood: where C w is the set of words in the context of w. The words are represented as one-hot vectors of size |W | that are projected into dense vectors of size d. Over a large corpus, the d-dimensional word projections encode semantic and syntactic features that are not only useful for maximizing the above probability, but also serve as general-purpose representations for words.
In (Bojanowski et al., 2016), a word vector is represented as the sum of its character n-grams which helps account for inflectional variations within a language, especially for morphologically rich languages where less frequent inflections are less likely to have good representations using only word-level features. Using n-grams helps account for lexical similarities among words within the same language; independently-learned embeddings with no explicit alignment would still have unrelated n-gram representations even if the languages share lexical similarities. We will refer to this model as the subword skip-gram.
Linear Transformation of Word Embeddings
Given word embeddings in two languages X and Y , and a dictionary of (source, target) word pairs with embeddings x s and y t , respectively, a transformation matrix T , such that y t = T x s , can be estimated with various degrees of accuracy (Mikolov et al., 2013a). Large, accurate dictionaries result in better transformations, but a good fit can also be obtained using a few thousand word pairs even in the presence of noise (see Section 4.3.4 for an empirical demonstration). Formally, given a dictionary of n word pairs, .., n, and M is a mapping from X to Y , the linear transformation matrixT is learned by minimizing the following cost function After learningT , the translation of new source words can be retrieved by transforming the word vector first, then finding its nearest neighbor in the target vocabulary.
Unsupervised Word Mapping
Learning an accurate transformation between word embeddings as described in Section 2.2 requires a seed dictionary of reasonable size. We propose a method that bypasses this requirement by learning to align the monolingual embeddings in an unsupervised manner. The underlying assumption is that word embeddings across different languages share similar local and global structures that characterize language-independent semantic features. For example, the distance between the words monday and week in English should be relatively similar to the distance between lundi and semaine in French. We attempt to recover the correspondences between different languages by exploiting these structural similarities.
Our approach consists of two main steps. In the first step (Section 3.1), we extract initial mappings using spectral features that encode the geometry of the local neighborhood around a point in the vector space. In the second step (Section 3.2), we it-eratively refine the correspondences using a greedy optimization algorithm, which we refer to as Iterative Mapping (IM for short). IM is a variation on the word mapping model in (Diab and Finch, 2000). The model does not make language-specific assumptions, making it suitable for learning crosslingual correspondences. We then use these correspondences to learn a linear transformation between the source and target embeddings, as described in Section 2.2.
Estimating Initial Correspondences
To analyze local structures in monolingual vector spaces, we treat each word embedding as a point in a high-dimensional space and further embed each point into a local invariant feature space, as proposed in (Chi et al., 2008) for affine registration of image point sets. The local invariant features are produced through eigendecomposition of the k-nearestneighbor (knn) graph for each point in the vector space as described below.
For a word embedding w, we construct its knn adjacency graph, A w , such that A w is a k × k matrix that contains the pair-wise similarities among w's knearest neighbors, including w itself. To embed the adjacency matrix in a permutation-invariant space, w is mapped to a feature vector v w that contains the sorted eigenvalues of L w , which is defined as, is the Gaussian similarity function and d ij is the Euclidean distance between points i and j. We will refer to the vectors of sorted eigenvalues as spectral embeddings.
After extracting these local features for all points in X and Y , each point p in X is mapped to its nearest neighbor q in Y using the Euclidean distance between their spectral embeddings. To minimize the spurious effect of hubs-points that tend to be nearest neighbors to a large number of other points (Radovanović et al., 2010)-we only include the correspondences where the neighborhood is symmetric; that is, if p and q are each other's nearest neighbor in the local spectral feature space.
The spectral embeddings are k-dimensional representations of the original word embeddings that encode the local knn structure around each word. Since a linear transformation preserves the distances between all points, the spectral embeddings allow us to map each source word to a target word with a similar knn structure. The parameter k offers a simple way to adjust the amount of contextual information used in building the spectral embeddings.
Estimating Global Correspondences
After extracting initial correspondences using spectral features, we iteratively update the mapping to preserve the global pair-wise distances using the iterative mapping (IM) algorithm. The objective of IM is to preserve the relative distances among the source words in the mapped space, which is achieved by locally minimizing a global loss function in iterations until convergence. Note that the spectral embeddings described in Section 3.1 are only used to extract tentative pairs for initialization. Since the spectral embeddings only capture local features, the rest of the algorithm uses the original word embeddings to preserve global distances among source words.
Given a set of n monolingual embeddings X for the source language, and a set of m monolingual embeddings Y for the target language, we use the residual sum of squares loss function defined below to optimize the mapping M from X to Y : where D X and D Y are the pairwise Euclidean distances for X and Y , respectively, and p = 1, ..., n, q = 1, .., n span the indices in X.
We seed the learning using the correspondences obtained by the spectral initialization method. The remaining words are mapped to a virtual token with a distance c from all other words, including itself, where c > 0 is a tunable parameter. The optimization is then carried out in a greedy manner: a source word, x i , is selected at random, and M (x i ) is selected to be the word in Y that minimizes the loss function L. This greedy algorithm yields a locally optimal mapping at each step and the final result depends on the initialization. The IM method is summarized in Algorithm 1.
After optimizing the global distances using IM, we use the (source, target) pairs in M to learn a linear transformation between X and Y as described in Section 2.2. input : Word embeddings X and Y output: Algorithm 1: Iterative mapping with spectral initialization
Experiments
We experimented with two language pairs: French-English, and Arabic-English. French shares similar orthography and word roots with English, but for evaluating the generality of the approach, we don't utilize these similarities in any form. 1 Arabic, on the other hand, is a dissimilar language with more limited resources, and it is noisier at the word level due to clitic affixation that is challenging to tokenize. This makes it a suitable test-case for a realistic lowresource language.
Data
We extracted various datasets with different levels of similarity to test the proposed unsupervised word mapping approach. We used the following data sources:
WMT'14 the Workshop on Machine Translation
French-English corpus (Bojar et al., 2014). This is a parallel corpus, but we don't use the sentence alignments. UN Parallel Arabic-English corpus from UN proceedings (Ma, 2004) We randomly extracted 5M sentences from each corpus to create the datasets in Table 1, which are either parallel (suffix:p), similar (suffix:s), or dissimilar (suffix:d). All datasets are within-genre to ensure that they share a common vocabulary. We tokenized the English and French datasets using the CoreNLP toolkit (Manning et al., 2014). We also converted all characters to lower case and normalized numeric sequences to a single token. Arabic text was tokenized using the Madamira toolkit (Pasha et al., 2014). We used the D3 tokenization scheme, and we further processed the data by separating punctuation and normalizing digits. Note that Arabic tokenization is non-deterministic due to clitic affixation, so the processed datasets still contained untokenized phrases.
Experimental Set-up
For each of the datasets described above, we generated 100-dimensional word embeddings using the subword skip-gram model (Bojanowski et al., 2016). We extracted the most frequent 2K words from the source and target languages and their embeddings for the iterative mapping (IM) method. The loss function L in equation 2 was used to guide the tuning of model parameters. We tuned k = [10,20,30,40,50] for the spectral initialization, and due to randomness in IM, we repeated each experiment 10 times and used the mapping that resulted in the smallest loss. For the final linear transformation T , we used the most frequent 50K words in both source and target languages, and we used the hubness reduction method described in (Dinu et al., 2015) with c=5000.
We extracted dictionary pairs from the Multilingual WordNet (Miller, 1995;Sagot and Fišer, 2008;Elkateb and Fellbaum, 2006;Abouenour et al., 2013) where the source words are within the top 15K words in all datasets. From these pairs, we extracted a random sample of 2K unique (source, target) pairs for training the supervised method, and the remaining source words and all their translations were used for testing. This resulted in a total of 977 French words and 473 Arabic words for evaluation.
Analysis and Results
The unsupervised word mapping method proposed in this paper consists of three parts: given a subset of source and target words with a viable mapping, we extract tentative correspondences using spectral features as in Section 3.1. These initial pairs are used to seed the IM algorithm to refine the mapping as described in Section 3.2. The final correspondences obtained by the IM algorithm are then used as a seed dictionary to fit a linear transformation matrix between the source and target embeddings. The linear transformation step serves as a smooth generalization of the mapping since it preserves the structure of the source embeddings and can be used to extract translations of additional word pairs.
Word Frequency Analysis
In order to extract a mapping between two sets of points, we first need to ensure that a viable mapping between the two sets exists. In an unsupervised setting, we can analyze the word frequencies within the monolingual corpora; it is reasonable to assume that certain words would have high frequencies in multilingual datasets that cover similar topics. Word frequencies follow a consistent power distribution that is at least partially determined by meaning (Piantadosi, 2014). Using a set of 200 fundamental words, (Calude and Pagel, 2011) reported a high correlation between word frequency ranks across 17 languages drawn from six language families.
We analyzed the consistency of word frequencies in the French-English dataset fr-en-s using all Word- Net translation pairs where source words fall within certain frequency bands. For example, given all French words in WordNet that fall within the 1K most frequent words, we report the fraction of these words that have a translation within the 1K most frequent words in English. Among the top 10K source words, we have a total of 4,653 words with Word-Net translations, almost equally distributed among the ten frequency bands.
As show in Figure 1, at least 80% of the most frequent 1K French words have a translation within the same frequency band. Smaller overlap is observed for lower frequencies, where only about a quarter of the words have a translation within the same frequency band. This both confirms previous findings about the correlation of frequency ranks across different languages and also indicates that the correlation itself is dependent on word frequency. Note also that frequency ranks for the least frequent words are rather meaningless since most words in any finite dataset are likely to occur only once. Therefore, we carry our analysis and mapping using only the top 2K source and target words to improve the chances of having a feasible mapping between the two point sets.
Nearest Neighbor Structures
To extract initial correspondences, we assume that similar words have similar knn graphs. Figure 2 shows colormap visualizations of knn adjacency matrices of various source and target words in fr-en-s, where red represents higher similarity scores close to 1. Translation Initial mapping organisation organization development agence agency office dit say with chine china singapore project plan questions ouest west amid victimes victims death partir go asked refusé refused named conflit conflict elections constitution constitution democracy Table 2: A sample of initial pairs extracted using spectral embeddings to initialize IM for fr-en-s. Source indicates the source French word, Translation is the gold English correspondent, Initial Mapping is the first locally induced correspondent.
Source
Most words have similar color distributions in their neighborhood graphs as their translations, although most of them are not sufficiently distinct from other words, which is expected given the small dimensionality of the spectral space. Note also that most verbs have dense adjacency graphs due to variations in conjugation that tend to be clustered densely in the vector space. Ambiguous verbs like hold have dissimilar local structures, which reflects their inconsistent usage across the two languages. Nouns, on the other hand, tend to have less dense and more distinct local structures. One exception here is monday whose closest neighbors are other days of the week that have very similar representations, which results in a dense but consistent structure. Figure 3 shows two-dimensional projections of original word embeddings and their corresponding spectral embeddings. Note that most words moved closer to their correct translations in the spectral space, where words with similar adjacency graphs are clustered in the same regions. Table 2 shows a sample of initial correspondences extracted using spectral features for IM initialization. As expected, most word pairs are incorrectly mapped but semantically related to the target translation.
Global Distances
To verify the consistency of global distances, we randomly extracted a set of 100 WordNet pairs that lie within the most frequent 2K words in fr-en-s, and (top) and French (bottom) words: (a) "go" -"partir" (b) "refused" -"refusé" (c) "hold" -"tenir" (d) "say" -"dit" (e) "monday" -"lundi" (f) "office" -"agence" (g) "china" -"chine" (h) "university" -"université". we divided the set into two sets of 50 words each and calculated the pair-wise Euclidean distances among the English words ( Figure 4a) and among the corresponding French words (Figure 4b). For comparison, we extracted an additional random set of French words and calculated the Euclidean distances among them ( Figure 4c). As shown, the colormaps of corresponding English and French words are relatively similar compared to random words, which indicates that global pairwise distances also reflect consistent language-independent features. Tables 3 and 4 show a subset of word mappings retrieved using IM with spectral initialization on the various datasets. Recall that the objective of IM is to preserve global pairwise distances of the source words in the mapped space. Most IM mappings are either correct or related to the target translation; for example, the French word for February is mapped to September or January, which are nearest neighbors of the correct word in the target vector space and are semantically related. Using samples of 100 words randomly extracted from each dataset, we estimated the quality of word translations in terms of semantic similarity and relatedness. 2 As seen in Figure 5, over 60% of translations are semantically related, of which at least 20% are semantically similar.
Linear Transformation
Learning optimal linear transformations between multilingual vector spaces depends on the quality and size of the seed dictionaries while unsupervised mappings are expected to be noisy. In this section, we evaluate the quality of linear transformations with suboptimal supervision. Figure 6 demonstrates the performance of the transformations learned using dictionary pairs extracted from wordNet with different sizes and perturbation levels. The performance is reported in terms of precision at k, where k is the number of nearest neighbors in the target vocabulary.
Larger dictionaries result in more accurate transformations as expected. A thousand or more accurate dictionary pairs are sufficient to learn high quality transformations, while smaller dictionary sizes result in much lower precision at all k levels. Figure 6b shows the performance using a training dictionary of size 2K perturbed with incorrect mappings. Surprisingly, the precision is reasonably high even when only 50% of the dictionary pairs are correct. This indicates that a bilingual transformation can be learned successfully using few thousand word pairs even in the presence of noise, so a reasonable amount of incorrect mappings can be tolerated.
Evaluation
Using the (source, target) pairs extracted using IM with spectral initialization (IM-SI), we fit a linear projection matrix from the source to the target embeddings to compare the results with supervised linear transformation. We also compare with a baseline of random initialization of the IM method (IM-Rand). We evaluate the linear transformations on the different datasets in Table 1 by reporting the precision of mapping each test word to a correct translation within its k nearest neighbors, for k ∈ {1, 5, 10, 20, 50, 100}. The results are shown in Figure 7.
While the initial spectral embeddings didn't always recover the correct correspondences (see Table 2), these tentative pairs helped initialize the IM algorithm in the right direction for better global convergence. As shown in Figure 7, initializing IM with random pairs resulted in poor performance while spectral initialization helped converge to plausible mappings. In fact, the use of spectral initialization in combination with IM to seed the transformation resulted in a precision close to the supervised baseline as seen in Figures 7a and 7b. Figure 8 shows the performance of transforming Arabic word embeddings using the various models. The supervised baseline results are lower than the French-English case, which is partly due to the low coverage of WordNet translations for Arabic (see Table 5). Nevertheless, we managed to recover accurate mappings and linear transformations that perform comparably to the supervised baseline. Table 5 shows some examples of correct and incorrect transformations at k = 5 on Arabic test words. Observe that even in the case of incorrect matches, the k nearest neighbors are related to the target words in meaning. For example, all five nearest neighbors of the word (''/'ﺑﻨﺎﻳﺔbuilding'), are building-related, such as 'tower', 'parking', 'three-story', and 'mall'.
Conclusion
We proposed an unsupervised approach for learning linear transformations between word embeddings of different languages without the use of seed dictionaries or any prior bilingual alignment. The proposed method exploits various features and structures in monolingual vector spaces, namely word frequencies, local neighborhood structures, and global pairwise distances, assuming that these structures are sufficiently consistent across languages. We verified experimentally that, given comparable multilingual corpora, accurate transformations across languages can be retrieved using only their monolingual word embeddings for clues. | 6,207.6 | 2017-12-19T00:00:00.000 | [
"Computer Science",
"Linguistics"
] |
Data assimilation finite element method for the linearized Navier-Stokes equations with higher order polynomial approximation
In this article, we design and analyze an arbitrary-order stabilized finite element method to approximate the unique continuation problem for laminar steady flow described by the linearized incompressible Navier--Stokes equation. We derive quantitative local error estimates for the velocity, which account for noise level and polynomial degree, using the stability of the continuous problem in the form of a conditional stability estimate. Numerical examples illustrate the performances of the method with respect to the polynomial order and perturbations in the data. We observe that the higher order polynomials may be efficient for ill-posed problems, but are also more sensitive for problems with poor stability due to the ill-conditioning of the system.
Introduction
The question of how to assimilate measured data into large-scale computations of flow problems is receiving increasing attention from the computational mathematics community [3,7,22,26,28,36].There are several different situations where such data assimilation problems as can be seen in the above examples.One situation is when the data necessary to make the flow problem well-posed is lacking, for instance, when the data on the boundary of the domain is unknown; instead, measurements are available in some subset of the bulk domain or boundary to make up for this shortfall.In such a case, the problem is typically ill-posed, and numerical simulations are significantly more challenging to perform than when handling well-posed flow problems.Ill-posed problems usually come up in inverse problems and data assimilation.Traditionally, these ill-posed problems have been solved by regularizing at the continuous level, using e.g.Tikhonov regularization [38] or quasi-reversibility [34].The regularized problem is well-posed and may be discretized using any appropriate numerical technique.Then, the regularization parameter must be tuned to the optimal value for the noise in the data.There is considerable literature of research on Tikhonov regularization and inverse problems, and we suggest the reader to [32] and its references for an overview of computational approaches employing this strategy.The quasireversibility methods relevant to the current study may be found in [10][11][12]21].
The goal of the current contribution is to develop a finite element approach directly applied to the ill-posed variational data assimilation form.Regularization is then introduced at the discrete level utilizing stabilized finite element methods that allow for a comprehensive analysis employing conditional stability estimates.The idea is presented in [13] for standard 1 -conforming finite element methods.Ill-posed problems are analyzed in [14], and in [16], the technique is extended to nonconforming approximations.In both cases, low-order approximation spaces are considered.The error analysis requires the availability of sharp conditional stability estimates for the continuous problem.The estimates are conditional in the sense that a particular a priori bound must be assumed to hold for the solution, and the continuity provided in this bound is often merely Hölder [33].In the literature, these estimates are referred to as quantitative uniqueness results and employ theoretical methods such as Carleman estimates or three-ball estimates [1,31].Error bounds derived using conditional stability estimates can be optimal because they reflect the approximation order of the finite element space and the stability of the ill-posed problem.In particular, when applied to a well-posed problem, the finite element method recovers optimal convergence.
The ill-posed problem that we consider here is the unique continuation problem.The unique continuation problem for the Stokes equations was initially studied in [25].The analysis of the stability properties of ill-posed problems based on the Navier-Stokes equations is a very active field of research, and we refer to the works [4-6, 8, 29, 30, 35] for recent results.
This study aims to determine whether using high-order methods in the primal-dual stabilized Galerkin methods is as helpful in the ill-posed case as in the well-posed situation.Inspired by the approach proposed in [9] for the lowest-order finite element discretization of the unique continuation problem subject to the Navier-Stokes equations, here we generalize the method to arbitrary polynomial orders and investigate the benefits of using higher-order polynomials in numerical experiments.
The rest of the paper is organized as follows.In Section 2, we introduce the considered inverse problem and some related stability estimates.In Section 3, we describe the proposed stabilized finite element approximation of the data assimilation problem and state the local error estimate.The numerical analysis of the method is carried out in Section 4. Finally, Section 5 presents a series of numerical examples which illustrate the performance of the proposed method.
The linearized Navier-Stokes problem
Let Ω be an open polygonal (polyhedral) domain in R , = 2, 3. Let (, ) be the solution of the stationary incompressible Navier-Stokes equations and consider some perturbation (, ) of this base flow.If the quadratic term is ignored, the linearized Navier-Stokes equations for (, ) can be written where Here, is a diffusion coefficient.We assume that belongs to [ 1,∞ (Ω)] and that (, ) satisfies the regularity For this problem, we assume that measurements on are available in some subdomain ⊂ Ω having a nonempty interior and our purpose is to reconstruct a fluid flow perturbation of for system (1)-(2) based on the measurements of velocity.Now, we will present some useful notations.Consider the following spaces: where 2 0 (Ω) = { ∈ 2 (Ω) : ∫︀ Ω = 0}.We also define the norms, for = 1 or , Observe that in the definitions, we employ the same notation for = 1 and = .For any subdomain ⊂ Ω, we set Next, define the bilinear forms as: for all (, ) where : := ∑︀ ,=1 , , and, for all (, ) The weak form of the inverse problem can be expressed as: and Here, ∈ [ 1 ( )] corresponds to the exact fluid velocity on , i.e. is a solution to the linearized Navier-Stokes' equations in and has an extension to all of Ω. Below in the finite element method we will assume that we do not have access to , but only some measured velocities = + .So corresponds to the exact velocity polluted by a small noise ∈ [ 2 ( )] .Consider the linearized Navier-Stokes problem with a non-zero velocity divergence We assume that if the boundary conditions of system ( 8)-( 9) are homogeneous Dirichlet boundary conditions, then it is well-posed.More precisely, we make the following assumption: Assumption 2.1.For all ∈ ′ 0 and ∈ 0 we assume that system (8)-( 9) admits a unique weak solution (, ) ∈ 0 × 0 and that there exists a constant > 0 depending only on , and Ω such that × is small enough, then the Lax-Milgram lemma implies that Assumption 2.1 holds.The assumption of smallness on ∇ is a sufficient condition, there are reasons to believe that Assumption 2.1 holds in more general cases.In the homogeneous case (which corresponds to = 0 in (1)- (2) or to = 0 and = 0 in ( 8)-( 9)), a solution (, ) satisfies a three-balls inequality which only involves the 2 norm of the velocity.This three-balls inequality result is stated in [35] (with their notations, corresponds to and to ∇ ).Theorem 2.2.(Conditional stability for the linearized Navier-Stokes problem).Let ∈ ′ 0 , ⊂ Ω and ∈ be given.For all ⊂⊂ Ω, there exist > 0 and 0 < < 1 such that for all (, ) ∈ [ 1 (Ω)] × 1 (Ω) solution of ( 8)- (9).
Proof.For the proof we refer the reader to [9, Appendix A].Theorem 2.2 provides a conditional stability result for ill-posed problems [1] in the sense that, for this estimate to be helpful, it must be accompanied by an a priori bound on the solution on the global domain (due to the presence of ‖‖ on the right-hand side).Specifically, Theorem 2.2 implies that a solution (, ) in [ 1 (Ω)] × 1 (Ω) of problem ( 6) and (7), must be unique.For the pressure uniqueness holds up to a constant.Moreover, in inequality (11), the exponent depends on the dimension , the size of the measure domain and the distance between the target domain and the boundary of the computational domain Ω.
Stabilized finite element approximation
In this section, we first introduce a discretization of problem (13) using a standard finite element method.Then, the discrete inverse problem is reformulated as a constrained minimization problem in the discrete space where the regularization of the cost functional is achieved through stabilization terms.Finally, the estimation of the error between the exact continuous solution and the discrete solution of our minimization problem is stated in Theorem 4.12 which corresponds to our main theoretical result.
Let {T ℎ } ℎ be a family of affine, simplicial meshes of Ω.For simplicity, the family {T ℎ } ℎ is supposed to be quasi-uniform.Mesh faces are collected in the set F ℎ which is split into the set of interior faces, F int ℎ , and of boundary faces, F ext ℎ .For a smooth enough function that is possibly double-valued at ∈ F int ℎ with = − ∩ + , we define its jump at as [] =: − − + , and we fix the unit normal vector to , denoted by , as pointing from − to + .The arbitrariness in the sign of [𝑣] is irrelevant in what follows.
We next define a piecewise polynomial space as where P ( ), ≥ 0, is the space of polynomials of degree at most over the element .Further, define a conforming finite element space as For the analysis below the polynomial degrees of the above spaces may be chosen as ≥ 1, 1 ≥ 1, 2 ∈ {max{1, − 1}, } and 3 ≥ 1 and the convergence order will be given in terms of .To make the notation more compact we introduce the composite spaces V ℎ := ℎ × 0 ℎ and W ℎ := ℎ × ℎ .We may then write the finite element approximation of (13): Find ( ℎ , ℎ ) ∈ V ℎ such that (( ℎ , ℎ ), ( ℎ , ℎ )) = ( ℎ ), (14) for all ( ℎ , ℎ ) ∈ W ℎ .Let us introduce the measurement bilinear form to take into account the measurements on given by (6).
where = max(, ‖ ‖ [ ∞ (Ω)] × ℎ) and > 0 will correspond to a free parameter representing the relative confidence in the measurements.The objective is then to minimize the functional under the constraint that ( ℎ , ℎ ) satisfies (14).
We now introduce the following discrete Lagrangian for ( If we differentiate with respect to ( ℎ , ℎ ) and ( ℎ , ℎ ), we get the following optimality system: for all ( ℎ , ℎ ) ∈ V ℎ and ( ℎ , ℎ ) ∈ W ℎ .However, the discrete Lagrangian associated to this problem leads to an optimality system which is ill-posed.To regularize it, we introduce stabilization operators that will convexify the problem with respect to the direct variables ℎ , ℎ and the adjoint variables ℎ , ℎ .We introduce The choice of stabilization terms will be discussed later.For compactness, we introduce the primal and dual stabilizers: for all ( ℎ , ℎ ), ( where and , , , and div are positive user-defined parameters.And for all ( ℎ , ℎ ), ( where * and * are positive user-defined parameters.Let us make some comments on these stabilization terms.The stabilization of the direct velocity acts on fluctuations of the discrete solution through a penalty on the jump of the solution gradient over element faces and has no equivalent on the continuous level.The form (•, •) is a Galerkin least squares stabilization.Let us mention that there is some freedom in the choice of dual stabilization, e.g.set * ( ℎ , ℎ ) = * ∫︀ Ω ∇ ℎ ∇ ℎ x.We will only detail the analysis for the first choice (23) below.We refer the reader to [13,15] for a more general discussion of the possible stabilization operators.
Stability and Error Analysis
To prove the stability of our formulations, we need the following result.
Lemma 4.1.There exists such that for all ℎ ∈ ℎ there holds Proof.The following Poincaré inequality is well known Lemma B.63 of [24].If : 1 (Ω) → R is a linear functional that is non-zero for constant functions then For instance, we may take As an immediate consequence we have the bound (27).
Let us prove that the discrete problem is well-posed.We can write the discrete formulation in a more compact form.
Using the above bounds to the componentwise extension of ℎ to vectorial functions, we deduce the following approximation bound.
In this section, we will present and prove several technical results.First observe that the formulation ( 25)-( 26) is weakly consistent in the sense that we have a modified Galerkin orthogonality relation with respect to the scalar product associated to : Lemma 4.7.(Consistency).Let (, ) satisfy ( 1) and ( ℎ , ℎ ) be a solution of ( 25)- (26).Then there holds Proof.The result follows by taking the difference between ( 13) and (25).
Proof.The approximation bounds can be deduced using the component-wise extension of ℎ to vector functions.
Proof.Let us derive the estimate (41).Using the definition of (•, •) : Consider the first term on the right hand side of (42).Using the Cauchy-Schwarz inequality and Poincaré inequality, The second term of (42) can be handled as: The last term of (42) can be handled as: Finally, the result follows by combining all the above estimates.
Lemma 4.10.We assume that the solution (, ) ∈ [ +1 (Ω)] × 2 0 ∩ (Ω) and we consider ( ℎ , ℎ ) ∈ V ℎ and ( ℎ , ℎ ) ∈ W ℎ the discrete solution of ( 25)- (26).Then there holds, Proof.We introduce the discrete errors The first term of (44) can be handled by using the Lemma 4.8.Consider the second term of ( 44) To estimate the right-hand side, we notice that, using the second equation of ( 26) with ( ℎ , ℎ ) = ( ℎ , ℎ ) Using Lemma 4.7, we obtained Adding ( 45) and (46), We bound the terms (1)-( 3) term by term.The first term is handled by using Lemma 4.9 Consider the second term on the right hand side of (47) We now estimate the terms on the right hand side of (49).Using the 1 -stability of ℎ , the first term of (49) can be handled as: .
The last term can be handled as: Put together (47) leads to The combination of the above estimates concludes the claim.
Corollary 4.11.Under the same assumptions as for Lemma 4.10, there holds and Proof.Using Lemma 4.10, we see that The estimate (51) is immediate by using the triangle inequality and the estimate (50).
The following theorem is the main theoretical result of the paper and states an error estimate for this method.
We introduce ℎ and ℎ being fixed.The linear forms and on 0 and respectively defined by: For all ∈ 0 and ∈ ⟨ , ⟩ ′ 0 , + ( , ) := (, ) − (( ℎ , ℎ ), (, )). (53) It follows that (, ) is the solution of ( 8)-( 9) with and in the right hand sides replaced respectively by and .Applying now Corollary 2.2, we directly get Using (25), we can write the residuals: for all ( ℎ , ℎ ) We take ℎ = ℎ and ℎ = ℎ in (55).Now, let us estimate the terms on the right hand side of (55).Consider the first two terms of (55) Applying an integration by parts to the first two terms of (56) and using Lemma 4.10, The last term is handled using the Cauchy-Schwarz inequality and Lemma 4.10, Applying the above bounds in (56) leads to The last term of (55) is handled using Lemma 4.10 As a consequence we can bound the quantity defined in (55) by Since this bound holds for all ∈ 0 and ∈ , we conclude that Using the Poincaré inequality ( 27), we have the bound Thus, we can bound the terms in the right-hand side of (54) in the following way: and Using these two bounds in (54), we conclude that which completes the proof of the theorem.
Numerical simulations
In this section, we use several two-dimensional numerical examples to apply the methodology described in Section 3.All experiments have been implemented using the open-source computing platform FEniCSx [2,37].A docker image to reproduce the numerical results is available at https://doi.org/10.5281/zenodo.7442458.The free parameters in ( 25)-( 26) are set to In all the numerical examples.In the first example we will verify the convergence orders for different polynomial orders using equal order interpolation for all variables.Then we consider the same test case using the minimal polynomial order that results in the same error bounds, 1 = 1, 2 = max{ − 1, 1} and 3 = 1.Finally, we study the robustness of the error estimate with respect to the viscosity for a configuration where the target subdomain is strictly downwind the data subdomain , so that every point is on a streamline intersecting .
Convergence study: Stokes example
To demonstrate the convergence behaviour of the method introduced in Section 3, we take the test case for the Stokes problem from [17].Let Ω = [0, 1] 2 be the unit square.We consider the velocity and pressure fields given by It is simple to demonstrate that (, ) is a solution to the homogeneous Stokes problem with = 1, corresponding to the system (1)-( 2) with = 0 and = 0.As a result, we consider ( 25)-( 26) with = 0 and = 0. Two different geometric settings are considered: one in which the data is continued in the convex geometry, inside the convex hull of , and one in which the solution is continued in the non-convex geometry, outside the convex hull of .The convex geometry represented by Figure 1a is given as: We begin by performing the computation using unperturbed data.The relative 2 -norm errors ‖ − ℎ ‖ [ 2 ()] / ‖‖ [ 2 ()] are computed in the subdomain .In addition, we present the history of convergence of the residual quantity for velocity stabilization: .
Figure 2 displays the velocity, pressure errors and residual quantity in the convex and non-convex geometry.Filled squares, circles and triangles represent the velocity errors; dashed lines represent the pressure error, and the plain thin lines represent the residual.The expected order of convergence is observed for the residual in Lemma 4.10.The local velocity error behaves consistently with the convergence rates obtained in Theorem 4.12.We can also see in Figure 2 that the higher order polynomials are more satisfactory for ill-posed problems.Next, we proceed with the numerical verification of the above method with data perturbation.Consider the perturbed data = | + , with random perturbations for some ∈ N 0 available for implementing our method.According to Theorem 4.12, we have the estimate consequently, convergence requires the condition − > 0. Figures 3-4 present the convergence history of the velocity, pressure and residual quantities with the data perturbation in the convex and non-convex geometry, respectively.The effect of different values of for relative 2 -error are studied in Figures 3-4.The relative error for = 0 is displayed in Figures 3a and 4a.In both cases, the results are in agreement with the Theorem 4.12.
As stated in (65), the = 1 polynomial approximation may diverge for = 1, which is confirmed by Figure 3b.
Next, the method = 2 converges linearly, whereas = 3 still manages to converge, albeit at a slower rate.As shown in the Figure 3c, this result is consistent with the fact that for = 2, convergence is no longer observed for any ≤ 3. Similar convergence results are observed in the non-convex domain as shown in Figure 4.The results of Figures 3-4 indicate that for the convex geometry ≈ 1 and for the non-convex geometry ≈ 2 3 .In Figures 5-7 the same results are presented for the case where the minimal polynomial order is considered that is 1 = 1, 2 = max{ − 1, 1}, 3 = 1.The results are very similar and we conclude that for these numerical examples there is no disadvantage in taking the smallest possible dual space.
Convergence study with varying viscosity
In this subsection, we consider the flow of a viscous Newtonian fluid between two solid boundaries at = , − driven by a constant pressure gradient.The source term is chosen such that the solution of the plane (a) As in the previous section, we have examined the convergence of the method by performing numerical tests on both unperturbed and perturbed data.We vary the viscosity between = 1 and = 0. Observe that since no boundary conditions are imposed nothing needs to be changed in the formulation in the singular limit.Also note that the choice of and in ( 20)-( 21) mimicks the choice for the stabilized method for (the well-posed) Oseen's problem used to improve robustness in the high Reynolds limit.Also with reference to high Reynolds computations for the well-posed case we here consider equal order interpolation for all fields.We wish to explore if the results on stability for the unique continuation for convection-diffusion equations in the limit of small diffusivity [19,20] carry over to the case of incompressible flow.The key observation there was that for smooth solutions to the convection-diffusion equation the method had Hölder stable error estimates when diffusion dominates, similar to the analysis above, but in the convection dominated regime the stability in a subdomain slightly smaller than that spanned by the characteristics intersecting the data zone is Lipschitz.In that zone the convergence for the ill-posed problem coincides with that of the well-posed problem for piecewise affine approximation.As a means to study the effect of incompressibility we compare with the case where in addition to in , is also provided as data in Ω.The proposed method can be modified to accommodate this case by including 1 2 ‖ ℎ − ‖ Ω , as an additional term in the Lagrangian (17).Note that when the pressure is added the velocity pressure coupling is strongly reduced.The relative 2 -errors for running the same problem as above are displayed in Figure 9. Left side plots of Figure 9 show the results without adding any additional pressure term, and right side plots of Figure 9 display the results by including the pressure data.We observe that the results with pressure information are consistently better than those without.In particular for high order polynomials and high Reynolds number the information on the pressure appears to provide a very strong enhancement of the stability.Further, the effect of data perturbations for different values of the viscosity coefficient is studied with and without the pressure augmentation, see Figures 10-11.We observe that if a priori information on the pressure is added and viscosity is reduced the convergence order for the relative 2 -error increases.This is consistent with the results of [19,20].If the pressure is not added however we do not observe this effect and it appears from these computational examples that we can not expect the result from [20] to hold for linearized incompressible flow.
In Figure 10-11 we present the results under perturbations of data.These results show that the robustness under perturbations is also substantially enhanced if the pressure is known, indicating that the pressure velocity coupling introduces a strong sensitivity to perturbations.
Conclusions
We have introduced a finite element data assimilation method for the linearized Navier-Stokes' equation.We proved the natural extension of the error estimates of [9] valid for piecewise affine approximation to the case of arbitrary polynomial orders.The expected increase in convergence rate was obtained, but the estimates also show that the sensitivity of the system to perturbations in data increase.The theoretical results were validated on some academic test cases.The main observations are that high order approximation for the illposed linearized Navier-Stokes' equations pays off, at least for sufficiently clean data.The spaces for the dual variables on the other hand can be chosen with piecewise affine approximation without loss of accuracy of the approximation.A study where the viscosity was varied showed that the incompressibility condition and the associated velocity-pressure coupling severely compromise the convective Lipschitz stability that is known to hold in the zone in the domain defined by points on the characteristics intersecting the data zone.If additional data in the form of global pressure measurements were added the results improved and were similar to the those of the scalar convection-diffusion equation.Future work will focus on the nonlinear case and the possibility of enhancing stability by adding knowledge of some other variable than the pressure, such as for example a passive tracer as in scalar image velocimetry [18].
Figure 1 .
Figure 1.Sketch of the domains used for computations in Section 5.1.(a) Convex geometry.(b) Non-convex geometry.
Figure 2 .
Figure 2. Relative error for geometrical setup displayed in Figure 1.(a) Errors for convex geometry in Figure 1a.(b) Errors for non-convex geometry in Figure 1b.
Figure 5 .
Figure 5. Relative error with using the minimal polynomial order for geometrical setup displayed in Figure 1.(a) Errors for convex geometry in Figure 1a.(b) Errors for non-convex geometry in Figure 1b.
Figure 6 .
Figure 6.Relative error with using the minimal polynomial order for geometrical setup Figure 1a in terms of the strength of the data perturbation.(a) = 0. (b) = 1.(c) = 2.
Figure 7 .
Figure 7. Relative error with using the minimal polynomial order for geometrical setup Figure 1b in terms of the strength of the data perturbation.(a) = 0. (b) = 1.(c) = 2.
Figure 8 .
Figure 8. Data set and error measurement regions (B). | 5,982.2 | 2023-01-13T00:00:00.000 | [
"Engineering",
"Mathematics",
"Physics"
] |
Prediction of potential disease-associated microRNAs by composite network based inference
MicroRNAs (miRNAs) act a significant role in multiple biological processes and their associations with the development of all kinds of complex diseases are much close. In the research area of biology, medicine, and bioinformatics, prediction of potential miRNA-disease associations (MDAs) on the base of a variety of heterogeneous biological datasets in a short time is an important subject. Therefore, we proposed the model of Composite Network based inference for MiRNA-Disease Association prediction (CNMDA) through applying random walk to a multi-level composite network constructed by heterogeneous dataset of disease, long noncoding RNA (lncRNA) and miRNA. The results showed that CNMDA achieved an AUC of 0.8547 in leave-one-out cross validation and an AUC of 0.8533+/−0.0009 in 5-fold cross validation. In addition, we employed CNMDA to infer novel miRNAs for kidney neoplasms, breast neoplasms and lung neoplasms on the base of HMDD v2.0. Also, we employed the approach for lung neoplasms on the base of HMDD v1.0 and for breast neoplasms that have no known related miRNAs. It was found that CNMDA could be seen as an applicable tool for potential MDAs prediction.
miRNAs functional similarity (MFS), Xuan et al. 22 proposed a prediction model via implementing random walk on constructed miRNA functional similarity network in which they assigned larger transition weights to marked nodes. At last, probability association scores of each disease-miRNA pair would be obtained and ranked. A calculation model was further built by Chen et al. 17 in which miRNA's k-nearest-neighbors (KNNs) and disease's KNNs were respectively searched and then these KNNs would be ranked according to support vector machine. After that, they finally got all potential MDAs with weighted voting. Under the framework of semi-supervised learning, a novel model 23 was presented for MDAs prediction via combining the optimal solutions in the miRNA space and disease space. Recently, Chen et al. 24 proposed another prediction model through calculating within-score and between-score for both miRNAs and diseases which were then combined to obtain the final MDA scores. Also, researchers put forward some other calculation approaches via considering relevant genes or proteins as a bridge to predict novel MDAs. For example, using a discrete probability distribution of hypergeometric, Jiang et al. 25 presented a prediction model on the basis of the constructed integrated network. By connecting miRNAs to diseases with the proteins as a bridge between them, a calculation model was employed by Mork et al. 26 through using a scoring scheme, which can greatly increase the model's efficiency. Furthermore, Shi et al. 27 implemented random walk on a built protein similarity network to identify MDAs.
By combining the known MDAs network and MFS network, a new calculating method was studied by Chen et al. 28 by the analyzed of random walk with restart (RWR). It is worth noting that RWR is a very effective model for MDAs prediction. By adopting RWR, a novel model named Composite Network based inference for MiRNA-Disease Association prediction (CNMDA) was presented in the light of a multi-level network which was built by combination of Gaussian interaction profile kernel similarity (GIPKS) for lncRNAs, integrated similarity for miRNAs (ISMs) and diseases (ISDs), known MDAs, lncRNA-disease associations (LDAs) and miRNA-lncRNA interactions (MLIs). In addition, leave-one-out cross validation (LOOCV) and 5-fold cross validation were adopted in this paper to assess CNMDA's effectiveness. It could be seen that the AUCs of LOOCV and 5-fold cross validation were respectively 0.8547 and 0.8533+/−0.0009. As for case studies, CNMDA was carried out on kidney neoplasms (KN), breast neoplasms (BN) and lung neoplasms (LN) to infer its associated miRNAs based on HMDD v2.0 29 . Also according to HMDD v2.0, we further infer novel miRNAs for BN after hiding its known associated miRNAs. At last, we carried out the case studies based on HMDD v1.0 30 to infer LN-related miRNAs. Based on the above results, the effectiveness of CNMDA for MDAs prediction was validated.
Results
Cross validation. In this paper, we carried out LOOCV and 5-fold cross validation to assess CNMDA's prediction accuracy according to HMDD v2.0 29 and then made comparison between CNMDA and four other classical computational models: RLSMDA 23 , HDMP 21 , WBSMDA 24 and RKNNMDA 17 (See Fig. 1). In LOOCV, test sample is one of the 5430 MDAs; training samples are the rest of 5429 known MDAs; candidate samples are those unlabeled 184155 miRNA-disease pairs. When each known MDA was taken to be the test sample, we would get association scores for all miRNA-disease pairs after implementing MCMDA and then the ranking of test sample among the candidate samples would be gained based on their association scores. We would say that the model makes a correctly prediction if the test sample ranked higher than the set threshold. Case studies. Three different case studies were also implemented to assess CNMDA' performance. In the first case study, CNMDA was employed to predict KN-related miRNAs based on HMDD v2.0. Further, another two reliable MDA databases (dbDEMC and miR2Disease) would be utilized to validate the top 50 identified outcomes. In the second case study, we respectively inferred BN-associated miRNAs and BN-associated miRNAs after removing all known BN-associated miRNAs in HMDD v2.0. In the third kind of case studies, CNMDA was adopted to predict for LN according to associations in HMDD v1.0 and v2.0, respectively. KN is a disease caused by cellular metabolic disorders 31 . If kidney tumors are detected and treated early and localized in the kidney, Patients would have a good disease-specific survival rate. Otherwise, patients have only an 18% two-year survival rate when they present with terminal disease 32 . With recent researches and studies, about two hundred and fifty thousand renal tumor patients are newly diagnosed annually, and KN' morbidity and mortality continue to increase 33 . Many miRNAs related to KN have been found based on a large number of biological experiments. For example, in renal cell carcinoma (RCC), up regulation of miR-21 is related to kidney cancer that with lower survival rate 34 . Through targeting MMP-9 in RCC, miRNA-133b can suppress cell proliferation, migration and invasion 35 . Finally, we implemented CNMDA for potential KN-related miRNA prediction. It was found that 8 of the first 10 and 37 of the first 50 miRNAs were verified (See Supplementary Table 1). we also provided the whole scores of potential MDAs on the base of HMDD v2.0 (See Supplementary Table 2).
BN is a major chronic disease affecting adult women and detected breast neoplasms can be removed surgically 36 . However, if people with BN have not been detected, BN may develop into a life-threatening clinical recurrence in the next 5, 10, 15, or more years 37 . Recent experimental studies have provide evidences that miRNA-195 may work as latent biomarker for early BN detection 38 . To find the novel biomarkers for BN for the treatment of the disease is significant. In the second, we employed CNMDA for potential BN-related miRNA prediction. It was found that 5 of the first 10 and 31 of the first 50 miRNAs were verified (See Supplementary Table 3). Also, we implemented CNMDA for the prediction of BN by hiding all its confirmed associations in HMDD v2.0. This means that we would remove all known BN-associated miRNAs and predict potential BN-associated miRNAs based on other known associations and corresponding similarity information. Supplementary Table 4 presents the top 50 predicted outcomes and their verification evidences. As a result, 9 of the first 10 and 41 of the first 50 miRNAs were confirmed (See Supplementary Table 4).
LN is the primary reason of cancer deaths on a global scale 39 . The genetic and epigenetic damage caused by tobacco smoke is the main cause of the disease 40 . Obviously, it is urgent to find a more therapy systemic 39 . In squamous cell carcinoma, miR-126 have been verified to be down regulated and two miRNAs of miR-185 * , miR-125a-5p were up regulated 39 . MiR-205 were expressed differently in the non-small cell lung carcinoma (NSCLC) 40 . In order to test the stability of CNMDA, we employed CNMDA based on the associations in HMDD v2.0 and HMDD v1.0 30 , respectively. It was found that 20 and 28 of first 50 associated miRNAs for LN have been verified, respectively (See Supplementary Tables 5 and 6).
As seen in the results above, we can arrival at a conclusion that CNMDA possesses excellent predictive performance for the novel MDAs prediction.
Discussions
As overwhelming evidences expounded that miRNAs are participated in all sorts of diseases. The development of new calculation approaches for predicting MDAs in a short time is important to further experimental validation. Accordingly, it is now possible to confirmed novel MDAs using biological experiments with low time and cost. Existing models are usually proposed based on four different calculation mechanisms 41 . Some scoring functions were constructed to prioritize disease-related miRNAs through carrying out probability distribution. Complex network algorithm-based prediction models were introduced through establishing complex network based on various data that are collected or calculated from different perspectives. Machine learning-based prediction models were introduced by using powerful machine learning algorithms. Moreover, multiple biological information-based models were put forward through constructing intermediate medium associations based on various biological datasets. We put forward the computing method of CNMDA to infer novel MDAs. In the model, we implemented RWR on a multi-level composite network that was built through combining collected and calculated data (ISD, ISM, GIPKS for lncRNAs, experimentally validated MDAs, MLIs and LDAs). From the evaluation results, it can be seen that the accuracy of our prediction model was superior in the comparison with other four models.
The main merits for the effective performance of CNMDA are as follows: Through taking advantage of multi-source information based on reliable database, it is no surprise that the integration strategy of CNMDA could predict potential MDAs effectively. Secondly, in comparison of local network information, RWR is an iterative process based on global network for the MDAs prediction. The attractive properties of global network information have been proved in the identification for potential disease-gene associations, MDAs 41,42 , LDAs 43 and drug-target interaction 44 . Furthermore, CNMDA could identify novel diseases that have no known associated miRNAs. At last, the implementation of CNMDA only needs positive samples as training data. Since there is no known negative sample information, the forecasting precision of CNMDA is more convincing. However, some limitations also exist in the computation model of CNMDA. For example, the number of experimentally determined MDAs, LDAs and MLI is insufficient. For the number of known MDAs, only 5430 known MDAs were collected. The more the known MDAs, the higher forecasting precision the model. Importantly, the current forecasting precision still needs to be improved according to the evaluation of LOOCV.
Methods
MiRNA-disease associations. Experimentally confirmed MDAs used in this paper were come from high-quality database 29 . Through constructing a adjacency matrix W dm to indicate the 5430 known MDAs, we made use of variables nm and nd to express the total amount of miRNAs and diseases in the known MDAs dataset, respectively.
dl MiRNA-lncRNA interactions. The known MLIs was from starBase v2.0 46 . In the same way, we need to delete excess MLIs whose miRNAs and lncRNAs do not exist in the 5430 known MDAs and 250 known LDAs. At last, 9088 known MLIs were gotten and an adjacency matrix W ml was used to refer to the 9088 MLIs.
where Δ is the semantic contribution decay factor. It is worthy of being mentioned that the value of contribution for disease D to its own semantic value is 1. The semantic value of disease D could be put forward.
At last, DSS1 between d(i) and d(j) can be described.
Disease semantic similarity model 2 (DSS2).
In the DSS2 48 , due to the fact that a more specific disease d appearing in less DAGs would contribute more to the semantic value of disease D. Accordingly, the contribution made by d for the semantic value of D can be described by Gaussian interaction profile kernel similarity. For disease d(u), we used IP(d(u)) to refer to row vectors of line u in W dm on the basis of known MDA. Through watching whether d(u) is related to each miRNA, we computed GIPKS for diseases d(u) and d(v) 50 . For lncRNA l(p) and l(q), GIPKS between them can be constructed. Similarly, the ISM between miRNAs m(i) and m(j) can be put forward by the integration of GIPK for miRNA and MFS 24 . studies of Yao et al. 51 Global information based on the multi-level network would be captured through RWR algorithm. At each steps, seed nodes move to their immediate neighbors with a probability δ − (1 ) or go back to the seed nodes with a restart probability δ. P 0 was put forward to denote the original probability vector, and P t+1 was introduced to represent a probability vector of node at step t + 1, which could be described by: where δ ∈ (0, 1) is a restart probability. In the multi-level network, the initial seed node probability M(i,j) represents the transition probability from i to j. In the network of GIPKS for lncRNAs, the transition probability from lncRNA i(l i ) to lncRNA j(l j ) was put forward. In the MDAs network, the transition probability from disease i d ( ) i to miRNA j m ( ) j was put forward. where x y z , , are the jumping probability between the network of GIPKS for lncRNAs and ISD network, between the network of GIPKS for lncRNAs and ISM network, and between ISD network and ISM network, respectively.
CNMDA is performed until the probabilities tend to a steady state, (the range between P t and P 0 computed by L 1 norm is smaller than 10 −6 ). Then, the candidate miRNAs can be ranked according to ∞ w . By incorporating MLIs and LDA into MDAs prediction, RWR was put forward on a constructed multi-level network to infer novel MDAs. In the network, because initial MLIs, LDAs and MDAs have more credibility, they all as weights in the RWR equations. Obviously, the one interaction and two associations play an equally important part in the network to disseminate information of miRNAs, diseases and lncRNAs for the novel MDAs prediction. In this study, we chose the same parameter as the one in previous literature 51 , which used RWR on the same multi-level composite network in their study. Therefore, we set the parameter δ to 0.7 and x, y, z, α, β to 1 3 . | 3,407.6 | 2018-10-25T00:00:00.000 | [
"Biology"
] |
A generalized estimating equations approach to quantitative trait locus detection of non-normal traits
To date, most statistical developments in QTL detection methodology have been directed at continuous traits with an underlying normal distribution. This paper presents a method for QTL analysis of non-normal traits using a generalized linear mixed model approach. Development of this method has been motivated by a backcross experiment involving two inbred lines of mice that was conducted in order to locate a QTL for litter size. A Poisson regression form is used to model litter size, with allowances made for under- as well as over-dispersion, as suggested by the experimental data. In addition to fixed parity effects, random animal effects have also been included in the model. However, the method is not fully parametric as the model is specified only in terms of means, variances and covariances, and not as a full probability model. Consequently, a generalized estimating equations (GEE) approach is used to fit the model. For statistical inferences, permutation tests and bootstrap procedures are used. This method is illustrated with simulated as well as experimental mouse data. Overall, the method is found to be quite reliable, and with modification, can be used for QTL detection for a range of other non-normally distributed traits.
INTRODUCTION
Various methods have been developed to detect a quantitative trait locus, ranging from the simpler regression based and method of moments, to maximum likelihood and Markov Chain Monte Carlo methods. These methods are mostly based on a continuous (normal) distribution of the trait. However, many traits of scientific and economic interest have a non-normal distribution. For example, binary data are frequently encountered with disease status, mortality, etc.
Count data occur in animal litter size and ovulation rate studies. Ordinal data (e.g. calving ease) and purely categorical traits are also encountered.
During the 1970s and 1980s, the generalized linear model (GLM 1 ) was developed as a uniform approach to handling all these above classes of data [27], and these procedures are now included in most major statistical packages. These methods would be applicable if data could be modeled as coming from one of the distributions of the exponential family (including Poisson for counts, binomial for binary and proportions data, as well as the normal distribution). Departures from the nominal variance-mean relationships can be handled by introducing additional dispersion parameters [27], and using a quasi-likelihood instead of the standard likelihood [43].
However, standard GLMs consider fixed effects only, and do not allow for any correlation structure in the data. Since the late 1980s, various methods have been developed to extend these GLMs to include the additional correlation structures [4,8]. One way to classify such extended GLMs is whether or not additional random effects are included in the model to take account of the correlation. When included, the type of model is usually termed a generalized linear mixed model (GLMM), or otherwise a marginal model. Another split in the type of approach is whether or not full parametric modeling is assumed. Specification of a full probability model for these extended GLMs usually involves numerical integration to evaluate the likelihood [4,28], or computer simulation if Markov Chain Monte Carlo methods are used [45]. An alternative approach has been developed that only makes assumptions about means, variances and covariance structures. This approach, known as generalized estimating equations (GEEs) was pioneered in the human epidemiology and biostatistics field [23,31], and a recent paper by Lange and Whittaker [21] has introduced this method to the field of QTL detection. The GEE approach and will be the basis in this paper for developing QTL models for non-normal data, although a somewhat different method of implementation will be used.
Models to detect QTLs differ fundamentally from the standard statistical linear models (LM), linear mixed models (LMM), as well as the models for non-normal data mentioned above (GLM and GLMM). The unobserved QTL genotypes result in a "missing data" problem, and general mixture methods are used to fit such models, frequently using the E-M algorithm [6,15,16,24].
Although the vast majority of QTL methodology papers are concerned with normally distributed traits, a minority do consider methods for non-normally distributed traits. Jansen's [15,16] general mixture methods provide a framework for modeling such traits as a finite mixture of GLMs. Visscher et al. [40] developed methods for analyzing binary traits from inbred lines, while Xu and Atchley [44] and Kadarmideen et al. [18] considered methods for outbred lines. Hackett and Weller [12] outlined a method for detecting a QTL for traits with an ordinal scale, by means of finite mixture modeling of an underlying liability measure. Other methods for ordinal QTL analysis have been proposed by Rao and Xu [33] and Spyrides-Cunha et al. [36].
The LMM -and in particular BLUP methodology -is central to both the theory and application of animal breeding [14], and these methods have been adapted to QTL detection [29,30,39]. Particularly through the use of Markov Chain Monte Carlo methods, complex pedigree structures are now routinely taken into account, at least for normally distributed traits [2,42].
The current paper provides a framework for QTL detection for non-normal traits with the addition of random polygenetic and/or environmental effects, and is an expansion of the method presented previously by Thomson [38]. This research has been motivated by finding a QTL for litter size in mice, a discrete (non-normal) variable. The method is general enough to be applied to other non-normal traits, especially within the context of inbred lines, and with certain modifications, to outbred lines. However, the method will be derived in terms of the mouse litter size model.
GENETIC EXPERIMENTAL DESIGN AND ASSUMPTIONS
Two inbred strains of mice were available, a highly prolific IQS5 (Inbred Quackenbush Swiss Line 5) strain (labeled S 1 here), and a regular C57BL/6J strain (labeled S 2 ). Their mean litter sizes were 15.5 and 7.0 pups respectively. Both strains can be assumed to be homozygous for all genes, at least for those relevant for the current analysis. These strains were crossed (F 1 generation), then backcrossed with both S 1 and S 2 males yielding BC 1 (= S 1 × F 1 ) and BC 2 (= S 2 × F 1 ). Each backcross female was then mated with a standard reference line of males on four occasions, and the litter size (and other phenotypic data) was recorded at each of the four parities. In addition, each backcross female was genotyped with 66 markers distributed over 18 chromosomes. Further details of the experimental procedures can be found in Silva [35] and Maqbool [25].
We will assume that there is a single QTL gene Q with alleles Q and q responsible for litter size. Similarly, we will denote the set of markers as M k ; k = 1, 2, . . . with alleles M k and m k . Thus we are assuming that parental S 1 genotypes are all QQ and M k M k while all S 2 genotypes are all qq and m k m k . All F 1 individuals are consequently heterozygous for all genes, Qq and M k m k . Genetic heterogeneity occurs in the backcrosses (BC 1 : QQ or Qq at Q; M k M k or M k m k at M k ; and for BC 2 : qQ or qq at Q; m k M k or m k m k at M k ). Relative frequencies of recombinant events (between QTL and markers) are then used to estimate the QTL location, based on flanking-marker methods (in the body of a chromosome) and single-marker methods (at the end of a chromosome).
Model for litter size
The basic model for litter size is a Poisson regression model. However, since there is empirical evidence that the variance:mean ratio is not unity, and that this ratio varies with parity, a dispersion parameter is included for each parity.
Rather than a full parametric model specification, only the first two moments are specified. The conditional means and variances are: where Y ij = litter size; µ = overall constant; α i = fixed parity effect (i = 1, . . . , 4); u j = random animal effect ( j = 1, . . . , n); q j = unobserved QTL genotype indicator variables; γ = (γ QQ , γ Qq , γ qQ , γ qq ) = QTL effects; and φ i = parity − specific dispersion parameter. Note that the terms of the model are additive on a logarithmic scale, i.e., and hence this type of model is also termed a log-linear model [27]. In particular, the effects become multiplicative when back-transformed to the original scale. For example, assuming that α 4 = 0 (parity 4 is reference group), then parity 1 has exp(α 1 )× the number of mouse pups on average, compared with parity 4. The QTL effects, γ, are provided to cater for the four possible QTL genotypes, with genotypes QQ and Qq originating from BC 1 and qq and qQ originating from BC 2 . Note that we do not assume γ Qq = γ qQ since these heterozygous genotypes also have different amounts of background genes coming from the appropriate parental strain (BC 1 has 75% of genetic material originating from S 1 compared with 25% originating from S 1 for BC 2 ). This issue will be discussed in detail later. The unobserved q j may be one of two forms, say q (1) j or q (2) j , with probability of 1/2 for either form, where superscript (1) and (2) indicate the homozygous and heterozygous forms of Q respectively. The observations y ij are assumed to be conditionally independent, given the random animal effect (u j ) and QTL genotype (q j ) and it is also assumed that random effects are normally distributed, u j ∼ N(0, σ 2 U ). It will also be useful subsequently to write the model in a matrix "regression"type form. We write the observed data set as a vector y = (y 1 , y 2 , . . . , y n ) where y j = (y 1j , y 2j , y 3j , y 4j ) . The conditional mean vector is: where u ∼ N(0, σ 2 U I n ); X = design matrix for fixed parity effects; Z = design matrix for random animal effects; and Q = random QTL incidence matrix = (q 1 , q 2 , . . . , q n ) .
In the current application with four records per animal, Z = I n ⊗ 1 4 where ⊗ is the Kronecker product.
An alternative parameterization for the QTL effects
Although it is computationally convenient to parameterize the QTL effects as γ = (γ QQ , γ Qq , γ qQ , γ qq ) (with γ qq = 0), a more useful and interpretable parameterization is to use an extension of the Falconer notation [9], by introducing additive (a) dominance (d) and a backcross effect (b). The backcross effect would act as a "bucket" to account for any additional genes affecting litter size not accounted for by the QTL gene Q. Specifically, the re-parameterization involves setting: where µ is a new overall constant. Note that γ = (γ QQ , γ Qq , γ qQ , γ qq ) is over-parameterized, and that we may set γ qq = 0, so both methods involve three estimable QTL parameters. Again, these effects operate on the log mean scale.
Marginal modeling approach
Since there are relatively few observations per animal for estimating the u j , a marginal modeling approach is used here whereby the dispersion components will be estimated, rather than the individual random effects. An approach similar to that in McCullagh and Nelder ( [27], p. 332) will be used.
Firstly, the dependence on the random effects is removed yielding: The covariance of litter size within an animal (i.e., across parities) is Next, the unknown QTL genotype dependence can be removed. Let µ (1) ij and µ (2) ij be the two possible mean litter sizes, E Y ij |q j , depending on the particular QTL genotype indexed by q j . In particular, µ (1) ij is the mean for the homozygous QTL and µ (2) ij is the mean for the heterozygous QTL. Let π j be the probability for a homozygous QTL genotype for animal j, given the marker genotype(s), m j . This will depend on the recombination fraction between the QTL and single marker (r) or flanking markers (r 1 , r 2 ) which in turn depends on the location of the QTL on the chromosome (d Q ). So the conditional moments, given the marker information, are These results may be expressed in matrix notation as E(Y|M) = µ(Ω) and Note that V has a block diagonal structure, with each block, V j say, corresponding to the four records for each animal y j .
QTL genotype probabilities
For backcross 1, two QTL genotypes are possible, QQ and Qq, whereas for backcross 2, qQ and qq are possible. The QTL genotype probabilities are defined as the probabilities of obtaining the homozygous genotype, given the marker genotype(s) m j of the animal, i.e., For a single marker model, let r be the recombination fraction between the QTL Q and a marker M. Then: For a flanking marker (interval mapping) model, let (0 ≤ d ≤ L) represent the map position on a chromosome of length L, and assume the QTL is located between adjacent markers, M 1 and M 2 , say. Let the positions of the markers and QTL be d 1 , It is assumed that d 1 and d 2 are known without error. Then assuming Haldane's [13] mapping function, we have: and where r 1 and r 2 are the recombination fractions between the two markers and the QTL respectively. In this case, the QTL genotype probabilities are
PARAMETER ESTIMATION
Since the model is not fully parametric, maximum likelihood cannot be used, and we consequently use a generalized estimating equations (GEE) approach [4,11,21,23,27] in which the quasi-likelihood takes the place of the log-likelihood [27,43]. There are two sets of parameters to be estimated, a set of "location" effects, θ = (µ, α , γ ) , and a set of "dispersion" effects, , and so the vector of all parameters is Ω = (θ , ψ ) . In particular, we solve two sets of GEEs simultaneously, one for each of the sets of effects, and this is known as the GEE2 approach [31,32]. Note that these GEEs are the analog of the likelihood estimating (score) equations for maximum likelihood estimation, and the normal equations for standard linear models. A set of linear GEEs is used to estimate θ and a set of quadratic GEEs used to estimate ψ. For this second GEE, we define the following quadratic variables for animal j, 1j , y 1j y 2j , y 1j y 3j , y 1j y 4j , y 2 2j , . . . , y 2 4j . The y j are the data that provide information on location effects, while the z j are the data that provide information on the dispersion (variance, covariance) effects. The following two sets of nonlinear equations are then solved, Expressions for ν j can be obtained by using standard results, namely, that . However, analytical expressions for W j are more difficult as they require further assumptions to made about 3rd and 4th order moments of Y ij . Prentice and Zhao [32] have outlined some possible choices and guidelines for choosing appropriate W j . However, these authors as well as Diggle et al. [4] have noted that the estimation procedure is fairly robust against choices of W j . In the current application, an alternative is to provide an empirical estimate of W assumed common for all animals, i.e., where n Ω is the number of elements of Ω to be estimated (12 here), andν j is the estimate of ν j based onΩ, the current estimate of Ω. Such an approach will in part avoid specific moment assumptions being made.
The sets of GEEs can be solved iteratively using a Newton-Raphson method with Fisher scoring, where the superscript (i) indicates the estimates at the ith iteration.
Parameter estimation in interval mapping
In practice, we want to look for the evidence for a QTL at different map positions (d) along the length of a chromosome. Consequently, we fit the QTL model at each d using the above estimating equations, but leaving out the parameter d Q .
• For d = 0 to L in steps of ∆ d (usually 1 cM): solve the GEEs for a fixed value of d to obtain estimatesθ(d),ψ(d); calculate the quasi-score function for the QTL at position d; However, U(d) = 0 has multiple solutions along the length of the chromosome, corresponding to local maxima of a profile log-likelihood (see Fig. 1). One solution therefore is to calculate the profile log-likelihood of d given the data z j , assuming that z j is multivariate normal N(ν j , W j ), i.e.
ignoring the normalizing constant, where the ν j (and hence W j ) are evaluated using the parameter estimates at the current map position, d. Note that since we have not specified a fully parametric model for litter size, we cannot calculate the likelihood exactly. We are using the normal-based profile log-likelihood as a "first-order"approximation here. However, some independent support for this as a measure is provided by constructing a quasi-likelihood function, as follows.
In standard parametric models, the score function U(θ) for some parameter θ is related to the log-likelihood function L(θ) by means of U(θ) = ∂ ln L(θ)/∂θ, and hence log L(θ) = θ θ min U(t)dt + C for θ min ≤ θ ≤ θ max [3,4]. The same results hold when dealing with profile log-likelihoods and profile score functions. In a similar way, we can construct the profile quasi-likelihood function, say, where C is a normalizing constant. The integral U * (d) can be approximated by a simple cumulative sum approach, Note that as a general rule with GEEs for correlated data, it is not possible to reconstruct the quasi-likelihood function Q(θ) based on the quasi-score function U(θ) = D V −1 (y − µ) ( [27], p. 333). However, it is possible in the current context as we have reduced the parameter space to one dimension (d Q ) by means of a profile quasi-score function, is readily integrated to produce Q(d).
Consideration of an appropriate choice of the normalizing constant C will be considered later. Regardless of the choice of C, the global maximum of Q(d) is the parameter estimate of d Q , corresponding to a solution of U(d) = 0. However, based on simulation studies, it was found that using either L(d) or Q(d) to estimate the QTL location gives extremely similar results. Furthermore, the shape of the two functions is also extremely similar, especially for large numbers of sets of records (n), as shown in Figure 1.
TESTING FOR THE EXISTENCE OF A QTL
Using either L(d) or Q(d), the location of a QTL can be estimated. However there remains the issue of whether or not the QTL actually exists at this map position. To address this, a null model is fitted whereby both QTL parameters a and d are set to zero, i.e., γ QQ = γ Qq and γ qQ = γ qq (= 0). That is, only the backcross effect, b is assumed. Recall that this is used as a "bucket" term for the effects of genes other than Q.
To fit a model only involving backcross effects, the GEE2 approach is again used. However, this model is simpler in that it is a non-mixture model. Writing the backcross effect as γ 0 (= γ QQ = γ Qq ), and s j as a 0-1 indicator variable for backcross 1, the marginal moments of Y ij are Having estimated Ω 0 = (µ, α , γ 0 , σ 2 U , φ ) , the normal based log-likelihood corresponding to the z j is calculated, say L 0 . Hence a likelihood-ratio type test statistic can then be calculated along the length of the chromosome, as This may then be converted into a LOD score, i.e., LOD(d) = L R (d)/ ln (10).
A test statistic may also be constructed based on the quasi-likelihood function. To do this, we set the constant of integration C in such a way that the average of the Q(d) equals the average of the L(d), over the range 0 ≤ d ≤ L, i.e., set Using this choice of C, the quasi-likelihood test statistic may be interpreted like a likelihood-ratio test statistic; we shall label this test statistic Q R (d).
As a very crude measure, we may apply χ 2 approximations to the distribution of L R (d) (and Q R (d)) to assess the significance of the QTL at position d Q . That is we may test However, L R (d Q ) does not behave like an ordinary likelihood-ratio test statistic, as noted in other QTL studies [20,34]. An alternative method is to apply a permutation test to assess the significance of the QTL [5]. In the current model, this is achieved by randomly permuting the maker data m j with the phenotypic data y j . However, permutations must be done within each backcross group so as to preserve the backcross effects. Each permuted data set should contain the same numbers of BC 1 and BC 2 records as in the observed data set. Repeated permutations and subsequent model fitting allow the distribution of L R (d Q ) under H 0 to be obtained, and the significance of the observed L R (d Q ) can then be assessed as the upper tail percentile of the null distribution.
Similarly, the bootstrap can be used as a method to obtain a reliable 95% confidence interval for d Q as well as other parameters [7,41]. For this (unselective bootstrap) approach, we randomly select (with replacement) complete (m j , y j ) records, again using the same number of BC 1 and BC 2 records as in the observed data set. Confidence intervals are obtained based on the appropriate percentiles of the bootstrap distribution, and this can also be used to calculate approximate standard errors for parameter estimates. Further improvements to the confidence intervals could be obtained using a selective bootstrap approach which more closely emulates the actual mapping process [22].
Applying the GEE2 procedure, the interval map as shown in Figure 1 was obtained. As mentioned previously, there is an extremely close agreement between the two test statistic profiles, Q R (d) and L R (d). In addition, the estimated QTL location was essentially the same at 0.27 M, quite close to 0.3 M. Other parameter estimates were similarly quite acceptable:μ = 1.77,α = (−0.328, −0.129, 0.366, 0) ,γ = (0.753, 0.522, 0.231, 0) ,σ 2 U = 0.0935, and φ = (0.399, 0.920, 1.606, 2.118) . Note that these estimates are those based on the maximum L R (d), however estimates of µ, γ, σ 2 U and φ are nearly identical when the maximum of Q R (d) is used. Since the parity effects α are independent of the QTL, their estimates are identical for either criterion; furthermore their estimates do not change along the whole length of the chromosome. The maximum value of L R (d) was 38.06, and using asymptotic χ 2 methods gives P < 0.001 for a test of no linked QTL. As a check, a permutation test was conducted using 1000 permutations. As none of the permutations had a test statistic this large, we can again conclude that P < 0.001. Although these P-values agree, the overall distribution of L R (d) under H 0 is not well approximated by a 1/2χ 2 2 distribution. This is demonstrated in Figure 2 which shows the histogram of the distribution of L R (d) against the 1/2χ 2 2 . As would be expected from this permutation-based distribution with no linked QTL, the means of the QTL estimates for BC 1 were nearly identical (0.515 and 0.517 for γ QQ and γ Qq respectively), and the mean QTL estimate for BC 2 was nearly zero (0.0006 for γ qQ , recall γ qq = 0 by design).
If the 1/2χ 2 1 approximation is used, a 95% confidence interval for d Q is obtained as 0.23 M to 0.32 M. In comparison, a bootstrap confidence interval, based on 1000 bootstrap simulations, gives an interval of 0.23 M to 0.40 M, somewhat wider than the asymptotic theory estimate. However, the histogram ofd Q reveals a bimodality with 87% of the distribution occurring between the markers at 1/6 and 2/6 M, and the balance between 2/6 and 3/6 M (Fig. 3).
In addition, the bootstrap procedure may be used to obtain standard errors (as well as confidence intervals) of any parameter estimates of the model. For a parameter estimateθ of θ, its bootstrap standard error is calculated as: whereθ i is the estimate obtained from the ith bootstrap data set (i = 1, . . . , B), andθ is the mean of the B bootstrap estimates. Further, differences betweenθ from the original data andθ may be used to assess possible bias in the parameter Table I. For the current model and simulated data, it would appear no substantial bias in estimation does occur.
Estimates and standard errors for the alternative parameterization of the QTL effects (additive, dominance, and backcross terms) can be achieved as follows. Noting that: That is we obtainâ = 0.231 with se(â) = 0.0224,d = 0.000, with se(d) = 0.0265, andb = 0.146 with se(b) = 0.0166.
Mouse data
The method has been used to estimate QTL from the data provided by Silva [35] and Maqbool [25]. The most promising region for a QTL for litter The results for the analysis are presented here. The estimated QTL location was at the marker (40 cM) (see Fig. 4) and based on a permutation test was significant (P = 0.01); however there was an extremely wide bootstrap 95% confidence interval from 0 to 108 cM. It was apparent that insufficient mice were available for reliably locating a QTL. To evaluate the power for this design to detect a QTL, the permutation (no linkage) and bootstrap (with linkage) distributions were further utilized. The critical value for testing linkage is the upper 5% point of the test statistic L from the permutation distribution: 4.09 here. If we use the parameter estimates as though they were the actual parameter values, the bootstrap distribution provides the distribution under the alternative (linkage) hypothesis. Since only 30% of bootstrap simulations returned L ≥ 4.09, the power or this design to detect a QTL is estimated at 30%.
The other estimates obtained from the data wereμ
MONTE CARLO SIMULATION STUDY
A Monte Carlo study has been conducted to assess the performance of this procedure, particularly to assess the effect of varying the number of animals available. Each Monte Carlo study consisted of 1000 simulations using the parameters as specified in the Simulated data section of Numerical illustrations. Equal numbers of BC 1 and BC 2 animals were considered, with the number in each backcross group being 50, 100, 200, and 500. As well as simulating the linked situation (QTL at 0.3 M), an unlinked situation was also simulated, allowing the distribution of the test statistic under the no linkage hypothesis to be obtained, providing critical values for the calculation of power. Summary results are shown in Table II. In general, there is relatively little bias in parameter estimation, especially as the number of animals increases. Similarly, there are reductions in standard errors of parameter estimates as the number of animals increases. It is evident that QTL location is extremely difficult to estimate for small numbers of records: with 50 animals per backcross, the bias was +20% with a standard error of about 50% of the mean. This is also demonstrated in the power analysis: a power of less than 50% to detect the QTL when only 50 animals are used per backcross, compared with a power of approximately 80% when the number of animals are doubled. A further doubling results in almost certain detection of the QTL.
DISCUSSION AND CONCLUSIONS
It was mentioned previously that the method presented here could be modified for other non-normal data types. At a more general level, we can write a model in the form g[E(Y|u, Q)] = Xβ+Zu+ZQγ where g(·) is the appropriate link function for the class of data (ln for count, logit for binary, identity for normal). To fit the QTL model for different classes of data, relatively little needs to be modified. We need to: (1) Evaluate the moments (given the marker data), µ(Ω) = E(Y|M), and V(Ω) = var(Y|M). Note that approximations may need to be used here [27]. (2) Evaluate the derivative matrices, D and E.
Having calculated these, all the other theory developed here may be applied without modification.
As mentioned in the Introduction, Lange and Whittaker [21] have also described a QTL detection strategy using GEEs. The approach they develop stems from a generalization of a regression method, as opposed to from a likelihood-based mixture method. If the random animal effects were not included in the model, both the current model and the one proposed by Lange and Whittaker can be expressed as: where g(·) and g −1 (·) are the link and inverse link functions respectively. In the current approach, expressions for the mean response, conditional only upon marker information, were obtained, This contrasts the approach adopted by Lange and Whittaker, Their approach has the benefit that the expression E Q (Xβ + ZQγ|M) will be linear in the parameters (β, γ), and so the resultant structure for µ LW (θ) is a generalized linear model form, allowing implementation within standard GEE software. However, the expression for µ LW (θ) will only approximate the "true" mean expression, µ(θ), since in general, apart from when g(·) is the identity link used for standard linear models. It should be noted that E Q [g −1 (Xβ + ZQγ)|M] is nonlinear in the parameters, so does no longer fit within the usual generalized linear model framework, and consequently requires additional programming effort. Analogous differences can also be made between V(θ) and V LW (θ). Clearly, there is scope for further development of this class of model. As a method of QTL analysis, we need to allow for multiple QTL affecting the trait of interest by means of a composite interval mapping or allied approach [17,46]. This can be implemented in the current model easily by including additional (marker) terms in the "fixed effect" part of the model. Other scope exists for handling repeated measures (longitudinal) data by applying one of the techniques outlined in Diggle et al. [4]. In the litter size example considered here, no serial correlation in the data is assumed: the only correlation is assumed to originate from a common random animal effect (u j ) and common QTL effect (q j ). The illustrative data used here consist of sets of four repeat measurements per animal; with extended longitudinal data sets, this aspect would need to be addressed.
There are several alternative approaches that might be used for modeling litter size data. Firstly, a normal-based model might be used, perhaps after first making some transformation of the data to a more normal scale. However, this would fail to address the underlying discrete data distribution. While the litter size data had a relatively large mean -and consequently normal-based methods might have been a reasonable approximation -the method derived can be applied reliably for animals with smaller litter sizes, such as awassi sheep. Indeed the method can be used on any other count type trait.
Another approach is to model litter size on an ordinal scale, using the methods presented in Hackett and Weller [12]. While attractive in a number of ways, additional parameters need to be estimated for the ordinal scale, and it also fails to capture all the information, since litter size is a measurement scale variable. Ordinal scale analyses usually assume a continuous underlying liability scale with the cut points identifying the particular response category realized. The appeal of an underlying liability may also be assumed in the current approach outlined here. We may consider the (conditional) mean litter size E(Y ij |u j , q j ) as the liability from which the observed litter size is drawn. However, unlike the ordinal scale models, the actual realization is fully stochastic which is biologically more appealing than the extended all-or-none threshold approach of ordinal scale modeling.
Various parametric models have been used to analyze litter size data. Foulley et al. [10] and Matos et al. [26] have used Poisson based models. Templeman and Gianola [37] have added random effects and catered for over-dispersion by fitting negative binomial models to litter size data. To a certain extent, a similar approach was used in the model derived here. Namely, a basically Poisson regression approach was used; however under-as well as over-dispersion was allowed for in the model. In addition, the model was not fully parametric: only assumptions about means, variances, and covariances were made rather than a full probability model. Intuitively, this approach would be expected to be relatively robust against the true (but unknown) underlying probability model.
However, there are difficulties with applying these Poisson-based models to litter size and ovulation rate data. While they may fit the data well empirically, the assumptions that lead to a Poisson process [3] cannot be easily justified for this type of variable. What is required is a mechanistic model for litter size as opposed to a descriptive model. Considerable research has been undertaken on determining the biological determinants that contribute to ovulation rates and litter size [1,19]. Biological models such as these could form the basis for a mechanistic stochastic model of litter size. | 8,012.2 | 2003-05-15T00:00:00.000 | [
"Mathematics"
] |
Performance analysis of a directly modulated semiconductor optical amplifiers using non ‐ return ‐ to ‐ zero, duobinary and quaternary pulse amplitude modulation signalling
Numerical investigation was done for the response of two semiconductor optical amplifiers (SOA) to direct modulation using three of the most commonly employed intensity modulation formats: non ‐ return ‐ to ‐ zero (NRZ), duobinary (DB) and quaternary pulse amplitude modulation (PAM ‐ 4). It was shown that an optimized SOA not only delivers an average optical power of 18 dBm, but can also be modulated at 25.4, 28.0 and 29.3 Gb/s with the aforementioned formats, respectively. No optical or electronic assistance is considered. The use of spectral ‐ efficient PAM ‐ 4 thus leads to an improvement of almost 4 Gb/s with respect to NRZ. Slightly faster modulation is reached by operating the SOA deeper into saturation. These figures fall to 12.8, 15.0 and 16.3 Gb/s after 20 km conventional single ‐ mode fibre propagation in C ‐ band. Calculation of 10 Gb/s back ‐ to ‐ back sensitivities at the low ‐ density parity ‐ check forward error correction bit ‐ error ratio (BER) threshold of 1 � 10 (cid:0) 2 resulted in (cid:0) 24.5, (cid:0) 20.5 and (cid:0) 20.0 dBm for NRZ, DB and PAM ‐ 4 modulations, with a 50 km transmission penalty lower than 3 dB for PAM ‐ 4. This enables the use of directly modulated SOAs as transmitter alternative in high ‐ loss access networks, such as super ‐ passive optical networks, provided that further technical improvements can be performed to meet its challenging loss
| INTRODUCTION
The design and eventual implementation of an opto-electronic transmitter exhibiting relatively broad bandwidth (BW) and high output power, packaged in a small integrated photonic circuit, is always welcome as a key element of an intensitymodulated with direct-detection (IM-DD) unamplified optical fibre system. These elements are useful not only because they help to fulfil the power budget requirements of the system, but because their employment normally reduces the overall power expenditure of the network. One relevant example of the need for these elements is found in the realm of short-reach systems. In particular, in time-division multiplexed passive optical networks (TDM-PONs), where the introduction of this kind of transmitters may help to increase the power budget margins.
Indeed, due to the point to multi-point nature of these networks and despite that they should only reach 20 km of conventional single-mode fibre (CSMF), these architectures rely on meeting a loss budget of at least 29 dB (PR30 in EPON, N1 class in ITU-T-PON) [1]. This tight budget requirement comes from their inherent 1:32 power splitter, necessary to build their tree topology. Even more challenging is the implementation of a Super-PON, which is currently under development by the IEEE P802.3cs Task Force [2] and the ITU through recommendation G.9807.3 [3]. This multi-wavelength PON architecture is expected to support a bit rate of 10 Gb/s following a passive point-to-multipoint topology (relying on a passive wavelength router) where a transmission reach of at least 50 km has been set as objective [4]. With its increased reach and an aggregation of up to 1024 customers, Super-PON is especially attractive as a solution to provide a competitive bandwidth to more sparsely populated areas. Among several design challenges, a loss budget of 41 dB (without considering fibre impairments) has to be surmounted using multi-wavelength amplification and optical receivers with sensitivities lower than À 30 dBm (non-return-to-zero [NRZ] format) [5].
As an alternative to Er-doped fibre amplifiers (EDFAs), currently being considered [4], the use of 10 Gb/s powerful transmitters might be attractive in terms of cost and power consumption savings. Current state-of-the-art 10 Gb/s transmitters relying on semiconductor optical amplifier (SOA) boosters deliver an output power of about 9 dBm [6]. Higher transmission power, nonetheless, can be produced by directly modulating an SOA that uses a low-power continuous wave (CW) laser as optical input. In this scheme, the SOA's pumping current is modulated by a radio-frequency data signal that in turn modifies the gain (and refractive index) of the amplifier. Correspondingly, the originally CW signal becomes simultaneously amplified and modulated, resulting, in the ideal situation, in an optical replica of the digital information to be transmitted. Nevertheless, this approach suffers from a very low opto-electronic BW [7], mainly determined by the relatively long differential carrier lifetime that is characteristic of the SOA [8]. An opto-electronic BW of a few GHz leads to data-pattern degradation [9] in 10þ Gb/s systems. Although customization of the SOA structure and proper adjustment of the operation point improves the SOA modulation BW [10], more practical solutions to tackle this limitation are based on serially connecting an offset optical filter into the SOA output to tailor the chirp dynamics of the outgoing optical waveform, thus reducing the undesired distortions [11]. Some already explored filtering configurations are summarized in Table 1. Unfortunately, this all-optical approach integrates an extra element (the filter) into the transmitter. This increases complexity and unwelcome insertion losses, which sometimes even overcome the gain produced by the SOA [9]. An alternative approach to prevent this, but yet augment the transmission bit rate, is to use advanced modulation formats, characterized by exhibiting a high spectral efficiency (instead of using plain NRZ format). Duobinary (DB) modulation, produced by filtering an XOR-precoded NRZ sequence with the aid of a fourth order Bessel electrical filter whose BW matched 0.25 � B, has been tested at a bit rate B ¼ 10 Gb/s, producing encouraging results. In the experiment, the corresponding electrical signal was employed to directly modulate a reflective SOA (RSOA) exhibiting an opto-electronic BW of 1.5 GHz. Thanks to its narrow BW and the fibre chromatic dispersion tolerance inherent to DB modulation, 10 km transmission was effectively demonstrated in C-band [12].
Due to its relative compact spectrum and its ease of implementation (e.g. as compared to coherent modulation) pulse-amplitude modulation of 4 levels (PAM-4) has attracted considerable attention in recent years [18]. It has, for example, substituted NRZ as de facto modulation format in the Ethernet standard, as it moves its data rate from 100 Gb/s (4 � 25 Gb/s) to 400 Gb/s (8 � 50 Gb/s) [19]. Despite its benefits, however, PAM-4 has not been sufficiently investigated as an alternative to directly modulate an SOA. In [20], Cho et al. analysed the transmission performance of a PAM-4 encoded signal when an RSOA, exhibiting an opto-electronic BW of 2.2 GHz, was employed as optical modulator. The authors achieved 20 km reach at a bit rate of 11 Gb/s in C-band. Aided by electronic equalization (7-tap FFE and 5-tap DFE) and proper adjustment of the four amplitude levels, the authors measured a sensitivity of about À 13 dBm at a bit-error ratio (BER) of 1�10 À 2 . Following this promising outcome, it results natural to ask whether PAM-4 can outperform DB modulation when utilized as coding technique to drive an SOA-based modulator. The question becomes particularly relevant when noting that the spectral BW of a PAM-4 signal is narrower than the corresponding one of a DB signal operating at the same bit rate. Indeed, Figure 1 shows the power spectral density of three electrical signals running at 10 Gb/s that are encoded using different modulation formats: NRZ, DB and PAM-4. The corresponding 3 dB BWs are, respectively, 4.0, 2.4 and 2.0 GHz. Clearly, the modulation with the broadest BW is NRZ, while that with the narrowest BW is PAM-4 and hence it should present the best performance when used to directly modulate an SOA, at least in back-to-back (BtB) configuration.
To test our hypothesis, in this contribution we present a system performance comparison as a function of bit rate of the three aforementioned modulation formats when they are employed to drive an SOA-based modulator. By means of simulations, carried out under the same system conditions, BtB and 20 km reach configurations are numerically analysed for two SOAs, each exhibiting different opto-electronic BW. It is shown that PAM-4 modulation indeed represents the best choice to extend the operation speed of directly modulated SOAs, especially when transmission along an optical fibre is taken into account. In contrast, NRZ performs rather poorly. Bit rates as high as 29.3 (BtB) and 16.3 (20 km propagation) using PAM-4 can be achieved. These results are complemented with simulations using both SOAs to determine the system sensitivity for all three formats at 10 Gb/s. BtB, 20 and 50 km configurations are investigated and the corresponding power budgets calculated. The feasibility of implementation of 10G PONs, 25G PONs, and Super-PONs using directly modulated SOA transmitters is briefly discussed. This article is divided into four main sections. In Section 2, we explain how the simulations were carried out, including some SOA characterization curves derived from the numerical model (Section 2.2). Next in Section 3, we present and discuss the chief results of our analysis. Transmission speed (Section 3.1) and system sensitivity at 10 Gb/s (Section 3.2) are investigated. We conclude in Section 4.
| SYSTEM SETUP AND SIMULATION DETAILS
The system to be simulated, implemented on a VPI Design Suite™V10.0-Matlab®R2019a co-simulation platform, is presented in Figure 2. It consists of a travelling-wave SOA whose optical input is derived from a CW laser emitting at λ ¼ 1550 nm with 10 MHz linewidth. The optical signal-to-noise ratio (OSNR) of the CW signal, prior to entering into the SOA, was set to 40 dB. The directly modulated SOA is driven using an electrical transmitter whose implementation details depend on the analysed modulation format, but includes a pseudorandom bit sequence (PRBS) generator, an encoder (with precoding in the DB case), an upsampling module that acts as digital-to-analogue converter and a driver that sets bias and amplification of the driving (pumping) signal. In all transmission cases, the same PRBS, 2 16 bits long, was encoded using NRZ, DB or PAM-4 formats. The sequence was then upsampled 64 times to simulate an electrical signal varying between 200 and 600 mA, irrespective of modulation format. In this way, we maintained the same (outer) extinction ratio in all cases. The characteristics of the SOA are discussed below. Depending on the state of a simple switch, the modulated optical signal is launched onto 0 (BtB case), 20 km or 50 km of (CSMF), which is modelled following a uni-directional timedomain formalism. The fibre model considers chromatic dispersion and Kerr non-linearities. For λ ¼ 1550 nm, the fibre parameters were chosen as: attenuation of 0.25 dB/km, dispersion of 17 ps/nm⋅km, slope of 0.08 ps/nm 2 km, nonlinear index of 2.6�10 À 11 μm 2 /mW and a core effective area of 80 μm 2 . After fibre transmission, a variable optical attenuator (VOA) is introduced to control the power impinging into the optical front end (OFE). The OFE consists of a PIN photodiode and a trans-impedance amplifier (TIA). The photodiode model, having a responsivity of 0.9 A/W, takes into account shot noise and thermal noise with a current noise density of 14 pA/Hz 0.5 and a dark current of 5 nA. It has an optoelectronic 3-dB BW of 0.75 � B Hz with Bessel characteristics, where B stands for the system bit rate. The TIA has a conversion gain of 4000 Ω and a noise current of 1.1 μA that captures all noise sources of the TIA. After clock-recovery, optimization of the decision threshold in both the horizontal (time) and vertical (voltage) directions is carried out, followed by decoding of the corresponding modulation format. The BER is finally calculated by direct bit counting. According to this conventional procedure to calculate the BER, 1.81�10 À 4 becomes the minimum BER that we can report with a confidence level of 95% [21]. This estimation can be determined from the safety margin of maximum allowed mistakes incurred while counting the bits, that we have set to six; and the number of transmitted bits (2 16 ) employed to carry out the error counting calculations, which in turn is limited by computational time and memory constraints.
| SOA modelling
Modelling of the bulk SOA was carried out with the most sophisticated SOA module provided by VPI. It is based on a well-tested, multi-section transmission line model [22] that takes into account the longitudinal distribution of the carrier density and the propagation of the optical waveform (fundamental mode) along the device. The calculation of the former is based on conventional rate equations that include ultra-fast non-linear effects. The latter is simulated via scattering matrices acting upon a forward and backward propagated (complex) optical field that travels along the transmission lines that interconnect the sections in which the SOA is divided. We have assumed a current injection efficiency of 100% that is homogeneously distributed along the SOA, and we have disregarded some electro-optical parameters in the SOA model such as capacitances, inductances, and resistances inherent to the SOA assembly [23]. These assumptions might lead to small inaccuracies that are inconsequential for the results reported in this work. Modelling of the carrier density-dependent amplified spontaneous emission (ASE) is included in the formalism. It uses Langevin noise sources scaled by means of a population inversion parameter. The refractive index dynamical behaviour is captured through the use of the well-known linewidth enhancement factor [24]. Since only one wavelength is considered in the analysis, we selected the flat gain dispersion model. The SOA photonic module accepts three ports: optical input, optical output, and electrical input. The modulated electrical signal is injected into the latter, which in turn modifies the carrier injection density (pumping), being responsible for generation of electron-hole pairs inside the active region. The carrier injection density represents a fundamental (for our analysis) term in the carrier density rate equation, which is also mediated by the recombination rate and stimulated emission rate. When the recombination rate is associated to a carrier lifetime [8], it determines the response time, and hence, the opto-electronic bandwidth of the active device. If the period of the transitions with which the carriers are injected becomes much lower than the response time of the SOA, the originally modulating signal becomes severely low-pass filtered (LPF) and distorted when transformed to a variation of the carrier density, or SOA gain. This in turn generates a distorted optical waveform with respect to the injected modulating signal. Further details of the modelling approach can be found elsewhere [25]. Table 2 lists the parameter values used with the SOA model in our simulations. Two sets of parameters are considered. The set corresponding to SOA1 refers to a standard bulk SOA, whereas the set of parameter values corresponding to SOA2 has been fine-tuned to match an amplifier that exhibits a faster response while maintaining similar gain characteristics, as demonstrated in the next subsection.
| Numerical characterization of the SOA
Before carrying out the main analysis of our contribution, it is always convenient to characterize some aspects of the amplifiers. This procedure is useful to set the most adequate SOA operation region. The derived curves are also helpful as a reference point for the interpretation of the results presented in Section 3. This analysis also provides confidence in the modelling approach and the actual parameter selection (see Table 2). Figure 3 displays the on-chip SOA gain as a function of input (red) and output (blue) power for a constant injection current value of 300 mA. Results for SOA1 (solid) and SOA2 (dashed) are presented. The curves follow the expected saturation behaviour [26]. Small-signal gains of 34.7 and 35.5 dBm are measured from the graphs for SOA1 and SOA2, respectively. Of particular interest is the input saturation power of SOA1 that corresponds to P in sat ¼ À 22 dBm, whereas P out sat ¼ 9.5 dBm.
Similar values can be measured for SOA2. Figure 4 presents the SOA output power (P out ) as a function of constant injection current for different values of input power (P in ) calculated using SOA1. As expected, once we reach the current required to produce sufficient gain to overcome the device losses, the optical output power (P out ) starts growing in a practically linear fashion. For the same current level, higher P out is obtained for higher P in , although gain saturation is effectively observed as P in becomes more intense. Very similar curves (not shown) are obtained for SOA2. Output powers as high as 80 mW are calculated for 400 mA at P in ¼ 10 dBm, corresponding to a gain of 9 dB. The gain becomes higher (about 18.5 dB) for a more reasonable P in ¼ 0 dBm that produces a P out ¼ 70 mW. This demonstrates the advantage in terms of output power that the use of an SOA as optical modulator offers. When SOA2 is employed with P in ¼ 0 dBm, the output power at 400 mA decreases to 63 mW, corresponding to an amplifier gain of 18 dB. As Figure 3 confirms, SOA2 exhibits a sightly lower gain than SOA1 at P in ¼ 0 dBm because of its marginally lower saturation power.
Particularly relevant for this work is the modulation BW analysis of the amplifiers. This is achieved by injecting a sinusoidal electrical signal into the SOA that varies from 300 to 400 mA (here the P out v.s. injection current curve behaves practically linear) and then measure the peak-to-peak power of the optical signal obtained at the SOA output while the frequency of the input periodic signal increases. The corresponding normalized curves for different values of P in are F I G U R E 2 Setup of the system to be simulated GUTIÉRREZ-CASTREJÓN ET AL.
shown in Figure 5 for SOA1 and in Figure 6 for SOA2. For low frequencies, an effective mapping is carried out by the transducer. Similar modulation response is obtained irrespective of the CW input power. However, as the frequency of the driving signal increases, a reduction of the modulation amplitude is observed, as also noted in the literature [7,10]. For sufficiently large frequencies, a higher optical input power leads to better response. For instance, while for P in ¼ À 20 dBm, the 3-dB optoelectronic BW becomes shorter than 2 GHz in SOA1, for P in ¼ 10 dBm, the same performance parameter becomes approximately 4.3 GHz. This behaviour can be ascribed to the higher saturation level presented by the SOA when a high input optical power is introduced. Indeed, when the SOA becomes saturated, its effective carrier lifetime decreases, leading to a faster response and broader BW of the device (see, e.g. [26], p. 99). The practical consequence of this observation is that better performance of the directly modulated SOA is obtained when a strong CW beam is employed. Unfortunately, it is also at this operation point that the amplifier delivers a compressed gain, thus downgrading the main benefit of using an SOA as modulator. A compromise between high gain and broad modulation BW has to be set. For the simulations presented in Section 3, two values of P in were considered: 0 and 10 dBm since, according to Figures 5 and 6, they lead to a similarly fast modulation response. Clearly, in both cases the amplifier operates well in its saturation regime (see Figure 3). Figure 6 is also useful to point out the broader opto-electronic BW exhibited by SOA2 as compared to SOA1. For instance, for P in ¼ 10 dBm, this relevant performance parameter amounts to 9.0 GHz; that is more than two times higher than the one measured for its non-tuned counterpart. This BW increase enables a faster SOA2-based transmitter, able to reach higher
| Transmission speed analysis
We carried out transmission simulations following the scheme presented in Figure 2. NRZ, DB and PAM-4 signalling were analysed. In order to guarantee a fair comparison among all formats and system configurations, and to avoid the overload of the photodiode (PD) at the receiver end, in all the situations analysed in this section we have set the received optical power (ROP) at the PD input to À 5 dBm. The VOA was then set accordingly in each case. The electrical spectra of the three modulation formats with all signals running at 10 Gb/s and captured prior to entering into the SOA, are displayed in Figure 1. As discussed in the introduction, the narrowest spectrum corresponds to PAM-4. Due to its inherent 2 bits-per-symbol coding scheme, a sharp decrease on its power spectrum becomes evident, showing a local minimum at 5 GHz, which corresponds to the symbol rate (5 GBd). NRZ has the broadest spectrum, with a 3-dB BW two times wider than PAM-4. Being a spectrally compressed version of NRZ, DB modulation shows a spectrum that decreases faster than NRZ, but still it is slightly broader than the spectrum of PAM-4. In this respect, it is worth mentioning that the DB signal was generated using a fifth-order Bessel electrical LPF showing a 3-dB cut-off frequency of 0.33� B. We noticed that this choice of BW offered the best results. Figure 7 shows the BER versus B curves resulting from simulations in BtB configuration when SOA1 is employed. First, a CW beam having an input power of 0 dBm (solid lines) was injected into the SOA, leading to an optically modulated output signal exhibiting an average power of 18.6 dBm (about 72.4 mW), irrespective of modulation format. This corresponds to an SOA gain of 18.6 dB. Our calculations hence demonstrate the benefit in terms of output power that using the SOA as modulator provides, showing its superior performance over other solutions (e.g. the AXEL [6]). The solid curves in Figure 7 show a pronounced increase of BER as a function of bit rate. All formats exhibit similar slopes. According to the figure, the best performance for a BER of 1�10 À 2 (see explanation below) is presented by PAM-4 (yellow curve) since the use of this format leads to the highest modulation speed. It is closely followed by DB modulation (blue curve), which even surpasses the performance of PAM-4 at low BER values. NRZ (red curve) shows the worst performance from the three analysed signalling schemes. Our numerical results then confirm our hypothesis: PAM-4, the modulation format with the narrowest spectrum, reaches the highest modulation speed, whereas NRZ, the modulation format with the broadest spectrum, achieves a rather modest bit rate. This observation can be explained as follows. Since, according to Figure 5, and due to its inherent carrier density dynamics, the SOA acts as a transducer with LPF characteristics, it results natural to expect higher transmission speeds when a format with a narrower spectral shape is employed. In other words, PAM-4 results less distorted by the BW-limiting characteristics of the SOA with respect to NRZ; consequently, lower BER values are achieved for a given bit rate. To quantitatively determine the performance difference among the analysed formats, we have set 1�10 À 2 as our reference BER. This value corresponds to the low-density parity-check forward error correction (LDPC-FEC) threshold [27]. For this BER value, the maximum bit rates that can be achieved by each format are presented in Table 3 (first row): 12.8 Gb/s for NRZ, 14.0 Gb/s for DB and 14.5 Gb/s for PAM-4. From these numbers it is evident that the use of PAM-4 signalling provides a bit rate extension of 0.5 Gb/s with respect to DB and even more, 1.7 Gb/s, with respect to NRZ modulation, thus demonstrating the advantage of using PAM-4 to increase the operational speed of a directly modulated SOA transmitter. This increase in transmission speed is simply achieved by switching to a modulation format having a higher spectral efficiency. No further optical or electronic assistance is employed. As already predicted with the aid of Figure 5, higher bit rates are expected when increasing the CW power injected into the SOA. Under these operation conditions, the amplifier is more deeply driven into saturation, shortening its effective carrier lifetime [8]. This can be confirmed using our simulation platform by setting P in ¼ 10 dBm. As the dot-dashed lines in Figure 7 show, the corresponding values of B at BER ¼ 1�10 À 2 are now 16.0 Gb/s for NRZ, 18.1 Gb/s for DB and 18.4 Gb/s for PAM-4. See also the second row of Table 3. This represents an increase as compared to the P in ¼ 0 dBm case, of 3.2, 4.1, and 3.9 Gb/s for NRZ, DB and PAM-4 modulations, respectively. This approximately uniform increase in bit rate leads to an effective shift of the three BER versus B curves along the B axis. It does not markedly affect their shapes. What it is more relevant to our analysis, however, is the fact that in spite of the increase of P in , PAM-4 modulation preserves the best performance, while NRZ remains the less favoured among the analysed formats. The increase in operational bit rate observed in all formats, nonetheless, comes with a penalty in amplifier gain. Indeed, according to Table 4, P out now amounts to 19.2 dBm, which corresponds to a gain of only 9.2 dB, instead of 18.6 dB measured for the P in ¼ 0 dBm case. Although P out ¼ 19.2 dBm can be considered a relatively high output power, an input power of 10 dBm is still difficult to achieve with standard laser diodes. P in ¼ 0 dBm is hence a more sensible choice, even though the consequent reduction in bit rate and the minor decrease in output power, of only 0.6 dB.
In the light of the aforementioned results, it is worth investigating the performance of each signal when propagated along an optical fibre, especially because DB and PAM-4 modulations are known to be chromatic dispersion tolerant [28,29]. Figure 7 shows, in dashed lines, curves of BER versus B for the three analysed modulation formats. They were produced via simulations where P in ¼ 0 dBm (as the solid curves), but following the 20 km optical fibre path shown in Figure 2. We chose a fibre length of 20 km since it is the target reach of current PONs [1]. Similarly to previous analyses, the VOA is set so the ROP amounts to À 5 dBm. The fibre model accounts for fibre dispersion and non-linear effects (see Section 2). The average input power into the fibre is 18.6 dBm, as indicated in the third row of Table 4. According to Figure 7, the effect of fibre propagation in all signals is to increase distortions and hence augment the BER for a given bit rate value. Again, all curves approximately maintain their shape but they appear shifted towards lower bit rates. Taking BER ¼ 1�10 À 2 as reference performance level, the bit rates after 20 km propagation are the following: 9.8 Gb/s for NRZ, 11.0 Gb/s for DB and 11.3 Gb/s for PAM-4. They are also presented in the third row of Table 3. Our simulation results demonstrate that, although a directly modulated SOA-based transmitter can effectively by employed in 10 Gb/s systems with maximum reach of 20 km, care has to be taken in choosing the most adequate operating conditions and modulation format. For
-
instance, whereas in our simulations PAM-4 is capable of reaching bit rates well above 10 Gb/s, NRZ falls short in this respect, favouring the choice of the former signalling scheme. After fibre propagation, Figure 7 shows that PAM-4 modulation barely keeps its prominence, whereas NRZ again exhibits the worst performance. When the obtained bit rates are compared to the BtB ones (first row in Table 3), the following differences are observed: 3 Gb/s for NRZ and DB modulations and 3.2 Gb/s for PAM-4. That means that for 340 ps/nm of accumulated dispersion, corresponding to 20 km of CSMF in C band, the maximum bit rate achievable by all analysed formats becomes affected by chromatic dispersion in practically the same manner. Note, however, that favourable noise conditions (high SNR at the receiver), resulting from a high value of ROP ¼ À 5 dBm, prevail. Further reductions in B can be anticipated as the fibre length increases, thus effectively limiting the system reach. In general, the degradation observed in the optical signal due to chromatic dispersion is expected to be higher as compared to the externally modulated situation because of the presence of chirp and distortions imprinted in the optical signal by the directly modulated SOA. A comparison analysis following these lines and considering varying fibre lengths, is still necessary to be done. This topic is, nevertheless, out of the scope of this report. Let us just mention that the use of a chirp management element, for instance, an optical filter (see Table 1), will most probably be helpful to extend the reach of a directly modulated-based transmission system operating at a given bit rate. Equivalently, lower penalties in terms of bit rate are expected in this kind of chirped-managed transmission systems at a given fibre length.
The overall performance of the 20 km long fibre system can be improved by running simulations with an input power into the SOA of 10 dBm (instead of 0 dBm). For the sake of brevity, these results have been omitted, but they can be qualitatively inferred based on our previous numerical analyses. Indeed, the expected outcome is a uniform shift of the dashed curves shown in Figure 7 to higher B values, where PAM-4 modulation will maintain the highest bit rate at the LDPC-FEC BER threshold, while NRZ will keep the lowest bit rate. Furthermore, it is not difficult to foreseen that NRZ will now be able to operate at 10 Gb/s since an increase of only 0.2 Gb/ s suffices to reach this relevant transmission speed. The 20 km system would hence become benefited from the increase on input power. Similarly, the SOA output power under these circumstances of input power can be predicted to be 19.2. dBm, irrespective of modulation format (see Table 4). This value is slightly higher than the one obtained using P in ¼ 0 dBm (i.e. P out ¼ 18.6 dBm).
Our transmission speed analysis can be extended by considering simulations employing SOA2. According to Section 2.2, this SOA exhibits similar gain levels to those presented by SOA1, while displaying a faster response time. A 3-dB BW more than two times higher than that determined for SOA1 was measured from Figure 6. Consequently, higher transmission speeds are expected when running simulations similar to those described above. The corresponding results are graphically presented in Figure 8 and summarized in the rightmost columns of Tables 3 and 4. According to the latter, the calculated power at the SOA output is indeed very similar to the one determined for SOA1, only approximately 0.5 dB lower. More relevant results can be read from Figure 8. First, we can observe that when measuring the bit rate at the LDPC-FEC threshold and, in agreement with our results for SOA1, it is PAM-4 (yellow curves) the modulation format that exhibits the best performance in all three analysed situations: BtB with P in ¼ 0 dBm, BtB with P in ¼ 10 dBm, and 20 km CSMF propagation with P in ¼ 0 dBm; while NRZ is still the less favoured one. Bit rate differences between PAM-4 and NRZ modulation formats amount to 3.9, 5.7, and 3.5 Gb/s for the three analysed cases, respectively (see Table 3). They represent the transmission speed gained when switching from NRZ to PAM-4. These bit rate extensions are higher than those calculated using SOA1 (1.7, 2.4, and 1.5 Gb/s, respectively). Second, we can observe that, although shifted towards higher B values, the shapes of the BER versus B curves are, in general, preserved. Third, irrespective of modulation format, the highest transmission speeds are obtained for the most powerful input beam (dot-dashed lines), followed by the P in ¼ 0 dBm case (solid lines), while the lowest modulation speeds correspond to the fibre transmission case (dashed lines). This behaviour is in line to what we observed when using SOA1. And fourth, faster bit rates are indeed found for all the analysed situations and modulation formats as compared to those calculated using SOA1. In particular, for both BtB cases, B is always greater than 25 Gb/s, even when using NRZ format with P in ¼ 0 dBm (see upper rows of Table 3). This means that properly optimized directly modulated SOA transmitters can, in principle, be employed in 25G fibre links. Unfortunately, optical signals modulated with higher B are also more severely affected by chromatic dispersion and other deleterious fibre effects. Therefore, after 20 km fibre transmission, the maximum achievable B becomes reduced to levels varying from 12.8 Gb/s for NRZ to 15.0 Gb/s for DB and 16.3 Gb/s for PAM-4. Although they are still higher than those obtained with SOA1, they are only fast enough to be used in 10G systems. The situation might be different in dispersion-managed photonic links, or those with channel plans laying in O-band, which are characterized by low chromatic dispersion and high fibre loss. There, high transmission speeds can be preserved, while the corresponding increase in loss budget can be compensated with the high output power delivered by the SOAbased transmitter.
| Sensitivity analysis
From the application standpoint, it is always welcome the calculation of the system sensitivity under particular conditions of bit rate and transmission distance. This allows the determination of power penalties and, ultimately, of the system power budget, which is an essential metric to decide on the technical feasibility of an optical link. Since the envisaged applications in this work are PONs and, in particular, Super-PONs, we have carried out a sensitivity analysis of the directly modulated SOA system depicted in Figure 2 for three different fibre lengths: 0, 20 and 50 km. We have opted for a CW input power of 0 dBm, which seems to be more akin to commercial applications. For the same reason we have chosen a bit rate of 10 Gb/s. In this way, our results might eventually be applicable to the design of a hypothetical next-generation Super-PON, which operates at B ¼ 10 Gb/s, with a maximum fibre length of 50 km. The analysis has been conducted for NRZ, DB and PAM-4 formats and we have included both investigated SOAs in our calculations. Figure 9 displays the BER versus ROP curves obtained from our simulations when employing SOA1. The ROP is varied by accordingly setting the losses of the VOA placed before the PIN photodiode. Curves for the BtB (solid), 20 km (dashed) and 50 km (dot-dashed) configurations are presented. For the bit rate of choice, and in agreement with Figure 7, when a signal with NRZ format (red curves) is transmitted along 20 and 50 km long fibres, it becomes severely distorted such that the corresponding BER values cannot be accurately calculated (hence, the values are not displayed in the figure). In contrast, when operated in BtB configuration, NRZ presents the lower sensitivity value of all formats. The situation is different with DB and PAM-4 formats, which, although exhibiting a higher distortion level than NRZ (and thus higher BER values) when coming out from the SOA (or BtB case), they become less affected by fibre propagation effects. This is particularly evident in PAM-4. Table 5 summarizes, for all the analysed formats, the sensitivities measured at the LDPC-FEC BER threshold. It quantitatively confirms our findings. Whereas NRZ presents a BtB sensitivity of À 20 dBm, the calculated sensitivities for DB and PAM-4 modulation amount to À 17.9 and À 18.5 dBm, respectively. However, the power penalties with respect to BtB of DB and PAM-4 formats are 1.0 and 1.6 dB, respectively, for 20 km propagation and a very large value (floor observed) and 6.5 dB for 50 km propagation. This indicates that, when SOA1 is employed for transmitting at 10 Gb/s, NRZ should be the format of choice only when systems having a very short reach (a few kilometres) are considered, whereas PAM-4 should be used in systems with fibres no longer than about 50 km, accepting the corresponding power penalty. Based on the calculated sensitivities and the high output power delivered by the directly modulated SOA (also shown in Table 5), the available power budget can be calculated for each modulation format. It is the difference (in dB) between the measured sensitivity and the SOA output power and is also displayed in Table 5. For the BtB configuration, the available power budgets are 38.6 dB (NRZ), 36.5 (DB) and 37.0 dB (PAM-4). Clearly, none of them is sufficient to meet the loss budget of 41 dB associated to Super-PON, especially after having considered the corresponding 50 km transmission power penalty. This is not the case, however, when considering 10 Gb/s PONs, where a loss budget of 29 dB (PR30 in EPON and N1 class in ITU-T-PON) and a transmission distance of 20 km can be readily bridged by DB and PAM-4 formats. Indeed, the available power budget in this case (20 km) is slightly greater than 35 dB for both formats. It is, therefore, 6 dB higher than strictly necessary by N1 class PONs, thus enabling other PON classes with higher required power budget. Curiously, due to limitations inherent to the SOAbased modulation approach, NRZ cannot be employed for the implementation of this kind of networks. This fact, together with the simplicity of directly modulated lasers [30], turn the directly modulated SOA approach into an impractical solution for 10G PONs.
The sensitivities presented in Table 5 for both, BtB and fibre propagation, are very dependent on the particular SOA characteristics. Among them, we can mention bandwidth and saturation power. Therefore, better overall system performance can be expected when using SOA2. To demonstrate this projection, we have carried out a similar 10 Gb/s sensitivity analysis, but this time using SOA2. The results are presented in Figure 10, whereas the corresponding power calculations and sensitivities measured at the LDPC-FEC BER threshold are shown in Table 6. Thanks to the broader BW exhibited by SOA2, a less distorted optical signal emerges from the amplifier output facet and hence, the measured sensitivity values are, in general, lower. Such is the case of NRZ modulation, which still presents the lowest sensitivity from all analysed formats in BtB configuration. It is now À 24.5 dBm. Moreover, for the same reason, the 20 km propagation case now presents a finite sensitivity of À 22 dBm, which is found to be below the sensitivities measured for DB and PAM-4 formats for the same fibre length. The sensitivities of the latter modulation formats in BtB configuration are around À 20 dBm, thus presenting an improvement with respect to the case where SOA1 is employed of 2.6 dB for DB and 1.5 dB for PAM-4. A negative power penalty of about 3 dB is also observed for these two formats in the 20 km propagation case. Furthermore, DB modulation now exhibits a finite sensitivity for the 50 km propagation case of À 15.0 dBm, whereas PAM-4 presents a relevant improvement of more than 5 dB with respect to the equivalent simulations performed with SOA1.
The improvement gained by switching to the optimized SOA (instead of using SOA1) is more striking when calculating the available power budget (see Table 6). In spite of the tiny reduction in SOA output power experienced by using SOA2, now NRZ can indeed be used to implement a 10G PON since the available power budget after 20 km propagation amounts to about 40 dB. However, the more interesting improvement comes from PAM-4 modulation, where the 50 km propagation case reaches a power budget of 35.3 dB. This figure is only 41.0-35.3 ¼ 5.7 dB shorter than the power budget required to use the discussed transmitter technology in Super-PONs. We think that this extra ∼6 dB can be gained by implementing a combination of factors: using an optimized photodetector (a sensitivity below À 30 dBm is reported in [4] for 10 Gb/s NRZ transmission); increasing the SOA gain; maximizing the PAM-4 outer extinction ratio and eye opening (especially of the lower eye) by optimizing the driving electrical signal; tailoring the chirp exhibited by the waveform coming out from the SOA; and using electronic digital signal processing to compensate for fibre dispersion and other system impairments. The envisaged Super-PON transmitters would, in principle, avoid the use of EDFAs and hence represent, we believe, an alternative worth investigating.
| CONCLUSION
We have presented a numerical analysis to compare, under very similar conditions, three of the most common IM/DD modulation formats when used to directly modulate a semiconductor optical amplifier. Both, BtB and fibre transmission configurations were considered. We found that, in agreement with a preliminary bandwidth analysis, PAM-4 outperforms DB and NRZ modulation formats in terms of achievable modulation speed when measured at the LDPC-FEC BER threshold of 1 �10 À 2 . The advantage is preserved even after 20 km transmission in C-band. Our analysis also demonstrates that for an optimized SOA and under favourable operation conditions, the amplifier can be modulated up to 29 Gb/s with PAM-4 signalling in BtB configuration, thus representing an almost 4 Gb/s extension with respect to the case where NRZ is employed. Higher modulation speeds can be achieved by driving the SOA deeper into saturation at the expense of amplifier gain. Unfortunately, the achievable operational bit rate becomes severely degraded due to fibre chromatic dispersion, thus preventing the use of the analysed SOA-based transmitters in short-reach 25G systems operating in C-band. They could be employed, nonetheless, as 10G PON transmitters since an output power as high as 18 dBm was numerically demonstrated for the analysed device. A more appealing application is Super-PONs because of its recent introduction and chance for improvement. According to our analysis, a 10 Gb/s PAM-4 sensitivity at BtB of À 20 dBm plus a 50 km transmission power penalty of less than 3 dB can be achieved. The available corresponding power budget for the 50 km case then becomes 35 dB, which is only 6 dB shorter than the one currently stated by the Task Force working on the Super-PON design (i.e. 41 dB). We are confident that this ∼6 dB could be bridged through a combination of novel techniques such as driving waveform optimization via digital signal processing, thus motivating further research in this direction [31]. | 9,844.8 | 2020-12-08T00:00:00.000 | [
"Physics"
] |
Adsorption and diffusion characteristics of lithium on hydrogenated α- and β-silicene
Using first-principles density functional theory calculations, we investigate adsorption properties and the diffusion mechanism of a Li atom on hydrogenated single-layer α- and β-silicene on a Ag(111) surface. It is found that a Li atom binds strongly on the surfaces of both α- and β-silicene, and it forms an ionic bond through the transfer of charge from the adsorbed atom to the surface. The binding energies of a Li atom on these surfaces are very similar. However, the diffusion barrier of a Li atom on H-α-Si is much higher than that on H-β-Si. The energy surface calculations show that a Li atom does not prefer to bind in the vicinity of the hydrogenated upper-Si atoms. Strong interaction between Li atoms and hydrogenated silicene phases and low diffusion barriers show that α- and β-silicene are promising platforms for Li-storage applications.
In the large family of 2D materials, silicene deserves a special consideration due to its compatibility and expected integration with current nanotechnology. Silicene consists of a single layer of Si atoms arranged in a hexagonal lattice. Unlike the gapless semimetal graphene, silicene has a tiny energy gap that stems from the intrinsic spin-orbit interaction [19]. Instead of the planar structure of graphene, silicene exhibits a low-buckled structure.
Although bulk silicon does not have a layered structure, syntheses of a 2D form of silicon via epitaxial growth on several metal substrates such as Ag(111) [5,20], Ir(111) [21], and ZrB 2 (0001) [22] were achieved. By performing ab initio calculations, Liu et al. predicted that the electronic properties of silicene highly depend on the substrate [23]. Johnson et al. showed that the Ag(111) surface leads to metalization of a few distinct forms of silicene [24]. Among the variety of substrates, Ag(111) surface comes to prominence for epitaxial growth of single-layer silicene. Lattice match and almost homogeneous interaction between Ag(111) and silicene support the formation of a honeycomb structure of silicene. Recently, a silicene field-effect transistor was successfully fabricated on Ag(111) with a measured room-temperature mobility of about 100 cm 2 ·V −1 ·s −1 [25]. In addition to pristine forms, hydrogenated derivatives of silicene were also studied extensively. Theoretically, it was predicted that hydrogenated silicene has two different atomic configurations (chair-like and boat-like) with energy gap values ranging between 2.9 and 4.0 eV [26]. It was found that half-hydrogenated silicene exhibits ferromagnetic semiconducting behavior with a band gap of 0.95 eV [27]. Hydrogenation leads indirect-to-direct gap transitions in bilayer silicene [28]. In the experimental study of Qiu et al., the ordered and reversible hydrogenation of silicene was performed [29]. Moreover, Medina et al. demonstrated that hydrogenation leads to a structural transition from the classical α-(3×3) phase to the β-(3×3) phase [30]. It was indicated that β-(3×3) phase could coexist with α-(3×3) phase. Despite recent experimental studies on these phases, no theoretical study has ever been reported for the hydrogenated forms of α-and β-silicene on a Ag(111) surface.
The adsorption of alkali metal atoms provides various ways to modify the structural, electronic and magnetic properties of 2D materials. It was found that adsorption of alkali atoms is a proper way to dope carbon nanotubes chemically [31,32]. It was reported that the hydrogen storage capacity and conductivity of single-walled carbon nanotubes could be enhanced by doping with Li and K [33]. The adsorption of Li atoms on the graphene surface was extensively studied [34][35][36]. It was found that the interaction of alkali metal atoms with silicene is stronger than with graphene, and the adsorption of metal atoms leads to the metalization of silicene [37]. It was calculated that the adsorption of Li atoms results in the stabilization of the unstable distorted T-phase of MoS 2 [38]. In addition, Zr-based MXenes were found to be candidates as electrode materials for Li-ion batteries [39]. For applications in Li-ion batteries, a high coverage of Li atoms on a material is required. Due to its buckled large surface area, silicene seems to be a good candidate for Li-ion battery applications. Li adsorption on pristine silicene has been extensively studied in the last several years [40][41][42][43][44][45][46]. To the best of our knowledge, the adsorption characteristics of a Li atom on hydrogenated silicene are still unknown.
In the present paper, we study the diffusion and adsorption characteristics of a Li atom on recently synthesized hydrogenated forms of α-and β-silicene phases on a Ag(111) surface using ab initio calculations within density functional theory. The paper is organized as follows: Computational methodology, hydrogenated structures of the silicene phases on Ag(111) surface, and the diffusion and adsorption characteristics of Li are presented in the section "Results and Discussion". Lastly, we conclude our results in section "Conclusion".
Computational methodology
The present calculations were performed using density functional theory (DFT) and the projector-augmented wave (PAW) method, as implemented in the "Vienna ab initio Simulation Package" (VASP) [47,48]. The exchange-correlation energy was described by the generalized gradient approximation (GGA) using the Perdew-Burke-Ernzerhof (PBE) functional [49]. A plane-wave basis set with kinetic energy cutoff of 500 eV was used for all the calculations. The van der Waals (vdW) correction to the GGA functional was included by using the DFT-D2 method of Grimme [50].
To properly simulate the structures, a 3×3-reconstructed hydrogenated silicene phase was placed on top of a 4×4 supercell of a two-layer Ag(111) surface. A 3×3×1 Γ-centered k-point mesh was used for the Brillouin zone integration. The cohesive energy per atom was formulated as (1) where E Ag , E Si and E H denote the single-atom energy of atoms Ag, Si and H, respectively. n Ag , n Si and n H are the number of Ag, Si, and H atoms contained in the unit cell, respectively. E SL+Ag(111) denotes the total energy of single-layer hydrogenated silicene and two-layer Ag(111). N is the number of total atoms contained in the unit cell.
Binding energies were calculated for the most favorable adsorption sites. Binding energies of the Li atom were calculated by using the formula (2) where E bind is the binding energy of Li atom on the hydrogenated α-or β-silicene, E SL+Ag(111) is the energy of hydrogenated α-or β-silicene on a two-layer Ag(111) surface, E Li denotes the energy of a single isolated Li atom, and E SL+Ag(111)+Li is the total energy of Li atom, single-layer hydrogenated silicene and two-layer Ag(111) surface.
Lattice constants and total energies were computed using the conjugate-gradient algorithm. The total energy difference between the sequential steps in the iterations was taken to be 10 −5 eV for the convergence criterion. The total force in the unit cell was reduced to a value of less than 10 −4 eV/Å. To hinder interactions between the adjacent cells, at least 12 Å vacuum space was used along the z-direction. All calculations were performed taking into account the spin-polarized case. Analysis of the charge transfers in the structures was determined by the Bader technique [51].
To determine how many layers of Ag (111) correctly simulate the supported α-and β-surfaces we examined the structural and electronic properties of these two phases on both two-layer and four-layer Ag(111) surfaces. As shown in Table 1, charge distribution and atomic distances are almost the same for both two layers and four layers. Therefore, it is reasonable to assume that characteristic properties of Ag(111)-supported silicene can be well simulated using two layers of Ag(111). Figure 1a and Figure 1c, respectively. To better demonstrate the structures, the lower and upper Si atoms are shown by blue and red atoms, respectively. Grey and yellow atoms denote, respectively, Ag and H. As seen in Figure 1, H-α-Si and H-β-Si do not exhibit the conventional low-buckled structure of silicene. Our total energy calculations show that the cohesive energies of both phases are almost the same which indicates that both phases can exist at the same time. This is in good agreement with previous studies reporting the coexistence of α-and β-phases. Therefore, a detailed structural analysis of these two surfaces are important to clearly understand adsorption and diffusion characteristics of an adatom on these surfaces. Similar to H-α-Si, the H-β-Si structure also has three different hexagonal units, namely β-I, β-II, and β-III, which are shown in Figure 1d. β-I has a geometric structure similar to that of α-I.
Diffusion of a Li atom on hydrogenated αand β-silicene
To understand how a Li atom adsorbs and migrates on H-α-Si and H-β-Si surfaces, total energy calculations are performed by placing a Li atom on 13 different points, which include the high-symmetry points. The distance between Li atom and surface is fully relaxed while the position of the Li atom parallel to the surface is kept fixed. During the adsorption, while Li and the nearest atoms to Li are fully relaxed, rest of atoms in the unit cell are fixed. Diffusion barriers are determined by setting the total energy of the most favorable site to zero. The most favorable binding sites are determined and their binding site, binding energy, height on the surface, the amount of charge transfer and energy barriers are given in Table 2. As shown in Figure 2a, four sites of 6Si, 2H, 2HT and 3H are considered as different binding sites for H-α-Si. Our calculations reveal that the most favorable site is 6Si, with the Si-Li bond length of 2.70 Å. In this binding site, Li atom binds with six lower Si atoms and the height of the Li atom is −1.19 Å lower than those of the H atoms. The binding energy of the Li atom on H-α-Si is 2.79 eV. Bader charge analysis shows that the Li atom donates 1e − to H-α-Si. Since the Li atom does not prefer to bind to the vicinity of H atoms, the nearest adsorption site to 6Si is 2H. It is reasonable to assume that Li atoms diffuse through these two favorable adsorption sites. The diffusion barrier of a Li atom between these two nearest binding sites is 768 meV. However, once the Li atom overcomes the energy barrier, its diffusion through the other possible sites 2H, 2HT, and 3H (having energy barriers of 100-250 meV) is more likely. We also study diffusion of a second Li atom on H-α-Si Figure 2c. The most favorable site of the second Li atom is 3H and the nearest adsorption site to 3H is 2HT. The diffusion energy barrier of the second Li atom between 3H and 2HT sites is 193 meV, which is 575 meV lower than that of the first Li atom. Hence, after the 6Si sites are occupied by the first Li atoms, the diffusion of the second Li atoms occur through the other sites relatively easily. As a result, despite such a large diffusion energy barrier between two most favorable sites, diffusion of Li atoms on H-α-Si is still possible.
Five sites, namely 3HSi, 2HT′, 2H, 3H and 3HSi′ on H-β-Si are shown in Figure 3a. The most favorable site of a Li atom on this surface is 3HSi′. The Li atom is placed in the middle of three H atoms, and it is almost in the same plane with these H atoms. The bond distances from the Li atom to the three H atoms are 1.94 Å. Li atom binds to H-β-Si with a binding energy of 2.82 eV, which is ca. 30 meV higher than that on H-α-Si. Therefore, Li atoms bind to H-β-Si slightly more easier than to H-α-Si. On H-β-Si, the Li atoms forms an ionic bond and it donates 1 e − to the surface. The nearest site to the most favorable site of 3HSi′ is 3H and this site is also energetically the second most favorable site. Thus, diffusion through these two favorable adsorption sites is most likely. The diffusion barrier of a Li atom on H-β-Si is 411 meV. Therefore, the energy barrier for the Li atom on H-β-Si is almost half of that on H-α-Si. As can be seen from Figure 3c, the 2HT′ site is the energetically most favorable site for the second Li atom on H-β-Si. The calculated diffusion energy barrier of the second Li atom between 2HT′ and 3HSi sites is 287 meV.
Contour plots of the energy barriers of a Li atom on H-α-Si and H-β-Si surfaces are shown in Figure 4a and Figure 4b, respectively. As seen from the figure, the energy differences for a Li atom on the H-β-Si surface are in a broader range than that on the H-α-Si surface. Diffusion of the Li atom around the favorable sites of H-β-Si is restricted because of high energy barriers around H atoms. In spite of the high diffusion barrier in H-α-Si, when Li atoms occupy all of the most favorable sites of 6Si, the following Li atoms on H-α-Si may diffuse more easily than on H-β-Si. The highest energy barriers seen by a Li atom are at the top of H atoms for both surfaces. These results suggest that a diffusing Li atom can follow a path of minimum energy barriers through the hydrogenated upper-Si atoms on both surfaces. In addition to the tops of the hydrogenated upper Si atoms, the tops of the lower Si atoms near to the 6Si site are also forbidden for Li atoms on H-α-Si.
Conclusion
The adsorption properties and diffusion characteristics of a Li atom on single-layer hydrogenated silicene on a Ag(111) surface were investigated. Structural properties of recently synthe-sized fully hydrogenated α-and β-silicene phases were investigated in detail. Our results showed that a single Li atom forms a strong ionic bond with H-α-Si and H-β-Si surfaces. The Li atom prefers to bind to the 3HSi′ site of H-β-Si with a binding energy of 2.82 eV. Due to the high diffusion energy barrier, a single Li atom is trapped at the 6Si site of H-α-Si, with a binding energy of 2.79 eV. However, when all the 6Si sites of H-α-Si are occupied, the diffusion barriers seen by Li atom decreases. Possible pathways of various diffusion processes of a Li atom were studied in detail. It was found that the Li atom does not prefer to bind in the vicinity of the hydrogenated upper-Si atoms on H-α-Si and H-β-Si. It is worth mentioning that H-α-Si surface is dominated by moderate energy regions, whereas the H-β-Si surface consists of partially convenient or forbidden regions for Li atom diffusion. High binding energies and relatively low diffusion barriers for a Li atom on H-α-Si and H-β-Si suggest that hydrogenated forms of α-and β-silicene are suitable materials for Li-ion batteries. | 3,378.2 | 2017-08-23T00:00:00.000 | [
"Physics",
"Chemistry"
] |
Bias-Flip Technique for Frequency Tuning of PiezoElectric Energy Harvesting Devices
Devices that harvest electrical energy from mechanical vibrations have the problem that the frequency of the source vibration is often not matched to the resonant frequency of the energy harvesting device. Manufacturing tolerances make it difficult to match the Energy Harvesting Device (EHD) resonant frequency to the source vibration frequency, and the source vibration frequency may vary with time. Previous work has recognized that it is possible to tune the resonant frequency of an EHD using a tunable, reactive impedance at the output of the device. The present paper develops the theory of electrical tuning, and proposes the Bias-Flip (BF) technique, to implement this tunable, reactive impedance.
Introduction
shows a schematic of a Piezoelectric (PZ) Energy Harvesting Device (EHD) that is the subject of this research. This structure is referred to as a cantilever structure, and is used to amplify the OPEN ACCESS amplitude of the source vibration [1]. Previous work has shown that maximum output power is achieved when the cantilever has a high Q resonance at the frequency of the source vibration. However, the frequency of the source vibration is not usually matched to the resonant frequency of the EHD. The source vibration may vary with time. This paper addresses the problem of electronically tuning the PZ EHD to achieve maximum power in situations where the source vibration is not a stable frequency matched to the mechanical resonant frequency of the EHD. In the interest of simplicity, we will analyze the structure in Figure 2. The results achieved through analysis of this structure can be generalized to the cantilever structure through the addition of geometrical constants.
Figure 2.
Schematic of the simplified EHD that is analyzed in this paper. A p is the area of the PZ capacitor, and t p is the thickness. Z is the complex amplitude of the source vibration, and X is the complex amplitude of the mechanical displacement of the mass M. This simplified model illustrates the concepts of electronic tuning that apply to the cantilever structure of Figure 1.
This paper describes three concepts for electrically tuning of PZ EHDs.
1. Use of voltage amplitude to tune the mechanical stiffness of the EHD; 2. Coupling of the mechanical resonator to an electrical RLC tank circuit; 3. Bias-Flip (BF) technique to emulate the large tunable inductor that is required for the RLC tank circuit. These three concepts were introduced in summary form in [2]. In the succeeding sections of this paper, these concepts will be presented in more detail. Section 6 shows that BF can be used to effectively optimize the power output from a PZ EHD. In this paper, we have changed some of the notation that we used in [2], in order to conform to generally accepted usage.
In this paper, we will analyze the PZ EHD. However, many of the results and conclusions are equally applicable to electromagnetic and electrostatic EHDs. Cammarano et al. [3] have described concepts very similar to #1 and #2 above in the context of electro-magnetic EHDs.
Frequency Tuning by Voltage
The material equations for PZ material can be written as follows [1].
The parameters are defined below.
Refer to the device of Figure 2. When the output is shorted, E = 0, and the mechanical stiffness is given by Young's modulus, for the case when δ = 0.
The equations for the PZ EHD shown in Figure 2 are given below These equations can be solved for ) When the source vibration frequency ω equals the mechanical resonant frequency m , Equation (5) for output voltage reduces to a familiar form.
This results in the familiar circuit model for the PZ EHD, shown at the left of Figure 3.
. These values are more representative of today's commercial devices.
. This can be understood as follows. For large N L G , the electric field is effectively shorted. As N L G decreases, the electric field in the EHD increases, and alters the effective spring constant of the cantilever beam. It is tempting to assume from the above that frequency tuning is possible only in the narrow range oc m [4]. However, as we will see below, the addition of a resonant electrical circuit allows the voltage to swing below zero and above oc V , thereby enabling a wider tuning range.
Coupled Oscillators
In the simulations in the previous section, we did not attempt to cancel the reactive admittance of the PZ capacitor, and we observed the degradation in output voltage.
the simulations above, the degradation is not large. However, in some cases, the PZ EHD has a large capacitance, which can substantially degrade output power at m . In Figure 5 Solution to the pole-splitting equation above, for the case The roots of the pole-splitting equation are shown in Figure 6 for several values of coupling constant . In Figure 5, we selected m mc , in order to optimize output power at discovered that, if we increased the load resistance, we could also optimize output voltage at w and w . (We will show in the next section that output power is also optimized at these frequencies). This analysis suggests that we can tune the EHD resonant frequency by varying mc .
We can gain further insight into the pole-splitting by returning to Equations (5) and (6). For small N L G , the following relationship holds between ) Using Equation (10) the force of the spring can be written as The above equation shows that, by tuning L, we can vary mc and vary the effective spring constant.
Equation (12) shows that the effective spring constant can be tuned over a wide range. It is also somewhat surprising that the peak voltages at and are 3.5× to 5.5× higher than max oc V . The simulations in this paper assume that the source magnitude Z is held constant as the frequency changes. As a result, the input acceleration increases in proportion to 2 , and . The important result is that the peak voltages away from resonance can be somewhat higher than max oc V , and the higher voltage enables frequency tuning.
Optimizing Output Power
In the previous section, we showed that voltage can be made to peak at frequencies and , , which are different from m . Figure 7 shows that power is also maximized at these frequencies. in Equation (5) is equivalent to varying the inductor.
Maximizing power with respect to mc gives the expression When we use Equation (13) to determine the value of mc that optimizes power at each frequency, the resulting voltage and power are shown in Figures 8 and 9. Equation (13) suggests that we need two strategies for optimizing power, depending on the source frequency . For frequencies near m , (Region 2), Equation (13) reduces to Note that, when , which is equivalent to matching the capacitive admittance (refer to Figure 3). When is above or below m (Regions 1 and 3), Equation (13) reduces to the pole-splitting Equation (9). Far from m , output power is maximized at the pole frequencies [roots of Equation (9)]. However, as approaches m , interaction between the poles shifts the max-power frequency [given by Equation (13)] slightly away from the pole frequency. Cammarano et al. [3] have derived an equation very similar to Equation (13): Equation (8) in [3]. They observe that the power conditioning system at the output of the EHD can be used to synthesize the complex load impedance required by Equation (13), and they comment on the challenge of reducing the power of such systems. Chang et al. [5] have implemented a switch-mode power conditioning system to the output of a PZ EHD, and have demonstrated the ability to harvest energy from two sources simultaneously:
Bias-Flip Technique
For a typical, discrete EHD, nF C mc 100 , and the inductor required to match this reactance at 100 Hz is impractically large: H L 25 . However, it has been shown that the Bias-Flip technique can be used to synthesize a reactive impedance for effective impedance matching [6,7]. This technique is suitable to ULP miniaturization. It utilizes a very small inductor together with ULP microelectronics to emulate an inductor that is large and tunable. The BF technique has been shown to be effective in maximizing the output power of PZ EHDs at m [7]. In this section, we will describe the Bias-Flip technique in the context of the equivalent circuit of Figure 3 describing a PZ EHD operating at the mechanical resonance frequency. The BF technique is illustrated in Figure 10. In the BF circuit, the large inductor is replaced by a small inductor, connected by MOS switches. When the switches are closed, a high frequency tank circuit is formed. After ½ period of oscillation of this tank circuit, the switches are opened, and the voltage on the capacitor has "flipped" adiabatically from +V to −V. In this paper, the switches are assumed to be ideal and lossless.
Refer to Figure 3. When an ideal inductor is used together with a matched resistive load In the worst case of very large mc C , the output power is degraded by several orders of magnitude, when no inductor is used. However, the Bias-Flip approach delivers power ) , which is % 81 / 8 2 of the max power obtained using an ideal inductor. This illustrates the effectiveness of Bias-Flip circuits to achieve high output power when mc C is large [7].
So far in this paper, we have discussed the case in which AC power is delivered to a resistive load. We have done this because the analysis can be performed in closed form. However, in many energy harvesting applications, it is necessary to rectify the AC power and store it in a battery or super-capacitor. The Bias-Flip technique is especially applicable to this case, as shown in [7].
The rectification circuit analyzed in [7] is shown in Figure 12. For simplicity, we assumed that the EHD is operating at the mechanical resonance frequency, and we use the equivalent circuit of Figure 3. The output AC voltage ) (t v is rectified in the diode bridge and stored on the capacitor RECT C that is maintained at voltage RECT V by the Energy Management Circuit. The analysis below assumes ideal diodes. Figure 12. Circuit to rectify and store the AC power being generated by the EHD. It is assumed that the EHD is operating at the mechanical resonance frequency.
Operation of the Bias-Flip rectifier is described with reference to Figure 13. When the capacitance is zero, as shown in Figure 13a, Bias-Flip is not required. , the diodes turn off, and ) (t v returns to zero following the curve . The presence of non-zero mc C degrades transferred power: Figure 13b. When the current turns positive, there is a negative bias on mc C that must be discharged before the voltage can swing positive. This delays diode turn-on, and forces a reduction in RECT V , both of which degrade transferred power. This degradation can be corrected by adiabatically flipping the bias on mc C when the current changes sign, as illustrated in Figure 13c. . When RECT V is low, the power transfer interval on off t t is long, but the power is low. When RECT V is high, the power transfer is high, but the transfer interval is short. In fact, for RECT V above a maximum value the diodes do not turn on, and no power is transferred. Figure 14 shows the power transfer as a function of RECT V , for various values of mc C . This simulation is made using the values k R in 10 and Hz m 100 Figure 15. Shows the rectified power as a function of mc C . For each point on the curve, RECT V was selected to give the max power transfer. Power is normalized to av P max , and capacitance has units Farads. Figure 15 shows that, for large mc C , output is severely degraded. However, the Bias-Flip circuit is effective in recovering most of the lost output power. This analysis confirms the conclusions of Ramadass and Chandrakasan [7] that for an EHD, operating at resonance, the Bias-Flip circuit is effective in canceling the reactive impedance of the device, and achieving near-optimum output power.
In the next section, we will demonstrate that the Bias-Flip technique can be used to form an effective LC tank circuit that, when coupled to the EHD can tune the resonant frequency.
Bias Flip for Frequency Tuning
In Section 5, we confirmed the effectiveness of the BF technique for power optimization at the mechanical resonant frequency. When m , and the equivalent circuit of Figure 3 applies, we can optimize power to the load by "canceling" or "matching" the reactive admittance of the capacitor with an inductor. We select an inductor value such that current from the source. We confirmed the finding of [7] that the BF inductor is effective in canceling capacitive admittance at m . In this section, we will demonstrate that the BF inductor can also be used to tune the resonant frequency of the EHD and optimize power at frequencies substantially different from m .
In order to maximize output power at any frequency, we need to maximize the input power delivered from the mechanical source to the EHD. In other words, we need to align the phase of the force with the phase of the source velocity.
In the following analysis, we assume the phase of , and the velocity of the source is ) sin . The source velocity has a phase of +90 o . The force acting on the EHD is given by Equation (3). Our goal is to maximize.
. From this, we conclude that input average power is maximized when F has phase +90°, matched to source velocity, and X has phase −90°. (2) Inductor optimized using (13) and (3) Inductor optimized using the pole-splitting Equation (9). In all three cases, 0 L G .
Additional insight into maximization of output power is seen in Figure 16. Here, we compare the phase of mechanical displacement ) ( X for three conditions Inductor optimized using the pole-splitting Equation (9). The phase is −90° for all frequencies.
The improvement in power at frequencies above and below m results from phase alignment between force and source velocity. Figure 17 shows output power for 3 conditions. Case #2 illustrates the case where the reactive admittance is chosen to optimize output power, but the load conductance N L G is kept at . Very little improvement is achieved, because the voltage is kept low by the high load conductance, and the voltage is ineffective in modulating the cantilever spring constant. Case #3 shows power improvement of ~50X compared to case #1. When we compensate for the increase in acceleration with frequency, case #3 demonstrates that it is possible to achieve output power at m that is comparable to the maximum power at m .
Additional insight into the mechanism of frequency tuning can be obtained by transforming the mechanical equations of motion to an equivalent circuit [1,8,9], as shown in Figure 18.
The subscript m denotes the mechanical circuit. ) ( S is used for velocity to avoid confusion with voltage; (b) Equivalent circuit model of Figure 18a, in which the electronic circuit is replaced by an electrical impedance Z e . (a) The equations for the mechanical portion of the equivalent circuit are shown below.
where e , defined in Figure 18, is given by Define m Z to be the impedance seen by the voltage source ) ( F V in Figure 18b. gives the pole-splitting equation, equivalent to Equation (9), in the limit The last term in the above equation can be used to tune the resonance frequency above or below the mechanical resonance frequency. The last term takes the form These results are summarized in Table 1.
Maximizing power in the three regions can be envisioned in term of an effective inductor. Alternatively, it can be envisioned in terms of setting the phase of the voltage ) ( V . The phase in each of the three regions is given in the (3) and (4), for the case of no inductor. These equations were solved subject to the boundary conditions.
In the case of no Bias-Flip, . The effect of the BF inductor is to change the phase of v(t) every half-period.
Using the voltage waveform, we calculated average output power. This is shown normalized to av P max in Figure 19. These simulations show that the BF technique is capable of achieving output power, comparable to the optimum power achievable with an optimized inductor. Moreover, the BF technique is self-tuning. If the bias is flipped whenever the source velocity crosses zero (as assumed in this simulation), the desired phase is maintained as the source frequency changes. No calculation is required to solve Equation (13). Figure 19. Normalized average power as a function of frequency. In Regions 1 and 3, the Bias-Flip technique (red and blue dashed lines) improves output power by ~100X compared to the case of no inductor and no BF (green line). Moreover, it gives output power that is comparable to the maximum power achievable with an optimized inductor (red and blue solid lines).
Analysis of the voltage waveforms reveals another aspect of self-tuning. In Region 1, the bias flips from negative to positive at 0 t and from positive to negative at 2 / T t , thereby emulating a +90° phase shift. In Region 3, the reverse happens. The bias flips from positive to negative at 0 t and from negative to positive at 2 / T t , thus emulating a −90° phase shift.
Conclusions
In the preceding sections, we have explained the principles for electrically tuning of PZ EHDs. These principles are summarized below.
Equation (11) shows that the effective spring constant of the mechanical resonator is a function of voltage. If the load conductance is large, the voltage is kept small, and the resonator responds only at the mechanical resonant frequency m . However, for small load conductance L G , the voltage can be used to tune the spring constant, and the resonant frequency of the mechanical oscillator.
In Regions 1 and 3, output power is maximized by maximizing input power (force x velocity), transferred from the source to the EHD. At frequencies below m (Region 1), this occurs when the phase of the voltage is +90° relative to the source vibration, and at frequencies above m (Region 3), output power is optimized when the phase of the voltage is -90 o relative to the source vibration.
This optimum phase relationship can, in theory, be achieved using a tunable inductor, whose value can be obtained from Equation (13). A large tunable inductor is not generally practical. However, the Bias-Flip technique can be used to emulate a large, tunable inductor. Previous work has shown that the | 4,548.6 | 2013-06-01T00:00:00.000 | [
"Engineering",
"Physics"
] |
Entropy, Economics, and Criticality
Information theory is a well-established method for the study of many phenomena and more than 70 years after Claude Shannon first described it in A Mathematical Theory of Communication it has been extended well beyond Shannon’s initial vision. It is now an interdisciplinary tool that is used from ‘causal’ information flow to inferring complex computational processes and it is common to see it play an important role in fields as diverse as neuroscience, artificial intelligence, quantum mechanics, and astrophysics. In this article, I provide a selective review of a specific aspect of information theory that has received less attention than many of the others: as a tool for understanding, modelling, and detecting non-linear phenomena in finance and economics. Although some progress has been made in this area, it is still an under-developed area that I argue has considerable scope for further development.
Introduction
Information theory as a tool for economics has a long history and at this point is wellestablished in many sub-fields. This foundational work was carried out by authors such as Kolmogorov [1], Theil [2], Wilson [3], Georgescu-Roegen [4], and Aoki [5], each contributing significantly to quite different fields within economics. A recent review of information theory at the agent level and economics can be found here [6] and a broader review of entropy in economics in general over the last 150 years can be found here [7]. Recently, many others have contributed key results to this body of work. At the market level Vogel et al. [8] used data compression and information theory to study different regimes of a financial market. Sornette has also written an earlier but highly informative review of work on markets as exhibiting critical phenomena in their non-linear dynamics [9]. At a similar scale but for housing markets Crosato et al. [10,11] have studied the criticality of city dynamics using maximum entropy techniques. At the individual agent level Dinis et al. [12] studied phase transitions in optimal betting strategies using the Kelly criterion.
This opinion piece argues for an alternative use of information theory that has been used earlier but has yet to make a significant impact in the field of economics or information theory: As a tool for the analysis of "critical phenomena" in economics. It follows on from earlier work I have completed applying the notion of critical phenomena to the abrupt breaks in time series data, such as market crashes, such as the 1987 crash [13], the Asian crisis of 1997 [14], the build up to the housing crisis of 2007 [15], and the COVID-19 crisis of 2020-2021 [16], all of which made use of information theory in its various forms. With collaborators, I have also explored the occurrence of bifurcations in micro-economics [17,18], as well as in housing markets [19,20], each using maximum entropy techniques. In order to make the case for information theory as a tool in the analysis of criticality in economics, I will argue for two important elements. The first is that critical phenomena, i.e., bifurcations, catastrophes, tipping points, etc., can be analysed most effectively using information theory due its intrinsic sensitivity to non-linear behaviour. The second is that market dynamics exhibit behaviour that is very much like what we should expect in critical phenomena.
These two points are covered in the next two sections and then some final points are discussed at the end.
Criticality and Statistical Measures
I begin by outlining and connecting some well established results that, to the best of my knowledge, have not previously been discussed in combination with each other. There is an early result due to Theil [21] that establishes the relationship between the amount of information shared between the dependent and the independent variables in a multiple regression analysis, and that it can be derived directly from correlations and partial correlations. The result is easy to state. Given a multiple regression analysis between a dependent variable X 0 and N independent variables X i ∈ {X 1 , X 2 , . . . X N } = X, the question arises as to how much each X i contributes to the behaviour of X 0 . Given the total correlation R between X 0 and X and the correlations r 0,1 between X 0 and X 1 , partial correlations r 0,2|1 between X 0 and X 2 conditional on X 1 , etc., then the total amount of information contributed from each of the X i to X 0 is a sum of their individual information contributions: where and as x is bounded on the interval [0, 1] this is a non-negative value corresponding to the information content, see the paper and references therein for the details. Contrast this approach to Scheffer et al. [22] (Box 3), in which the relationship between the non-stationary properties of the auto-correlation coefficient of an AR(1) process as it approaches a tipping point is analysed and we see that to first order in Equation (1), i.e., I(r 2 1,0 ), there is an informational analogue to Scheffer et al.'s analysis of the precursory signals of an impending tipping point.
There has already been progress in developing this direction as Barnett and colleagues [23] studied the relationship between "Granger causality" (G-causality), first developed by Granger in econometrics [24], and transfer entropy (TE). According to G-causality, given a vector X of stochastic variables that evolve in time it is said that "X i G-causes X j " if, by including X i in the predictive information set of X j , the subsequent prediction of X j is improved beyond the extent to which X j is already able to predict its own future. The central insight of the work of Barnett et al. is that, for Gaussian variables, G-causality is equivalent to TE, making a direct connection between the predictive analysis of vector auto-regression and information theoretical approaches to causal inference. This becomes relevant to critical phenomena not only because of the relationship with Scheffer et al.'s work but also because TE peaks before the phase-transition in the two-dimensional Ising model [25], where the Gaussian assumption no longer holds, i.e., TE becomes a candidate for the analysis of phase transitions at precisely the point where the relationship between TE and G-causality is expected to break down.
There is a similar correspondence between Pearson correlations and mutual information (MI) in the Ising model. Away from the critical temperature there is an exponential decay in the correlations between the individual spins. However, as the temperature approaches the critical temperature, the relationship between correlations and MI become strongly non-linear, although still expressible in closed form [26]. A distinguishing characteristic between MI and TE is that TE peaks before the phase transition (on the disordered side of the transition) whereas the MI peaks (diverges) exactly at the phase transition.
A final example is the use of Kullback-Leibler divergence (KL-divergence) to measure the statistical separation between probability distributions. Both MI and TE are specific examples of KL-divergence but the more general form is useful in its own right. It is defined for two discrete probability distributions P(X) and Q(X) for X = {X 1 , X 2 , . . . , X n } as: Although the KL-divergence is central to MI and TE, it is also central to other information measures, specifically the Fisher information (FI) which has also been used in the study of critical phenomena. To see the relationship start with a θ-parameterised family of distributions P(X|θ), then the KL-divergence between two members of this family is D KL ((X|θ); (X|θ )) and as the divergence is minimised (zero) when θ = θ we can expand this around θ to second order in θ [27] (Section 3.3: Information Measures): where the matrix of second derivatives (the elements are denoted ∂ i,j D(θ; θ )) in this equation is the FI matrix, i.e., the FI is the first non-zero term in the expansion of the KLdivergence about θ = θ . We note that the FI is known to measure the gain in transient sensitivity of a distribution [28]. In that work, Prokopenko et al. were able to relate the ∂ i,j D(θ; θ ) terms to the rate of change in the corresponding order parameters θ. Of relevance to the current article is that these relationships allow for the identification of second-order phase transitions via the divergence of individual ∂ i,j D(θ; θ ) terms of the FI matrix. This work was later generalised to the Fisher TE [29], which was used to capture both transient and contextual aspects of the second order phase transition of the two-dimensional Ising model.
Critical Transitions Are a Phenomena of Markets
One of the first approaches to using statistical measures to understand sudden behavioural changes in financial markets is the work of Onella et al. [30] on the "Black Monday" crash on 19 October 1987. In that study they used a modified form of the Pearson correlation coefficient to measure the dyadic relationships between pairs of equities. This measure begins with the correlations between all pairs of equities ρ i,j and transforms them into a distance measure d i,j = 2(1 − ρ i,j ) which results in a distance matrix that can be thought of as a network of distances between equities. The underlying correlations were based on a window of time: [t a , t b ] that was a subset of the complete time series, and then through a sliding of this window over the whole time series a sequence of equity trees could be built up and the dynamical properties of the market correlations could be studied as Black Monday approached. What was observed is that the equity tress collapsed to a star network at the point of the market crash, very similar to the abrupt transitions observed in the topologies of networked systems going through a phase transition [31]. This network approach has been applied in theoretical and empirical studies of networked equity markets in order to test the robustness of the phase transition idea, see for example the work of Kostanjvcar et al. [32].
This approach was extended to information theoretical measures in two distinct ways in order to further understand market crises as critical phenomena. In the first instance, the d i,j measures were replaced with MI and the same analysis as that of Onnella et al. was carried out for the subsequent MI network [15]. In that study, it was shown that there are peaks in the MI at crisis points as predicted by the Matsuda et al. [26] study of the Ising model, and, furthermore, the MI could be broken up into its entropy and joint entropy components in a diagnostically informative fashion, for example distinguishing between the market disruption of the 11 September 2001 attacks which had no discernible increase in joint entropies, only an increase in the entropy terms, and the 1987 crisis which had a significant increase in the joint entropies. It was also noted that there was a peak in MI away from any known critical points, suggesting that MI may be identifying other non-linear transients indicative of the market restructuring in more subtle ways than market crashes. In a second extension to the Onnela work a modified version of TE that accounts for the continuous flow of information through the market (rather than artificially discretising the data) was applied to the Asian financial crisis of 1997 [14] in order to build a network of information flows around a market crisis point. The key finding was that Pearson correlations and continuous TE distinguish between qualitatively distinct aspects and that continuous information flows are a more sensitive measure of dynamics during a crisis.
Other approaches to modelling criticality in economic markets have focused on the application of potential functions to market dynamics in order to test for the statistical significance of tipping points in uni-variate times series. In several recent papers [33][34][35], researchers have used the stochastic form of Thom's catastrophe theory put forward by Cobb [36] and Wagenmakers et al. [37] to examine the empirical evidence for critical transitions in housing and equity markets. This follows on from a recent re-evaluation of catastrophe theory in economics as argued for in the review by Rosser, Jr. [38]. In principle, if a system has a well-defined potential function (sometimes "potential landscape"), a necessary element for catastrophe theory, then the system should also be susceptible to the methods proposed in a variety of fields [39][40][41][42] for the detection of nearby critical transitions, which brings us back to the study mentioned above by Scheffer et al. [22]: nearby critical points can (sometimes) be detected using statistical methods that measure the progressive deformation of the probability distributions caused by the deformation of the potential function near a critical point.
Limitations and Future Directions
The points laid out above are not without their issues and there are reasonable arguments for why this approach is less attractive than traditional statistical methods. However, I believe most of these can be addressed and here I divide them into two broad classes: issues of practice and issues of principle.
Some practical issues are the same for every discipline that uses information theory: the computations are expensive, there are fewer out-of-the-box software packages available, and more data are needed to obtain statistically reliable results. The first point is simply one that we may need to accept, even as computers become faster, it will likely remain the case that, for example, the Pearson correlation will be faster to compute than the corresponding MI. However, the computations will get faster in absolute terms as computers get faster, and other fields with large datasets, such as neuroscience, have seen the benefits of these new methods [43,44] with efficiency gains being made as well [45,46]. On the other hand software packages are becoming more readily available, and economics can benefit from the software advances that have been made in other fields. Two popular packages that have come from neuroscience are JIDT [47] and TRENTOOL [48] and their successor IDTxL [49]. As the methods become more readily used no doubt more implementations will become available. The data problem is a constant issue in economics, independent of the arguments made above, and aside from financial and industrial economics where data are rich and progress was initially quite rapid as computer scientists and physicists worked on market dynamics [50], data tends to be more sparse. However, while infrequently sampled time series and non-stationary data can make long term temporal analysis and prediction problematic, there is often considerable high resolution geospatial data, for example tax revenue or house prices indexed by postcodes. From this point of view long term prediction may still be difficult but temporally localised dynamics is achievable if the information theory tools can be adapted accordingly to suit the task at hand. It is also hoped that as data limitations more clearly become the bottleneck to better analyses, then private and government agencies will gather more data and this will become less problematic.
Another issue arises though, and it is a matter of principle rather than practice: Is information theory more useful than simply a new tool? In neuroscience and artificial intelligence there is a good "in principle" argument for why information theory is useful, it measures the amount of information being stored, processed, and transmitted within a complex adaptive system. For example Zhu et al. [51] studied neuromorphic nanowire networks using TE and active information storage, finding that information theoretical values peak when the networks transition from a quiescent state to an active state, illustrating the relationship between information theory as a measure of computational capacity and criticality in an artificial system. Likewise, other studies have shown that biological brains may be poised at or near a critical state [52] where it has been argued the brain is at a point of "self-organised criticality" , a term introduced by Bak [53], and see the recent critical review by Girardi-Schappo [54]. Others have argued that this may be a widespread property of many other systems as well, see, for example, the recent article by Tadić and Melnik [55]. However, the case has yet to be made that, at this more conceptual level, information theory and criticality adds to economic discourse, so I would like to discuss one, rather speculative, path through which this is relevant to economics. The point is fairly straightforward, Mirowski and Somefun [56] and Axtell [57], amongst others, have argued that markets and economies are computational processes in their own right, as Axtell frames it: There is a close connection between agent computing in the positive social sciences and distributed computation in computer science, in which individual processors have heterogeneous information that they compute with and then communicate to other processors. This is very much in the same vein as how neuroscientists might describe the processing of information in the human brain at the neuronal level [58]. The analogy does not map across in a trivial way though and care is needed. In a financial market, for example, instead of electrical signals between neurons price movements are the primary means of communicating and coordinating economic activity, and this might, at a suitably high level, justify the view that a market or an economy is indeed a computational process. However, market traders do not form long term price signalling relationships between each other in the way that neurons form connections with one another and so we need to be careful about the precise specification that comes from this analogy. One way in which we can keep the brain-market analogy but make it more pertinent is to take the recent work of Solé on "liquid brains" [59] that have been used as a computational model of ant communities as the analogy, rather than the "solid brains" of neural networks with their more rigid connections. This brings us to the point of self-organised criticality in economics and why it might be a relevant lens through which to see market dynamics. In this view, which has been espoused several times in recent work [60][61][62], markets need to be able to sensitively adapt to informational changes in such a way that allows prices to reflect news, and like liquid brains a critical or near critical state of the market may be the most effective position in order for a market to do so. | 4,292.4 | 2022-01-28T00:00:00.000 | [
"Computer Science"
] |
Polymer–Metal Bilayer with Alkoxy Groups for Antibacterial Improvement
Many bio-applicable materials, medical devices, and prosthetics combine both polymer and metal components to benefit from their complementary properties. This goal is normally achieved by their mechanical bonding or casting only. Here, we report an alternative easy method for the chemical grafting of a polymer on the surfaces of a metal or metal alloys using alkoxy amine salt as a coupling agent. The surface morphology of the created composites was studied by various microscopy methods, and their surface area and porosity were determined by adsorption/desorption nitrogen isotherms. The surface chemical composition was also examined by various spectroscopy techniques and electrokinetic analysis. The distribution of elements on the surface was determined, and the successful bonding of the metal/alloys on one side with the polymer on the other by alkoxy amine was confirmed. The composites show significantly increased hydrophilicity, reliable chemical stability of the bonding, even interaction with solvent for thirty cycles, and up to 95% less bacterial adhesion for the modified samples in comparison with pristine samples, i.e., characteristics that are promising for their application in the biomedical field, such as for implants, prosthetics, etc. All this uses universal, two-step procedures with minimal use of energy and the possibility of production on a mass scale.
Introduction
Metals and metal alloys have been used in medicine for at least 5000 years [1], and they have been irreplaceable for many years for their excellent mechanical properties, biocompatibility (in the case of noble metals such as gold) or bioactivity (e.g., the possibility to achieve osseointegration in the case of titanium alloys).However, the main problems with metal prostheses were their bacterial attachment and colonization [2].A bacteria-contaminated implants can cause, for example, acute cellular rejection [3].As an alternative, in the second half of the 20th century, polymers were introduced into medicine and pharmacy.They brought along revolutionary solutions to the treatment of various disorders and diseases and helped in prosthetics [4,5], drug delivery [6,7], and wound healing [8].
Today, new polymers are continually being produced with better characteristics including outstanding and tissue-like mechanical properties [9,10] and excellent biocompatibility [11,12].Their high plasticity (shaping as demanded) arises from the preparation methods, such as heat-driven polymerization [13] or usage of three-dimensional printers [14], by which the monomer is put into the meld of a desired shape before its polymerization.
Composites consisting of metallic and polymeric parts with significantly enhanced properties, such as a perfect balance between flexibility and high toughness of the mate-Polymers 2024, 16, 508 2 of 13 rial [15], open new applications, e.g., in a trans-tissue (bone and ligaments) region [16,17].Conventionally, composites are created using "mechanical" methods, consisting of smelting and casting, or polymer interlocking during polymerization.Such operations are typically performed under elevated temperatures or via exothermic reactions that are highly powerconsuming, expensive, and unstable in certain cases.Also, there is always a possibility of generating internal or thermal stresses in the metals or unintended changes in their original bio-characteristics [18].Hence, new methods of preparing such composites are still being sought.
One of them may consist of the covalent bond between these two materials: a metal and a polymer.Many previous works showed that functional groups of some compounds have a high potential to achieve bonding between materials of several types [19].A reduction in these functional groups using a variety of processes (e.g., spontaneous or electrochemical diazotization) will create radicals, which can be utilized for covalent binding of the rest of the compound onto the surfaces of almost any solid material [20][21][22][23].
Several studies on the chemical bonding of metals and polymers have been published up to now.Alageel et al. [24] presented a method for the chemical binding of Ti to poly (methyl methacrylate) using aryldiazonium salt (p-phenylenediamine) as a coupling agent.This procedure leads to an excellent enhancement in the mechanical properties of this composite compared with the reference samples.Related results were obtained via a different pathway on alloy/polymer composite prepared by grafting the surface of polyamide 6 polymer with 4-nitrobenezenediazonium (NBD) salt using L-ascorbic acid (LAA).In this way, an intermediary organic layer was created, leading to an enhancement in the mechanical properties of the resulting composite and an increase in its hydrophilicity [25].Zheng et al. [26] described a successful bioinspired bridging between Li 7 La 3 Zr 2 O 12 alloy nanofibers and poly (ethylene oxide) by using an azole-containing compound (Dynasylan Imeo).Although this method showed significant improvements in the characteristics of the resulting materials (mainly in tensile strength), this approach has limitations due to its dependence on the chemistry of the alloy of choice, which can decrease the universality and versatility of this method and prevent it from being applied over a long line of other alloys or metals.However, the chemical stability of the bonding needs is worthy of further study since "unbinding" can happen easily in environments common in biomaterial applications.
In this work, we present a low-cost and facile chemical approach for bonding metals/alloys with polymers via an alkoxy-functional group (R-O-R') as an intermediary agent.The method leads to a composite material with increased surface hydrophilicity, chemically stable bonding, and enhanced bacterial anti-adhesive properties.The obtained results demonstrated that the alkoxy group is a favorable candidate for achieving the coupling of metals/alloys with polymers and the utilization of the advantageous properties of both.The prepared composites could find applications in new, previously unexplored biomedicine fields.The main advantage of this method is the ability to apply it theoretically to any metal/alloy and polymers because it does not depend on their chemistry but on the properties of the alkoxy amine.
Materials and Methods
To achieve the maximum usability of the resulting composite material in various applications, a relevant metal/alloy and polymer had to be chosen.Considering the possibility of integrating the properties of both, we selected foils of titanium (99.6%, 0.5 mm, Goodfellow, Huntingdon, UK) as the metal and foils of stainless steel (SS) AISI 316 (0.5 mm, Goodfellow, Huntingdon, UK) as the metal alloy.Both types of foils were cut into 10 × 10 mm 2 samples and cleaned by ultrasound in acetone and deionized water for 15 min each.These samples were split into two groups: (i) pristine samples, to study the characterization and functionality before grafting and modification, and (ii) samples intended for grafting and modification.
As an additive polymer layer, polyethylene glycol (PEG) was selected for its variety of applications and facile manipulation.We used PEG (Goodfellow, Huntingdon, UK) of different molecular weights, specifically, liquid (Mn of 400) and crystals (Mn of 6000), that were dissolved in methanol to reach a concentration of moles of polymeric chains of 1.3 × 10 −2 mol/L and stirred in ultrasound until the solution was fully transparent and homogenous.
Salt Preparation and Reduction
For the grafting process, alkoxy amine was prepared according to the method described earlier [27].The salt reduction process started with dissolving 0.07 g of p-toluene sulfonic acid (P-TSOH) in 1 mL of acetic acid (CH 3 COOH) at 25 • C.After complete dissolving, 0.03 mL of tert-butyl nitrite was added gradually to the mixture and stirred with a magnetic stirrer until a homogenous solution was formed.After that, 2.5 × 10 −3 g of the alkoxy amine was added to the solution and stirred for 40 min.Finally, diethyl ether was used and added to the solution with a ratio of 1:1 and centrifuged at a speed of 7500 rpm for 30 min until full decantation of the salt.Then, the salt was washed and centrifuged one more time with diethyl ether.The remaining salt is reduced alkoxy amine diethyl (1-((1-(4-amino phenyl) ethoxy) (tert-butyl) amino)-2,2-dimethyl propyl) phosphonate.
Chemical Grafting
An aqueous solution of the reduced alkoxy amine with a concentration of 5700 mol/m 3 was prepared, into which the pristine samples of Ti and stainless steel were immersed for 30 min.at room temperature 25 • C. Subsequently, the samples were washed with deionized water (3×) and then with 98% (v/v) methanol (3×).
Surface Modification
The polymer solutions were deposited on the surface of the grafted samples by a spin coater (1000 rpm, 1 min) to produce a homogeneous polymer layer of unified thickness.To initiate coupling, a source of UV-C light (280 nm, with an intensity of 2000 mW/cm 2 ) was used for 1 h at a distance of 2 cm from the samples.The chemical grafting and surface modification steps are demonstrated in Figure 1.
Methods of Characterization
To confirm the chemical bonding between the surface of metal/alloys and the organic layer on one side and then between the organic layer with the polymer on the second side, Raman spectroscopy was measured on a portable ProRaman-L spectrometer (laser power 15 mW) Raman spectrometer with 785 nm excitation wavelength.Spectra were measured 30 times, each of them with a 3 s accumulation time to detect the vibrational modes of the
Methods of Characterization
To confirm the chemical bonding between the surface of metal/alloys and the organic layer on one side and then between the organic layer with the polymer on the second side, Raman spectroscopy was measured on a portable ProRaman-L spectrometer (laser power 15 mW) Raman spectrometer with 785 nm excitation wavelength.Spectra were measured 30 times, each of them with a 3 s accumulation time to detect the vibrational modes of the molecules involved.Further, the surface-enhanced Raman spectroscopy (SERS) technique was used to generate a peak distribution map of the activated and reduced salt on the surface of the grafted samples.The usage of the SERS technique was chosen for the mapping due to the high accuracy of detection (single-molecule level) to give a precise distribution map of the activated, reduced, and grafted alkoxy amine, for which the usage of standard Raman is not able to constrict and to stack the spectra accurately at this stage of the modification process.
Changes in the surface roughness (R a ) of pristine samples (SS or Ti) before and after grafting and the deposition of the polymer were measured by a confocal laser scanning microscope (CLSM; Olympus OLS 3100) using a magnification lens (×50) without optical zoom.Roughness was calculated using automatic calibration; it was collected from 10 different positions, and then the average was calculated to acquire accurate roughness on a micron scale.
The electrokinetic potential of all samples was determined by a SurPASS instrument (Anton Paar, Graz, Austria) in a cell with an adjustable gap at 25 • C and a pH of 6.7.The experimental error of the measurement was ±5%.For the determination of the zeta potential, the streaming current method and the Helmholtz-Smoluchowski equation were used.Specific surface area and pore volume were determined from nitrogen adsorption/desorption isotherms with a NOVA3200 (Quantachrome Instruments, Boynton Beach, FL, USA) using NovaWin software.The samples were degassed for 24 h at 60 • C. Brunauer−Emmett−Teller (BET) analysis was applied to determine the total surface area, and the Barrett−Joyner−Halenda (BJH) model was applied to determine pore volume.
The surface structure was studied using scanning electron microscopy (SEM) (Tescan Lyra 3 GMU) with a high voltage of 20.0 kV and 4.15 KX magnification.The elemental composition was measured by an energy dispersive spectroscopy (EDS) analyzer (X-MaxN) with a 20 mm 2 SDD detector (Oxford Instruments, Abingdon, UK) embedded with the basic (SEM) device and evaluated using AZtecEnergy software to determine the spatial distribution of the elements and their approximate concentrations in the samples.
X-ray photoelectron spectroscopy (XPS) was performed using an Omicron Nanotechnology ESCAProbeP spectrometer fitted with a monochromated Al K Alpha X-ray source working at 1486.6 eV to study the composition, and these results were also used to determine the thickness of the layer (organic layer + polymer), as demonstrated before [28].For this purpose, the well-known equation I/I 0 = exp(−d/λ sinθ) was used, where d is the layer thickness, λ is the free path of the photoelectron in the organic layer, the angle θ with respect to the plain surface is 90 • , and I/I 0 is the ratio of detected intensities of the elements Fe/Ti before and after the modification.
Sample functionalities were extensively studied, starting with their surface wettability, which is supposed to be radically shifted after the polymer application and by the electrokinetic analyses.The wettability test consist of measuring the static and dynamic water contact angle (WCA) by goniometer Krüss (DSA 100).For the static angle, deionized water droplets with a volume of 2 µL were dropped on 10 different positions on the surface of both the pristine and modified samples.The dynamic CA measurements were performed by deposition of the water drop on the sample surface, followed by increasing and subsequently decreasing the water drop volume, varying between values of 2 −10 µL with a speed increase/decrease of 0.03 mL•min −1 , with simultaneous measurements of the contact angle.
Wettability tests were also used to evaluate the chemical stability of the bond.Two sets of samples were prepared (i) the first one consisting of modified samples of titanium or Polymers 2024, 16, 508 5 of 13 stainless steel as aforementioned and (ii) the second one of titanium or stainless steel with a deposited layer of the polymer modified under the same conditions but without the grafting step on the surface (i.e., metal/alloy with deposited PEG only).Both sample sets were soaked in deionized water for 30 min, air-dried, and measured by the goniometer one more time.The changes in WCA were measured at various positions and repeatedly 30 times.The establishment of chemical bonding will protect the polymer from being dissolved in water and will keep the WCA stable at hydrophilic values.In the case of missing chemical bonding, the polymer dissolves, and the goniometer reading should indicate significant changes in WCA.
Further, we studied the bacterial anti-adhesive activity of the prepared materials.For this purpose, two bacterial strains were chosen: Escherichia coli (E.coli, DBM 3138) as a model of Gram-negative bacteria and Staphylococcus epidermidis (S. epidermidis, DBM 2124) as a model of Gram-positive bacteria.Both bacterial strains were from the microorganism collection of the Department of Biochemistry and Microbiology at the UCT Prague (Czech Republic).To assess the bacterial anti-adhesive potential of the prepared materials, we used the drop plate method similarly as reported in [29,30].First, Luria−Bertani (LB) liquid medium was inoculated with one colony-forming unit (CFU) of either E. coli or S. epidermidis [31,32] and cultivated in an orbital shaker at 120 rpm at 37 • C for 18 h.Then, the inocula were diluted in phosphate-buffered saline (PBS, sterile) at pH = 7.4 to achieve three concentrations, i.e., 8 × 10 8 , 4 × 10 7 , and 1 × 10 4 of E. coli and S. epidermidis per mL.The evaluated samples were immersed into the bacterial suspensions and evaluated in triplicates.Then, the samples were incubated at room temperature for 1, 4, and 24 h while gently shaking.After these time points, 25 µL aliquots in five technical replicates were taken from each sample (after gentle mixing), loaded onto pre-dried LB agar plates, and incubated at 37 • C for 24 h.As a control, bacteria cultivated only in PBS, without a material sample addition, were used as well as bacterial suspensions cultivated with pristine Ti and pristine SS.After the 24-h incubation, the numbers of CFU of each bacterial strain were counted using Image J software.
In addition, to examine the bacteria incubated with the evaluated materials in greater detail, an SEM analysis of the samples was performed.After 24 h of incubation, the samples were gently washed with 1 mL of PBS and then fixed using the mixture of 2% formaldehyde with 2.5% glutaraldehyde in PBS for 4 h at 23 • C.After that, the samples were gently washed with PBS two times and then dehydrated similarly as described in refs.[33,34].Briefly, the samples were incubated with ethanol solutions in water for 10 min in the following order: ethanol: water (v/v): 50, 60, 70, 80, 90, and 98%.After that, hexamethyl disiloxane (Sigma Aldrich, St. Louis, MO, USA) was added for 10 min twice and then removed, and then the samples were dried at 37 • C for 16 h.This process was followed by the sputtering of a 5 nm platinum layer and then examination by (SEM) at 10 different positions.
Results and Discussion
The process of the chemical coupling of titanium (Ti) or stainless steel (SS) with PEG can be described as a two-step procedure: (i) the reduction of the salt, as demonstrated, left free radicals, which allows the salt to be grafted on the surfaces of any solid material (here, Ti and SS), and (ii) the deposition of the PEG and then using UV-C led to the homolysis of the N-O bond of the salt, which forms radicals allowing for the bonding of the alkoxy amine and both PEG 400 and PEG 6000.However, the WCA measurements of PEG 6000 showed a more hydrophilic character; therefore, the following measurements are focused on PEG 6000.
The successful grafting of the salt was confirmed by Raman spectroscopy with new peaks appearing in the gathered spectra.These new peaks are found at Raman shift 450-500 cm −1 and 1400 and 1600 cm −1 for the aromatic ring, 550-600 cm −1 , 700 cm −1 , and 1300 cm −1 for Isopropyl (i-pr), 800-900 cm −1 and 1300 cm −1 for N-O, 1100 cm −1 and 1320-1350 cm −1 for P=O, and finally, at 1200 cm −1 for C-N [35].Also, the successful modification with PEG 6000 can be confirmed by the changes in certain peaks, related to the interaction of PEG 6000 with the salt (see Figure 2A,B).These are related to the break of the N-O bond in the alkoxy amine, the disappearance of the peak at 1300 cm −1 , and the formation of a new C-O bond between 1350 and 1400 cm −1 between PEG and alkoxy amine.Moreover, the homogenous distribution of the activated reduced salt on the surface of the stainless steel and titanium was confirmed by SERS (see Figure 2C,D).The chemical composition of the samples before and after the modification was studied by EDX and XPS techniques.The results are presented in Table 1, where corresponding results for the concentrations of substrate elements (Fe, Cr, Ti, etc.) are shown.Both methods confirmed a dramatic increase in the concentrations of the alkoxy amine groups and the elements of the PEG 6000 polymer such as C, O, and N on the surfaces after the modification for both of the substrates, with the biggest portion of the increase being for C (between 4 and 8%), O (4-6%), and N (1-2%), respectively, which correspond with the ratios of these atoms within the formula of PEG.It is also possible to notice a decrease in the elements forming the substrates only after the modification as the penetration of the analysis is reduced because of the organic + polymer extra layer.It can also be seen that the percentage of elements forming PEG 6000 is higher for XPS than for EDX due to the depth of analysis achievable by both individual techniques.
To calculate the thickness of the layer (d), we first calculated the value of λ, which was deduced from the empirical formula derived by Seah and Dench: λk = An/E 2 K + Bn/ E 1/2 K ., where Ek is the kinetic energy of photoelectrons.
After the calculations, it was found that the thickness of the organic/ polymer bonded with the Ti/ SS layer was d ≈ 2.8 nm and d ≈ 2.7 nm, respectively.The chemical composition of the samples before and after the modification was studied by EDX and XPS techniques.The results are presented in Table 1, where corresponding results for the concentrations of substrate elements (Fe, Cr, Ti, etc.) are shown.Both methods confirmed a dramatic increase in the concentrations of the alkoxy amine groups and the elements of the PEG 6000 polymer such as C, O, and N on the surfaces after the modification for both of the substrates, with the biggest portion of the increase being for C (between 4 and 8%), O (4-6%), and N (1-2%), respectively, which correspond with the ratios of these atoms within the formula of PEG.It is also possible to notice a decrease in the elements forming the substrates only after the modification as the penetration of the analysis is reduced because of the organic + polymer extra layer.It can also be seen that the percentage of elements forming PEG 6000 is higher for XPS than for EDX due to the depth of analysis achievable by both individual techniques.
To calculate the thickness of the layer (d), we first calculated the value of λ, which was deduced from the empirical formula derived by Seah and Dench: , where E k is the kinetic energy of photoelectrons.After the calculations, it was found that the thickness of the organic/polymer bonded with the Ti/SS layer was d ≈ 2.8 nm and d ≈ 2.7 nm, respectively.
The data gathered from the CLSM showed that the surface roughness R a of both the pristine and modified samples for SS stayed almost unchanged at an R a of ca.1.4 µm to 1.3 µm after the modification.For the Ti samples, however, the surface roughness slightly decreased after the modification from an R a of ca.1.8 to 1.2 µm.However, no significant changes in the surface morphology were observed by the SEM technique, with minor changes noticed on the original topography of the Ti (see Figure 3A for pristine Ti and Figure 3C for modified Ti).In the case of stainless steel, differences between the fusion lines by their number and depth (Figure 3B) were noticed, while the modified sample had fewer of these lines with obviously less depth (Figure 3D).
The changes in the surface roughness of the samples before and after the modification were proven also from the surface area and porosity values determined by adsorption/desorption nitrogen isotherms, as presented in Table 2.The surface area and porosity increased after the modification of both stainless steel and Ti, with more apparent changes in the Ti samples.
Changes in surface chemistry and polarity were confirmed also by electrokinetic analysis.The values of zeta potential are presented in Table 2 (the last row).These results are quite interesting, especially after the modification, when the zeta potentials changed differently for both substrates: SS and Ti.For SS, the zeta potential changed to lower negative values, from −51.3 ± 2.8 mV for the pristine SS surface to −39.0 ± 2.3 mV for the modified one, which indicates some positively charged groups on the surface (presence of amino groups) [36].The Ti surface, however, after the modification showed more negative values of zeta potential −52.1 ± 5.6 mV in comparison with −45.7 ± 1.4 mV for the pristine Ti surface.The change can be affirmed by more negatively charged oxygen atoms on the modified surface of Ti.The diazotization process has the potential to introduce negatively charged groups onto the surface of titanium (Ti).During diazotization, a diazonium salt is typically formed, and the resulting diazonium group can be covalently attached to the Ti surface.The presence of nitrogen in the diazonium group, especially in the form of a negatively charged nitrosonium ion (NO + ), can contribute to the overall charge of the modified surface.As was reported previously, some compounds bond to different surfaces Polymers 2024, 16, 508 8 of 13 differently, with a preferential orientation of some functional groups depending on the polar/unipolar behavior or different roughness of substrate surfaces [36].These results can be confirmed by XPS measurement (Table 1).Here, it is clear that the amount of N atoms is 0 at unmodified samples (both Ti and SS), while after modification, the amount of N atoms is visible and is slightly higher at modified SS.Therefore, this means a higher amount of amino groups on the surface at SS, which resulted in less negative zeta potential at the modified SS in comparison with the modified Ti.We can also see the amount of oxygen atoms (O amount), which has an impact on the negative surface charge.It is clear that a higher amount of O was determined in both cases at the Ti samples.Therefore, the zeta potential is much more negative for the Ti samples (the pristine and modified ones) in comparison with the SS samples.
amount of amino groups on the surface at SS, which resulted in less negative zeta potential at the modified SS in comparison with the modified Ti.We can also see the amount of oxygen atoms (O amount), which has an impact on the negative surface charge.It is clear that a higher amount of O was determined in both cases at the Ti samples.Therefore, the zeta potential is much more negative for the Ti samples (the pristine and modified ones) in comparison with the SS samples.The modification of the samples led to an increase in the wettability of the surfaces of the composites, manifested by a lower contact angle, i.e., the WCA.This was confirmed using both dynamic and static WCA goniometry.As can be seen from Figure 4A, the static WCA significantly decreased after the material modifications, where the decrease was especially large for PEG 6000, consisting of longer chains in comparison with PEG 400.Also, the dynamic WCA results correspond with those obtained for the static WCA; the hydrophilic surface was kept at similar values whether the droplet volume was advancing or The modification of the samples led to an increase in the wettability of the surfaces of the composites, manifested by a lower contact angle, i.e., the WCA.This was confirmed Polymers 2024, 16, 508 9 of 13 using both dynamic and static WCA goniometry.As can be seen from Figure 4A, the static WCA significantly decreased after the material modifications, where the decrease was especially large for PEG 6000, consisting of longer chains in comparison with PEG 400.Also, the dynamic WCA results correspond with those obtained for the static WCA; the hydrophilic surface was kept at similar values whether the droplet volume was advancing or receding, in contrast to the case of the more hydrophobic pristine samples.These exhibit bigger differences, which is one of the common properties of hydrophobic surfaces, see Figure 4B.These results are the same for all substrates, and they correspond well with those of the zeta potential tests.
Polymers 2024, 16, 508 10 o receding, in contrast to the case of the more hydrophobic pristine samples.These exhi bigger differences, which is one of the common properties of hydrophobic surfaces, Figure 4B.These results are the same for all substrates, and they correspond well w those of the zeta potential tests.
The results of the chemical stability tests show a higher performance of the modif samples after being immersed in water.As anticipated, the immersion leads to the d solving of the PEG deposited layer, which was not pre-grafted, leading to the instant "c lapse" of the composite hydrophilic character.In the case of the modified samples w the help of the grafted salt, the PEG 6000 chains stay attached to the surface (see Figu 4C).These findings are specifically important in showing the durability of the modif composites that can survive the next step, which is the tests of their bacterial anti-adhes properties.The bacterial anti-adhesive properties of the prepared materials were determined CFU counting of two bacterial strains of S. epidermidis and E. coli, which were in cont with the evaluated samples for 4 h.For this purpose, three concentrations of bacterial ocula were chosen, i.e., 8 × 10 8 , 4 × 10 7 , and 1 × 10 4 per mL.For E. coli at the two high concentrations, 4 h contact with the prepared materials did not result in a decrease in number of grown bacteria.However, for S. epidermidis at the 8 × 10 8 concentration, th was a ca.20% decrease in the bacteria grown when incubated with the modified Ti or samples, which was further pronounced to a ca.60% decrease at the lower 4 × 10 7 per m The results of the chemical stability tests show a higher performance of the modified samples after being immersed in water.As anticipated, the immersion leads to the dissolving of the PEG deposited layer, which was not pre-grafted, leading to the instant "collapse" of the composite hydrophilic character.In the case of the modified samples with the help of the grafted salt, the PEG 6000 chains stay attached to the surface (see Figure 4C).These findings are specifically important in showing the durability of the modified composites that can survive the next step, which is the tests of their bacterial anti-adhesive properties.
The bacterial anti-adhesive properties of the prepared materials were determined by CFU counting of two bacterial strains of S. epidermidis and E. coli, which were in contact with the evaluated samples for 4 h.For this purpose, three concentrations of bacterial inocula were chosen, i.e., 8 × 10 8 , 4 × 10 7 , and 1 × 10 4 per mL.For E. coli at the two higher concentrations, 4 h contact with the prepared materials did not result in a decrease in the number of grown bacteria.However, for S. epidermidis at the 8 × 10 8 concentration, there was a ca.20% decrease Polymers 2024, 16, 508 10 of 13 in the bacteria grown when incubated with the modified Ti or SS samples, which was further pronounced to a ca.60% decrease at the lower 4 × 10 7 per mL concentration of bacteria for the modified SS samples in comparison with the untreated control as well as pristine samples.Notably, at the lowest concentration of bacteria, i.e., 1 × 10 4 per mL, the modified Ti or SS impacted the number of both bacterial strains E. coli and S. epidermidis, see Figure 5A.At these conditions, there was a ca.30% decrease in the E. coli CFU number after 4 h of incubation with pristine and modified SS and pristine Ti.An even more pronounced effect on the lower adhesion of bacteria was found for the modified Ti, where 4 h of contact with the bacteria resulted in a reduction in the E. coli CFU number by ca.70%.Interestingly, for S. epidermidis at the bacteria concentration of 1 × 10 4 per mL, the inhibition efficiency of the modified Ti and SS samples after 4 h of incubation differed from that of E. coli.Here, the modified SS was the most efficient in bacterial growth inhibition, the presence of which resulted in a decrease in the S. epidermidis CFU number by ca.95%, while the modified Ti resulted in a decrease of ca.50%.In contrast to the results gained for E. coli, no effect on the CFU number of S. epidermidis was detected for the pristine Ti or SS.These results were further confirmed by SEM images of the bacteria on all types of samples, see Figure 5B,C.Moreover, the data from the SEM analysis documented that only a negligible number of bacteria of both strains adhered to the modified Ti and SS samples when compared with the heavily colonized pristine samples.These results suggest that the usage of alkoxy amine is a reliable way to create bilayer material (metal/metallic alloy and polymer) that can effectively reduce bacterial adhesion on the surface of the resulting material, which can be used for many medical devices and implants to decrease the possibility of inflammation and body rejection.When comparing it to similar approaches to form composites, whether for similar or different applications The differences between the observed adhesive behavior can be understood by the original surface characteristics of the substrate (namely, surface area, porosity, and roughness), which are different between the SS and Ti samples, as shown before, and by the original biocompatibility, in addition to the way each bacterial strain adheres to the surface (surface binding with different proteins in the case of E.coli and S. epidermidis) [37,38].However, all samples showed less adhesion of bacteria after the bonding, which means that the surface would become more bacteria-resistant, which might protect medical devices from causing infections or even the rejection of prosthetics.
These results suggest that the usage of alkoxy amine is a reliable way to create bilayer material (metal/metallic alloy and polymer) that can effectively reduce bacterial adhesion on the surface of the resulting material, which can be used for many medical devices and implants to decrease the possibility of inflammation and body rejection.When comparing it to similar approaches to form composites, whether for similar or different applications [39,40], the usage of the alkoxy amine seems to be an easier, cheaper, and more universal approach.Even though the material does not have antibacterial properties, from a chemical point of view, such properties can be acquired by including antibacterial elements (such as silver nanoparticles) [41], which can widen the application of this method considerably.
Conclusions
In this study, we demonstrated a universal, alternative approach to the conventional methods to "bond" Ti or stainless steel surfaces with PEG via the grafting of alkoxyamine.The successful chemical bonding was demonstrated by Raman measurements and changes in the element concentrations, as confirmed by EDX and XPS measurements.The successful modification resulted in significant changes in the surface properties of the materials, which were clearly shown by wettability, surface area, and zeta potential measurements.This chemical bonding technique makes it possible to fabricate composites with reliable stability in water solutions after 30 cycles and several useful functionalities.Therefore, this bonding technique deserves closer research into its applications not only in biomaterials but also in other fields.Modified Ti showed good bacterial anti-adhesive properties against both E. coli and S. epidermidis, while modified SS only showed properties against S. epidermidis.Therefore, both modified Ti and SS have high potential as bacterial anti-adhesive surfaces.
Polymers 2024, 16 , 508 4 of 15 Figure 1 .
Figure 1.Schematic representation of salt diazotization: formation of alkoxy amine groups on the surfaces (A) followed by surface grafting and modification of the surface with PEG (B).
Figure 1 .
Figure 1.Schematic representation of salt diazotization: formation of alkoxy amine groups on the surfaces (A) followed by surface grafting and modification of the surface with PEG (B).
Polymers 2024, 16 , 508 7 of 15 Figure 2 .
Figure 2. The Raman spectra of pristine, grafted, and modified Ti (A) and SS (B) samples, and Raman mapping of the significant peaks of alkoxyamine on the surface of the samples determined by the SERS technique for Ti (C) and SS (D).
Figure 2 .
Figure 2. The Raman spectra of pristine, grafted, and modified Ti (A) and SS (B) samples, and Raman mapping of the significant peaks of alkoxyamine on the surface of the samples determined by the SERS technique for Ti (C) and SS (D).
Figure 3 .
Figure 3.The surface morphology of the samples as observed by SEM for pristine Ti (A), pristine SS (B), Ti modified (C), and SS modified (D).
Figure 3 .
Figure 3.The surface morphology of the samples as observed by SEM for pristine Ti (A), pristine SS (B), Ti modified (C), and SS modified (D).
Figure 4 .
Figure 4. Static water contact angle (A); dynamic water contact angle (WCA) determined for in vidual samples by goniometry (B); and chemical stability measured by changes in WCA after mersion of the samples into water and measuring the WCA (C).
Figure 4 .
Figure 4. Static water contact angle (A); dynamic water contact angle (WCA) determined for individual samples by goniometry (B); and chemical stability measured by changes in WCA after immersion of the samples into water and measuring the WCA (C).
15 Figure 5 .
Figure 5.The number of colony-forming units (CFUs) of S. epidermidis and E. coli incubated for 4 h with the pristine and modified Ti and SS samples (A).SEM images of S. epidermidis (B) and E. coli (C) on the pristine and modified Ti (I and II, respectively) and the pristine and modified stainless steel (III and IV, respectively).
Figure 5 .
Figure 5.The number of colony-forming units (CFUs) of S. epidermidis and E. coli incubated for 4 h with the pristine and modified Ti and SS samples (A).SEM images of S. epidermidis (B) and E. coli (C) on the pristine and modified Ti (I and II, respectively) and the pristine and modified stainless steel (III and IV, respectively).
Table 1 .
Element surface concentration determined by XPS and EDX for both the titanium and stainless steel pristine and modified samples.
Table 2 .
Surface area, pore volume, and electrokinetic potential (zeta potential ζ) of the individual stainless steel and titanium samples in pristine and modified forms.
Table 2 .
Surface area, pore volume, and electrokinetic potential (zeta potential ζ) of the individual stainless steel and titanium samples in pristine and modified forms. | 8,435 | 2024-02-01T00:00:00.000 | [
"Materials Science",
"Medicine",
"Chemistry"
] |
A new estimation of protein-level false discovery rate
Background In mass spectrometry-based proteomics, protein identification is an essential task. Evaluating the statistical significance of the protein identification result is critical to the success of proteomics studies. Controlling the false discovery rate (FDR) is the most common method for assuring the overall quality of the set of identifications. Existing FDR estimation methods either rely on specific assumptions or rely on the two-stage calculation process of first estimating the error rates at the peptide-level, and then combining them somehow at the protein-level. We propose to estimate the FDR in a non-parametric way with less assumptions and to avoid the two-stage calculation process. Results We propose a new protein-level FDR estimation framework. The framework contains two major components: the Permutation+BH (Benjamini–Hochberg) FDR estimation method and the logistic regression-based null inference method. In Permutation+BH, the null distribution of a sample is generated by searching data against a large number of permuted random protein database and therefore does not rely on specific assumptions. Then, p-values of proteins are calculated from the null distribution and the BH procedure is applied to the p-values to achieve the relationship of the FDR and the number of protein identifications. The Permutation+BH method generates the null distribution by the permutation method, which is inefficient for online identification. The logistic regression model is proposed to infer the null distribution of a new sample based on existing null distributions obtained from the Permutation+BH method. Conclusions In our experiment based on three public available datasets, our Permutation+BH method achieves consistently better performance than MAYU, which is chosen as the benchmark FDR calculation method for this study. The null distribution inference result shows that the logistic regression model achieves a reasonable result both in the shape of the null distribution and the corresponding FDR estimation result.
Background
In shotgun proteomics, the identification of proteins is a two-stage process: peptide identification and protein inference [1]. In peptide identification, experimental MS/MS spectra are searched against a sequence database to obtain a set of peptide-spectrum matches (PSMs) [2][3][4]. In protein inference, individual PSMs are assembled to infer the identity of proteins present in the sample [5][6][7].
*Correspondence<EMAIL_ADDRESS>† Guanying Wu and Xiang Wan contributed equally to this work. 1 The Dental Center of China-Japan Friendship Hospital, Beijing, China Full list of author information is available at the end of the article Inferred proteins are the most biologically relevant outcome of a shotgun experiment. Therefore, the ability of accurately inferring proteins and directly assessing such inference results is critical to the success of proteomics studies. To date, many effective protein inference algorithms have been developed such as ProteinProphet, ComByne and MSBayesPro. However, the problem of accurate assessment of statistical significance of protein identifications remains an open question [8,9]. Past research efforts towards this direction can be classified into p-value based approaches and false discovery rate (FDR) approaches: • p-value based approaches provide a single protein-level p-value for each reported protein.
• FDR approaches apply a single threshold to all proteins identified from the data rather than generate individual significance values for each protein.
Both p-value based approaches and FDR approaches aim at controlling the quality of identified proteins, though they consider this problem from different perspectives. Unfortunately, available methods still deserve certain drawbacks, as summarized below: 1 Reliance on specific assumptions. Most methods depend on particular assumptions regarding the model or the distribution of false positive matches. For instance, the p-value based PROT_PROBE approach [10] assumes that protein identification by a collection of spectra follows a binomial model. Similarly, the representative of FDR approaches, MAYU [11] is based on the assumption that false positive PSMs are equally likely to map to either the target or decoy database and the number of false positive protein identifications is assumed to be hypergeometrically distributed. 2 Reliance on the two-stage calculation process. Generally, the protein-level confidence measure is obtained by combining peptide-level p-values (e.g., [8]). Such process may propagate errors at the peptide-level to the protein-level in a non-trivial manner [12].
Based on above observations, we propose a new framework for the protein-level FDR estimation that can avoid above-mentioned shortcomings. In this framework, we are permuting protein sequences and performing searching against these fake sequences on a dataset to get the corresponding null distribution at the protein-level before p-value and FDR calculation. Therefore, our calculation does not rely on the two-stage calculation process. In addition, we do not need to make any assumption on the distribution of protein identification scores since the permutation procedure is non-parametric. More importantly, once the null/permutation distribution is available, we can calculate p-values and the FDR without searching a decoy database. Experimental results on several real proteomics datasets show that our framework is effective in p-value and FDR calculation and outperforms MAYU consistently.
Although this framework is very appealing, the time required to perform the permutation procedure renders it infeasible to generate the null in an on-line manner before we have a fast permutation algorithm. To alleviate this problem, we suggest to do the permutation in an off-line manner and then store the null distributions for future use. When null distributions built on existing samples are not applicable in analyzing new-coming data with different features, we propose to use logistic regression to infer the null distribution from existing null distributions.
The rest of paper is organized as follows: "Methods" section illustrates the details of our methods. "Results and discussion" section presents the experiment results. "Discussion" section concludes the paper.
Overview of the methods
Proteins that are present in an experimental sample are true positives; others are false positives. Each protein is associated with a score measuring its confidence. The higher the score, more confident we are that the protein is in the sample. If we treat the protein score as a test statistic, the distribution formed by scores of false positives is the null distribution. Given N proteins, we can determine the p-value of each protein from the null distribution. For a certain FDR α, we can determine how many proteins are accepted based on their p-values according to the Benjamini-Hochberg (BH) method:
Algorithm 1
The Benjamini-Hochberg (BH) procedure [13] 1. Suppose p 1 , p 2 , ..., p N are ordered p-values associated with N proteins. 2. Fix the FDR α and let 4. Accept all proteins l for which p l ≤ p L .
Given a subset of proteins obtained by setting a protein score threshold, we can also determine the FDR according to the BH procedure.
In the method, the p-value calculation method and the BH procedure are well-established statistical routines. The major source of errors in estimating the FDR may come from the null distribution estimation. Generally, the more data we have, the more accurate the null distribution. Thus, we estimate the null distribution by using a permutation method, which can generate plenty of data for robust data analysis. However, the permutation method is inefficient. This method becomes computational expensive when handing large datasets. This motivates us to develop a method that can infer the null distribution of a new dataset from null distributions of known datasets. We can store the previous estimated null distributions and conduct the protein-level FDR estimation in an off-line mode. In this way, both accuracy and efficiency can be achieved. Details are provided in the following sections.
The permutation method
We employ the target-decoy technique to determine null distributions. In the permutation step, each sequence in the original protein database is randomly shuffled [14]. The shuffled proteins are appended into the original protein database to form a concatenated database. Then, proteins are identified from the concatenated targetdecoy database. Protein identifications mapping to decoy sequences are false positives, whose scores are used to form the null distribution. When the sample size is small, we may not have enough false positives to form a reliable null distribution. Thus, the shuffling step and the protein inference step are repeated multiple times (e.g. 20 repeats). In each iteration, decoy protein scores are stored.
Suppose we obtain M decoy proteins in the above step. Let Z = {z 1 , z 2 , ..., z l , ..., z M } be the set of decoy protein scores. We partition the range of z l values into K bins of equal length: Here, Z k contains protein scores belonging to the k-th bin. Define y k as the count in the k-th bin: and let x k be the center point of Z k . Note that When a protein belongs to Zk,k = 1, 2, ...K. Then, its p-value can be approximated as: Given N proteins, we can estimate their p-values. The determination of the relationship of the FDR and the number of proteins is straightforward by applying the BH procedure mentioned in the previous section.
In the permutation method, we need to shuffle and identify proteins multiple times. Thus, the notable limitation of the permutation method is its low efficiency. Null distributions of different samples can be stored in the protein database for future use in an off-line mode.
A general null distribution inference model
The protein identification result can be affected by various reasons such as the tandem MS peak count and the sample complexity. Null distributions built on existing samples may not be applicable in analyzing data with different tandem MS peak counts and a different sample complexity. Determining the null distribution of new data is time consuming by applying the permutation method. Thus, we design a way to infer the null distribution from existing null distributions in the case that high efficiency is desired.
A raw data can be described by many features. For instance, tandem MS peak counts and tandem MS spectral quality measured by the mean noise level. Suppose we have I existing samples and each sample can be described by J features. Denote features of the i-th sample as (r i,1 , r i,2 , ..., r i,J ) and let H i (x) be the null probability density function associated with the sample. The feature of a new sample is denoted as (r 0,1 , r 0,2 , ..., r 0,J ) and our objective is to infer its null density function H 0 (x).
For a protein score belonging to the k-th binx ∈ Z k , we collect the following information from existing samples: Then, the relationship of the probability Pr i,k (x ≤ x|x ∈ Z k ) and J features can be described by the following logistic regression model: After fitting the logistic regression model, we estimate the the probability Pr 0 (x ≤x|x ∈ Z k ) of the new sample as: For bins Z 1 , Z 2 ,... and Z K−1 , we collect information as shown in Table 1, conduct logistic regression by model (5) and obtain the fitting coefficients β k,j (k = 1, 2, ...K − 1; j = 0, 1, 2, ..., J) as shown in Table 2. It is unnecessary to perform logistic regression on the last bin Z K because Pr i (x ≤x| ∈ Z K ) = 1, i = 0, 1, 2, ..., I. We use a coefficient table to store the information: Then, the density function H 0 (x) can be approximated as: When k = 1, H 0 (x ∈ Z k ) becomes ill-posed because Z 0 is undefined. In this case, let Pr 0 (x ≤x|x ∈ Z 0 ) = 0. By using the coefficient table and equation (7), we obtain the null density function H 0 .
The feature protein database
We can use a feature table to organize our data. A feature database is shown in Fig. 1 When a new raw data is input, protein inference and feature extraction are performed. We can use existing protein inference algorithms such as ProteinProphet to identify proteins from the protein database in the feature database.
Then, we can compare the new sample with samples in the feature database based on their features. We can measure the similarity of two samples by calculating the correlation of their feature vectors. Similar samples are often encountered when we analyze replicate samples. If the similarity between the new sample and an existing sample i is high (e.g. the correlation of features is above 0.9), we use H i (x) as the null distribution to calculate the proteinlevel FDR. If we cannot find any similar sample in the feature database, we can plug the coefficients in the coefficient table into function (6) and use Eq. (7) to infer a new null distribution for the new sample.
The permutation method takes lots of time. When the number of bins in the null distribution and the number of features are large, the logistic regression fitting may also take a great amount of time. The off-line information (i.e. the feature table and the coefficient table) is used to achieve a new null distribution without the permutation step and the logistic regression fitting step. Thus, it makes the protein-level FDR estimation efficient.
Our current implementation of the framework
When applying the proposed protein-level FDR estimation framework, two key points are: features and similarity measurement. A sample can be described by features. When a novel sample is similar to an existing sample by comparing their features, the null distribution of The error propagation from the peptide-level to the protein-level is non-trivial. Features of raw data such as tandem MS peak counts are faraway from the final protein inference result. Thus, these kinds of features may not have a clear connection with protein scores. In our current implementation, we determine to directly select features from protein scores.
First, we partition the range of protein scores of sample i into 10 bins of equal length. The probabilities of protein scores falling in 10 bins are denoted as P i,1 , P i,2 , ..., P i, 10 . Then, we choose sample j as a reference sample. The similarity of protein identification results of sample i and sample j is measured by their Kullback-Leibler (KL) divergence: The smaller the value of D i,j , the more similar sample i and sample j. We choose the KL divergence from each sample to the reference sample as a feature, which is used to infer the null distribution and measure the sample similarity.
Overview of the experiments
The whole framework consists of two parts: The first part employs the permutation method and the BH procedure to estimate the FDR (Permutation+BH); the second part provides a logistic regression model to infer the null distribution of a new sample based on existing null distributions. We first conduct the experiment to verify Permutation+BH in FDR estimation. The performance of our method is compared to MAYU based on three datasets with groundtruth. Then, we conduct another experiment to illustrate the performance of our null distribution inference method. In the last part of our experiments, we discuss the reference dataset issue in our current implementation of our framework. The whole framework is implemented in Ruby (v1.9.2p290). Target-decoy concatenated databases are generated from UniProtKB/Swiss-Prot (Release 2011_01) by appending shuffled protein sequences into the original protein database. Peptides are identified by X!Tandem (v2010. 10.01.1) [4]. Then, ProteinProphet (Embedded in the Trans-Proteomic Pipeline v4.5 RAPTURE rev 0, Build 201109211427) is employed to perform peptide probability calculation and protein inference, respectively [5,15].
In our experiments, we use six public available datasets: ISB, ABRF, Yeast, Yeast_Train, Human and Human_Test. The ISB dataset was achieved from a 18 standard protein mixture [16]. The sample was analyzed on a Waters/Micromass Q-TOF using an electrospray source. The ABRF sPRG2006 dataset contains 49 standard proteins. The Yeast and the Yeast_Train dataset were obtained by analyzing cell lysate on both LCQ and ORBI mass spectrometers from wild-type yeast grown in rich medium [17,18]. The dataset contains a protein reference set which is used as the groundtruth. The Human dataset was obtained from human HEK293T cell lines and analyzed on the ORBI mass spectrometer. The Human_Test dataset was obtained by analyzing human serum samples with Thermo LTQ-FT. In our experiments, ".RAW" files are converted to ".mzXML" files by TPP. The addresses to access these datasets are shown in Table 3:
FDR estimation
In this experiment, the first three datasets are used: ISB, ABRF and Yeast. For the ISB dataset, the 18 standard proteins together with 15 contaminants are marked as the groundtruth [16]. For the ABRF dataset, the 49 standard proteins and 78 contaminants are used as the groundtruth. Readers can refer to the supplementary document for more information [19]. For the Yeast dataset, all proteins in the protein reference set are treated as true proteins.
The permutation method includes two steps to obtain a null distribution: a shuffling step and a protein inference step. In the shuffling step, each protein sequence is shuffled and appended into the original protein database. In the protein inference step, proteins are identified from the target-decoy concatenated database with TPP. The shuffling step and the protein inference step repeat for 20 times. The protein mapping to a decoy sequence is considered to be a false positive. The protein probabilities of all false positives from the 20 protein identification results are collected. Then, the histogram of the protein probabilities is built and used as the null probability density function. In general, the smaller the bin size, the more detail the null distribution contains and more data points are desired to build the null distribution. In our experiments, the length of each bin is empirically chosen to be 0.003. After the null distribution has been built, the p-value of each protein is calculated according to Eq. (4). Next, pvalues of all proteins are sorted in the ascending order. Then, the BH procedure is conducted on p-values to obtain the relationship of the number of proteins and the FDR.
We apply our method and MAYU to the three protein datasets to estimate the FDR. The true FDR is calculated as the ratio of the number of proteins belonging to the groundtruth set and the total number of protein identifications. The performances of different methods are validated by comparing the absolution difference between the estimation and the groundtruth. The results based on three datasets are shown in Fig. 2.
According to our experimental results, our method and MAYU are comparable in performance on the ISB dataset. For the ABRF dataset, our method is better than MAYU on average. Our method is dominantly better than MAYU on the Yeast dataset.
Null distribution inference
In this dataset, the first five datasets listed in Table 3 are used to fit the logistic regression model (5) and the Human_Test dataset is used to validate the null distribution inference result.
In this experiment, we choose the ISB dataset as a reference dataset and calculate the KL divergence from other samples to the ISB dataset by using Eq. (8). The feature table for six datasets is shown in Table 4.
The null distributions of six samples are obtained by the permutation method. The first five null distributions are used to infer the null distribution of Human_Test. The last null distribution will be used as a reference. Fig. 2 a, b and c show the absolute differences between FDRs estimated and true FDRs. The smaller the difference, the better the performance. In (a), our method is comparable with MAYU. In (b), our method is better than MAYU on average. In (c), our method is dominantly better than MAYU Let the first five samples be sample 1,2,3,4 and 5, respectively. Human_Test is denoted as sample 0. The KL divergence from sample i to the reference sample is denoted as r i,1 . Since the bin length 0.003, the number of bins is K = 334. The probability Pr i (x ≤x|x ∈ Z k ) is calculated from the null distribution of sample i for bin k. The logistic regression coefficients for bin k are obtained through the following model: Here, β k,0 is the intercept coefficient; β k,1 is the sample KL divergence coefficient, respectively; L is a loss function measuring the error in estimation. In our experiment, we choose L = · 2 . In our Ruby program, we implement a R (v2.13.1) interface from which users can call any robust loss function such as the Huber loss. We partially show the coefficient table in Table 5. The feature table and the coefficient table are stored in the feature database. When analyzing the new sample (i.e. Human_Test), we just plug coefficients in the coefficient table in Eq. (6) and use Eq. (7) to get the null probability density function of Human_Test. The result is shown in Fig. 3. Figure 3a shows the probability density functions of the inferred null and the null obtained by the permutation method. The peak height of the inferred null is overestimated compared with that of the permutation null. In Fig. 3b, Permutation+BH and InferredNull+BH estimate the FDR by applying the BH procedure to the null distribution generated by the permutation method and the inferred null distribution, respectively. According to the result shown in Fig. 3b, the performance of Inferred-Null+BH is closer to Permutation+BH than that of MAYU. The correlation of the inferred null distribution and the permutation generated null distribution is 0.9052.
The reference dataset
In our current implementation of our framework, we need to reference dataset. The reference dataset is chosen to calculate the KL divergence of each sample to the reference dataset. Then, the KL divergence is used as a feature in both similarity measurement and null distribution inference. In the previous experiment, we take the ISB dataset as the reference dataset. The KL divergence is a non-symmetric measure of the difference between two probabilities. Thus, a different reference dataset may lead to a different null distribution inference result. In the following experiment, we take the ISB dataset, the ABRF dataset and the Yeast dataset as the reference dataset, respectively. The result is shown in Fig. 4. The correlations of the inferred null distribution and the permutation generated null distribution when using the ISB dataset, the ABRF dataset and the Yeast dataset as a reference dataset are 0.9052, 0.6779 and 0.3317, respectively. According to the experimental result, the best performance in null distribution estimation is achieved when the ISB dataset, which contains 18 proteins, is taken as the reference dataset. The performance is worst when the Yeast dataset containing hundreds of proteins is used as the reference dataset.
Readers may be interested in the results of inferring the null distributions of other samples (other than Human_Test) by using the ISB dataset as the reference dataset. In the following experiment, we conduct two extra experiments to inferring the null distributions of the ABRF dataset and the Yeast dataset. In each of the two experiments, we treat either the ABRF dataset or the Yeast dataset as test data and using remaining datasets as training data. The result is shown in Fig. 5.
The difference between the inferred null distribution and the empirical null distribution obtained by the permutation method may be caused by the following reasons: • The data used in fitting the logistic regression model may be neither typical nor enough. Data representative to different conditions are desired to obtain a robust regression model. When information of some typical conditions are missing, it is may be hard to make it up by using mathematical models. • In our experiment, we only consider one feature in our logistic model. The single feature may not explain all kinds of variation in the protein inference process. A more accurate model can be achieved by using more features and plenty of data in building the feature database. • Even if we obtain an ideal logistical model with perfect coefficients, it is not guaranteed that the new data is not an outlier. It is often the case that the new data locates at a point that has a certain distance to the ideal model.
The biggest advantage of the null inference method is its efficiency. Once the coefficient table is obtained beforehand, the inference of the null distribution is just the calculation of deterministic functions (6) and (7). The whole process of the FDR estimation just takes a few seconds. This should benefit the large-scale data analysis.
Discussion
In the Permutation+BH method, we use the permutation method to generate the null distribution and apply the BH procedure to estimate the FDR. The method does not relies on specific assumptions and works directly at the protein-level. Thus, the problems related to improper assumption and error propagation are avoided. The flexibility of our method also implies that it can be used with any search method or protein inference method of the user's choice. According to our experimental results based on three datasets, our method performs better than MAYU. We believe that this is partly due to a more accurate estimation of the null distribution through the increased sampling by our permutation method, than in a typical 1:1 target-decoy approach as used in MAYU.
In the Permutation+BH method, the efficiency is low because we need to shuffle protein sequences and conduct protein inference multiple times. We propose an off-line strategy to handle this issue. In the off-line strategy, a feature protein database is built beforehand with null distributions obtained from existing samples, a feature table and a coefficient table. When a new sample cannot find a match in the feature table, a new null distribution is inferred by directly plugging the coefficients in the coefficient table into the logistic model. The logistic regression model provides an efficient way to infer the null distribution. Our model is currently trained only on a few samples and including only 1 feature, limiting its accuracy. We will seek to improve this model by adding many more features and training the model on more datasets, as part of our future work.
Conclusions
In this paper, we propose a protein-level FDR estimation framework. The framework includes two major components: the Permutation+BH FDR estimation method and the logistic regression-based null distribution inference method. The Permutation+BH method first applies the permutation to generate the null distribution and then uses the BH procedure to estimate the FDR. However, this method is inefficient for online identification. Therefore, we propose the logistic regression-based null distribution inference method to handle this issue. In our experiment based on three public available datasets, our Per-mutation+BH method achieves consistently better performance than MAYU, which is chosen as the benchmark FDR calculation method for this study. The null distribution inference result shows that the logistic regression model achieves a reasonable result both in the shape of the null distribution and the corresponding FDR estimation result. | 6,216 | 2018-08-01T00:00:00.000 | [
"Biology"
] |
A perception centred self-driving system without HD Maps
Building a fully autonomous self-driving system has been discussed for more than 20 years yet remains unsolved. Previous systems have limited ability to scale. Their localization subsystem needs labor-intensive map recording for running in a new area, and the accuracy decreases after the changes occur in the environment. In this paper, a new localization method is proposed to solve the scalability problems, with a new method for detecting and making sense of diverse traffic lines. Like the way human drives, a self-driving system should not rely on an exact position to travel in most scenarios. As a result, without HD Maps, GPS or IMU, the proposed localization subsystem relies only on detecting driving-related features around (like lane lines, stop lines, and merging lane lines). For spotting and reasoning all these features, a new line detector is proposed and tested against multiple datasets.
I. INTRODUCTION
Ziegler's system [1] can drive full-autonomously over 100 kilometers without any interruptions in 2014. Despite these early achievements, the industry leaders are still struggling to pass the necessary tests according to [2]. It is critical to inspect why the current self-driving system is hard to implement and widely used. Current systems rely on HD Maps to produce centimeter-level accuracy of position. Readers are referred to [3] for more about typical system architecture. The big question is whether accurate positions necessary?
Human drivers make driving decisions based on what they see. They make sense of the environment around and decide when to turn or keep the current driving direction. They cannot mark the exact position of themselves on a map, but they know how to travel through a complicated intersection based on the knowledge of which way they should take. Likewise, a selfdriving system without accurate locations should be a viable solution?
In this paper, a new perception centered self-driving system is proposed and discussed in two driving scenarios: the cruising scenario and the turning scenario. The cruising scenario is when the vehicle cruises on parallel lanes. The turning scenario is when the vehicle drives through free spaces (defined as the drivable area outside of lanes, like intersections or parking area).
The proposed system comes with several advantages in these two scenarios. Firstly, it does not rely on HD Maps. So it is easy to scale without recording new HD Maps.
Secondly, the proposed feature detection method is not based on any specialized end-to-end deep learning solutions. Hence it is easy to debug and visualize. Also, it does not need additional time-consuming training process for scaling. Lastly, it performs more robustly with a severely changed environment (like seasons, weather or lighting condition).
Just like the human drivers, the system only involves with related visual features (defined as traffic features, including traffic lines, traffic lights and traffic signs). The workflow of the detection and localization subsystem is shown in Fig. 1. In the cruising scenario, only the first step is needed, including 1.1 and 1.2. In the turning scenario, all four steps must be done. Note that the vehicle position from the localization subsystem is based on the rebuilt scene rather than a global map. The localization subsystem also projects the rebuilt scene onto a digital map (like Google Map) to provide navigation instructions while crossing free spaces. The navigation instruction leads the car to travel from one exit to the target entrance of the free space. The path planning system and control system also works on the rebuilt scene. Hence they are map unrelated.
The proposed system relies on traffic lines (including curbs) for tracking the vehicle's position. Hence, the lines detector is the priority. A general lines detector for understanding complicated traffic lines on the road is vital. The experiment covers several types of lines, including lane lines, stop lines, curbs, merging and splitting lines and intersections in a roundabout. For the popular lane lines detection problem, the proposed new traffic lines detector performs as good as other deep neural network supported approaches leveraging the prior knowledge of lines position and angles with easy erosion and clustering. This robust and straightforward method is then generalized and successfully detected other kinds of lines as well. After that, the process of localizing the position in the rebuilt scene will be discussed with examples and limitations. In that example, the system requires neither GPS signals nor IMU signals nor 3D HD Maps to locate the vehicle.
II. RELATED WORK
What is a perception centered self-driving system? Most self-driving systems are relying on a map-based localization subsystem. They are categorized as localization centered systems because all other subsystems are working under the map space from the localization subsystem. The perception centered system uses a local scene, instead of a global map, as the working space for all other subsystems. Limited research have been done on this direction. One of the exceptions is [4] by Bojarski from Nvidia. In this work, they tried to build an end-to-end system from camera images to control signals with the help of augmented learning. It is also map-unrelated. However, this system only works for minimal lane-keeping tasks in the cruising scenario. It is not compatible to work with other subsystems, and the scalability is not tested for more sophisticated roads or sensor settings.
A. Localization
For most localization centred systems, all decision making and path planning are based on a centimetre level localization accuracy from their localization subsystem. Using GPS, with the aid of IMU, is a popular solution and provides accuracy better than 20 centimetres with SLAM over an HD Map [5]. The problem of GPS is that the signals are not always available, and the result tends to drift accidentally. For quite a long time, SLAM is considered as the key to solving the localization problem for self-driving cars. The SLAM algorithm uses visual features stored in the HD Map to match features extracted from the live camera on the self-driving cars. Visual features are usually organized as bags of features (BoF) in the descriptor space. Without HD Maps or IMU, researchers can hardly reach the centimetres level accuracy like [6] and [7].
However, two problems of the SLAM based localization approach are tricky to solve. Firstly, the performance decreases once the environment changes. Light angle changes might cause different shadow shapes and season changes cause massive appearance changes on the trees and grass. These changes yield new visual features which cannot be matched with the recorded ones on the HD Map. This problem requires routine labour-intensive map recording once after the changes occur. Secondly, the localization result tends to drift after a long-range driving, and the error will accumulate with growing driven distance, as discussed in [5]. The intrinsic reason of these problems is that the original SLAM algorithm is designed for indoor localization problems where dramatic environment changes or long-distance moving is not considered. Hence these problems are hard to eliminate.
Recent researchers, like Ma [8], started to use as less visual features as possible for localization. Besides saving the storage for the BoF of these features, using fewer features decrease the risk of being affected by the environment changes [9].
This trend brings the idea of using minimal features for localization. The LaneLoc system proposed by Schreiber [10] tried to use the exact appearance of lane markings for matching from pre-recorded maps. This approach could be seen as counting the number of dashed fragments the vehicle travelled to localize the car itself. This approach still has several limitations. Firstly, it will not work on a solid line situation and ends up with only relying on IMU without any visual aids. Secondly, the exact appearance will eventually change one day in the future. Think about the time when those dashed lines were repainted or worn out, which are both prevalent cases. Thirdly, the performance is very fragile. Slight turbulence, like occlusions or heavy shadows, will make the system omit one or more fragments and yield a steady error as a result. Lastly, the labelling process is both complicated and hard to finish accurately, as discussed by Schreiber in their paper. The proposed system solved these limitations by abstracting line features further to types and directions by the proposed lines detector.
B. Traffic Line Detection
The traffic line detection, or the lane detection which is a narrower problem, was the essence of many early driving assistant systems [11] like Lane Departure Warning System (LDWS) and Lane Keeping Assist System (LKAS). Many researchers, like Kim [12], used Convolutional Neural Network (CNN) to reduce noise and get the segmentation of the markings of those lines. Wang [13] used shape extracted from OpenStreetMap (OSM) as prior knowledge to help detect the lanes. Some problems remain for the CNN supported approaches.
Firstly, they still can not solve the long-tail challenging situations because CNNs heavily relies on the distribution of the training dataset. As a result, CNN generally works terribly in rare situations. Secondly, the segmentation result of the CNN approaches often cause blurry edges when it is not confident about the prediction. These blurry edges come with difficulty for the following algorithms when they try to form a line from these ambiguous pixels. Lastly, CNNs are significantly dataset related. They tend to work well only on the dataset they have been trained on [14]. This limitation is because that different datasets and sensor settings tend to create distinctive patterns of noise in the images. For example, in the KITTI dataset [15], the same line marks show different appearances in different locations under the BEV space. Lines far from the camera shows clear artifacts caused by the BEV transformation. The self-driving related datasets are often covering just one type of the available camera settings. A vast and comprehensive dataset like MS-COCO [16] for the object detection task does not exist for now.
As a result, CNN was not used for lines detection in this paper. The proposed lines detector leverages the lines information from a topology map, similar to what Wang did in [13] from the OSM, as prior knowledge to help. The proposed lines detector separates different line types to boost the performance even more by using different lines detector for each type of lines (solid or dashed lines, straight or curved lines). It also used a sliding window to detect and connect traffic lines, similar to what Tsai did in [17]. The sliding window approach is proved to be both robust and easy to visualize for debugging.
III. SYSTEM DESIGN
The overall workflow is shown in Fig. 1. In the cruising scenario, the detection subsystem will finish the part 1.1 and 1.2 to give the current lane number of the vehicle, and that is enough for generating a driving path and control signal without involving the localization system at all. However, the detection system needs to continuously detect the traffic features for the next traffic part (could be another lane ahead or a free space connected with an exit). The order of the series of traffic features are based on the topology map.
The topological map, being used as the descriptor space for matching with the digital map and the rebuilt scene, is the center and the relationship is shown in Fig. 2. The topology map should be drawn before the system can run on a new area. The topology map also provides lane information helping lines detection as prior knowledge and helps the vehicle to change to a preferred lane in advance. The topology map contains the following information: Each turning point on the digital map is used for finding a nearest entrance-exit pair which have the correlated directions. Define T = {(λ t , φ t ), α t , β t } as the set of all turning points on the digital map, where λ t and ϕ t is the latitude and longitude of turning point t, α t is the direction before the turning and β t is the direction after the turning.
are the set of all entry points and all exit points. The score function f is the multiplication of g and h, as equation 1, where g is the Euclidean distance between two points and h is the difference of two angles, defined as } is the set of all legal pairs of entrance and exits. All legal pairs should connect with a same free space and follow the traffic law. For example, the exit on the end of a right turning lane cannot pair with the entrance ahead with the same direction. The optimal pair for a minimal f score is the matched result with the condition of (d * in , d * out ) ∈ P . This method assumes the turning point on the digital map is the center point of the target exit and the target entrance.
The data of P and D are manually initialized as part of the topology map. These data usually do not need to be changed unless the traffic features are changed. For example, an intersection was updated with an additional right changing lane or new construction on the road updated the lane changing rules temporarily. The maintenance of the topology map is easy and fast since the only parts need to be changed in the sets of P and D are the data of the lanes. For the turning scenario, the detection subsystem only needs to detect one pair of non-parallel lines to form an anchor to rebuild the scene. For example, under the intersection scenario shown in Fig. 4, the middle lane line and the stop line are enough for a strong anchor to rebuild the scene based on the given relative position from the topology map. The target entrance on the right side can be predicted and used for path planning. Once the vehicle has driven into the free space passing the stop line which will no longer be detected, the stop line of the target lane will be detected and provide a strong anchor to follow up. The starting point of the target lane will form a weak anchor as additional clues for localization.
The detection of anchors might be effected by occlusions caused by other objects on the road. In other situations, there is a chance when the vehicle is crossing a large intersection, the vehicle will have no available anchor in sight in some area. The target lane direction and the current drivable area, as a backup, will aid the vehicle to finish the turning. The free space situation ends with positive detection of the next detectable lane set. If there are multiple lines parallel with each other nearby, the system assumes the detected one is the nearest one based on the current lane level position.
The system needs to be initialized at the beginning of each run based on GPS signals and the current driving direction from the gyroscope to tell the system which lane the vehicle is on. The GPS signal does not need to be centimetre-level accurate, and the detection subsystem will update the lane number, relying on counting the line numbers between the vehicle and the detected curbs. This paper does not cover behaviour decision among crossing lanes because this can be considered as a separated and solved problem thanks to previous research like [1]. This behaviour decision includes behaviours, like yielding to vehicles coming out from other merging lanes. These rules are universal and consistent.
C. General Lines Detector
The proposed lines detector in the detection subsystem can detect diverse types of lines. The code for lane lines detection for the KITTI dataset can be found on this repository. These types of lines were tested: (1) lane lines, (2) curbs, (3) stop lines, (4) merging or splitting points of two lines (pair of lines), (5) special lane lines or curbs (which are not parallel to the current ego lane). The lines detection problem was dissected by tracing back to the most significant visual feature of the lines, which is their long and narrow appearance. A sliding window was used to follow possible lines. All noise without this narrow feature was eliminated by applying these methods: • Region Restriction: The detection subsystem leverage a given prior knowledge about the starting points to eliminate noise in unrelated regions. This knowledge comes from either previous lines detection results or predicted by the positive detection results of neighbour lines with given lane width from the topology map. For dashed lines, the sliding window moves at a step size of dash segment intervals given from the topology map to make sure optimal detecting position for each segment. The system tolerates minor errors for this interval distance. The more knowledge about the lines are available, the smaller window for detection can be used. A smaller region of interest gives better resilience for challenges, helps the segment normalize better and speeds up the lines detection process.
• Special Convolution Kernel: The system uses a special kernel, as shown in Fig. 5. This proposed kernel helps to produce a cleaner result in the Hough space for the next steps with less noise. Also, this kernel is more friendly for detecting curves, merging lines and splitting lines than the simple vertical kernel.
• Directional Erosion: The system uses a special directional erosion structuring element to erode noise which is not spanning through a specific direction (A B, A is the pixels in the window and B is a 5 by 1 narrow structuring element), as illustrated in Fig. 6. The direction of the target lines is given from the topology map. In a sliding window, the line segment can be considered as a straight line. Sharp turning lines or circles will also be eroded into small segments which will be filtered out. Though there are some other more complicated ways to leverage the information of direction for lines detection [18], the directional erosion is the simplest and it works.
• Types of Lines: The system leverages prior knowledge of the types of the lines to get a better performance. For curves in each detection window, the turning angles are restricted to the thresholds, which is usually very small given from the topology map. For straight lines, a much narrower window for detection can be used. For dashed lines, the marks which are too long or too short will be filtered out, as shown in Fig. 7. The topology map gives the length of segments of the dashed lines.
The proposed lines detector uses the Y channel from the YUV color channels since it was proved to perform better by Lin in [19]. The system works on the Bird-Eye-View (BEV) space since the prior knowledge of those lines can be leveraged without predicting the camera pose or estimating the vanishing point (VP) [20]. More about the homography transformation from the camera image to a BEV space with a given camera pose can be found in [21].
For the feature detection on the Hough space, a low-highlow kernel was widely used by [22], [23] and [24]. A new lowmiddle-high kernel was used and then mirrored to make the detection on the left and right side separately. So merging and splitting points and their directions (merging from / splitting to the left or the right) can be detected by comparing the lengths of these two lines detection results. For example, at the place a line is splitting to the right, the line detection from the right side will break coming with a shorter length of the line than the left side, as shown in Fig. 8. To separate splitting and merging, two additional windows will be created facing upwards and downwards. Positive result of lines in the upwards window means splitting and positive result in the downwards window means merging.
Lastly, the procedure for stop lines detection is as follows.
After the detection of a window, if the line is broken in the upper end, two side windows will be created. A horizontal line detection, using horizontal convolution kernel and erosion structure, will be applied to detect the stop lines. If the result is positive, then this lane line is marked as finished, and no window will be created above. For special lines which are not parallel to the current ego lines, an initial position for the sliding window to start will not be available to use. However, the system can still use the direction information from the topology map. Spotting the anchors from the target entrance while turning in free spaces is one of the situations which requires detecting special lines, as shown as in Fig. 4. The process is a little different, shown as follows: lines. The later part of this chapter shows how the localization method helps the vehicle travels through an intersection in the turning scenario.
For lane lines detection, the method was tested on KITTI [15] and Cityscapes [25]. For general traffic lines detection, The proposed method was tested on the Berkeley deep drive (BDD 100k) [26], KITTI and a self-recorded video. These results of general lines detection cannot be compared to other methods due to lacking metrics. At last, the BDD 100k dataset and images from a self-recorded video are used for testing the localization method while passing free spaces.
A. Lane Lines Detection
The proposed lines detector, ECPrior (Erosion and Cluster with prior knowledge), perform as good as other deep neural network supporting approaches [27] [28] [29] [30] based on the KITTI behaviour evaluation [31] metric. The result is shown in Table I. Some of the detection results are shown in the first row of Fig. 9. The proposed detector does not include object detection; hence it will be affected by other cars close to the lines. A typical object detector can be added before to get a better result, like Satzoda did in [32]. The object detection is usually a separate module, and the same feature should not be implemented again in the lines detection module. The proposed lines detector works equally fine on Cityscape showing its scalability, as shown in the second row of Fig. 9, despite they have very different object aspect ratio from the aspect ratio of images from KITTI. The limitations of ECPrior are: • Like all other methods, ECPrior relies on a stable and accurate BEV transformation. The transformation is hard to be accurate when the ground is not flat. Although the deep neural networks can learn to avoid this for a specific dataset, it is still hard to scale over different datasets. When it comes to non-flat surfaces, the width of a lane might shrink, as shown in the first fail case in Fig. 10. Dynamic adjustment of the window width can avoid windows from merging. ECPrior can tolerate minor distortion of the BEV transformation.
• Because ECPrior is for general cases, the input images should not have special manifests which would disturb the detector, as shown in the second fail case in Fig. 10. For KITTI, these manifests are mainly caused by the BEV transformation over low quality areas.
B. General Lines Detection
ECPrior can solve the problem caused by shadows or short breaks for general lines detection. ECPrior is also proved to be robust with different lighting conditions. For stop lines, images from the BDD 100k was used for testing. The result is shown in Fig. 11. The upper case in that image is under a lightly snowing daylight environment, and the lower case in that image is in a night lighting environment. In both cases, ECPrior successfully detects the stop lines ahead.
ECPrior also detects special lines well. A self-recorded video was used for testing. An example in Fig. 12 shows the ability to detect special lines under a turning scenario travelling into a roundabout. In this situation, ECPrior needs to detect the rear inner side of the roundabout. The left side curb of the current lane and the inner side curb of the roundabout can then form a strong anchor used to rebuild the scene of the free space for localization. ECPrior uses intense erosion and threshold so that only a small portion of target lines will be detected at the pixel level. Hence the ECPrior detector is not a pixel-level detector. ECPrior, as an intact line detection module, provides lines detection result using regression for dash line segments and straight lines and using Spline for the others. ECPrior inevitably relies on an accurate BEV transformation to leverage the prior knowledge of the lines. Distortion due to camera behind the windshield or problematic camera settings also cause a narrower efficient area for general lines detection, at that situation only lines lie in the middle of the front can be detected. As an example, the detector failed to detect the left side of the inner curb due to distortion in Fig. 12.
C. Localization
Based on these results from previous examples, strong and weak anchors can be established to locate the vehicle in the turning scenario. The proposed localization approach relies on neither GPS nor IMU for vehicles to travel through urban areas. The system provides a stable and accurate position based on the rebuilt scene for path planning and control subsystems in the turning scenario. For the cruising scenario, the detection system gives a lane level localization result (which lane the vehicle is on) which is enough for the following subsystems.
There are several limitations for using the naive approach of my proposed system for localization. Firstly, the proposed localization method relies on visual clues of specific traffic features. Heavy occlusion blocking most of the target traffic lines will affect the location result in some degree. In one situation, the vehicle was approaching the intersection with heavy traffic ahead, blocking most of the coming stop lines. The localization system did not spot anchors until when the vehicle was very close to the stop lines, producing a short reaction time to stop for the following subsystems. In another situation, the vehicle was about to turn right into a small allay based on the navigation. Several parking vehicles blocked the view of the right side curb. Hence the detection subsystem did not detect the right turning feature for the allay and make the vehicle miss the target turning.
In the first situation, the behaviours of other vehicles can be exploited as an input for the localization subsystem, like the way Gao leveraged the position of other vehicles in [33]. For example, when the system detects a line of stopping vehicles, it can assume the position of the first stopping car is indicating the position of the stop line to form a prediction to extend the reaction time for the following subsystems. In the second situation, a more comprehensive drivable area analysis will show a right side road extension indicating the allay. Additionally, the localization subsystem is compatible with traffic lights, traffic signs and GPS as pieces of additional information to help.
V. CONCLUSIONS
This paper proposes a new perception centered self-driving system and focuses on testing the proposed general lines detector, ECPrior, and the localization method on several urban cases. The proposed system design is a skeleton and a starting point with all potentials to work with additional modules to get better performance. For example, users can try to apply the method by Hillel in [34] to get rid of the lens flare to make the detection of ECPrior more robust when driving towards the sunshine. The potential is much more promising than other deep neural networks based detection methods. And diverse types of scenes rebuilding can be discussed in future works. Places like indoor parking area without GPS signals will heavily rely on the rebuilt scene to localize the vehicle. Hence they should be prioritized.
In the end, I appeal to the community to reconsider the necessity of using SIFT like visual features for localization, as well as the need for relying on deep neural networks for traffic lines detection in the context of self-driving. | 6,512.8 | 2020-09-02T00:00:00.000 | [
"Computer Science"
] |
The vesicular trafficking system component MIN7 is required for minimizing Fusarium graminearum infection
Disruption of the ARF-GEF protein encoding gene AtMin7 in Arabidopsis and silencing of the orthologous gene in wheat result in hypersusceptibility to the fungal pathogen Fusarium graminearum.
Introduction
In nature, plants are frequently exposed to various environmental stresses including pathogens, and yet more often than not plants appear healthy or show only weak or mild disease symptoms. To maintain this healthy status, plants have evolved an elaborate and tightly regulated innate immune system that allows them to restrict pathogen invasion or slow down/minimize disease progression (Jones and Dangl, 2006). These defensive processes not only include secretion of various peptides and secondary metabolites in response to pathogen attack (Dixon, 2001;van Loon et al., 2006;Yun et al., 2013), but also the tight regulation of this secretion (Yun et al., 2013).
In addition to the cell wall, each plant cell is enclosed by the plasma membrane, and the cytoplasmic contents include a variety of membrane-enclosed organelles. Transport of various cargo molecules across different membranes and the sorting of these into the correct cellular compartments is a process central to the functioning of multiple plant cell types (Bassham et al., 2008). The transport of components in small, membranebound vesicles between the intra-and extracellular space is referred to as vesicular trafficking (Yun and Kwon, 2017). Regulation of multiple cellular responses by the membrane trafficking network during plant-microbe interactions is required to facilitate a coordinated defense response at sites of pathogen attack (Ben Khaled et al., 2015;Gu et al., 2017;Yun and Kwon, 2017;Ekanayake et al., 2019). The vesicular trafficking system comprises two main pathways, secretory and endocytic (Fig. 1A), with both implicated in effective immunity against pathogens. A wide range of defense-related proteins, antimicrobial metabolites, and compounds such as callose that strengthen the plant cell wall can potentially be secreted at the sites of pathogen invasion (Gu et al., 2017). Concomitantly cell-surface immune receptors are subjected to endocytosis, which is necessary for initiation of signal transduction and regulation of receptor activity (e.g. through recycling or degradation in the vacuole) (Ranf, 2017). Secretory pathways transport newly synthesized proteins and other macromolecules (collectively referred to as 'cargo') from the endoplasmic reticulum via the Golgi apparatus to the plasma membrane or the extracellular space (Bassham et al.,Fig. 1. Schematic diagram of vesicular trafficking pathways in Arabidopsis. (A) Major cellular vesicular trafficking pathways: secretory (red arrows), endocytic (green arrows) and retrieval (blue arrows). Labels in orange indicate the location of specific regulators of the vesicular trafficking system. (B) Vesicle formation and budding. Bud formation requires small GTPases of ADP-ribosylation factor (ARF) or secretion-associated Ras-related protein (SAR1) type as well as adaptor proteins that recognize and recruit specific cargo receptors. Phosphorylation and activation of ARF/SAR1 are regulated by guanine nucleotide exchange factor (GEF) proteins that stimulate the release of GDP to allow binding of GTP. The latter triggers a conformational change in ARF/SAR1 that allows their stable association with the membrane surface and recruitment of specific coat proteins (COP), initiating the budding process. Once the rounded vesicle shape is formed, the large dynamin-related multidomain GTPases catalyse membrane scission, generating a transport vesicle. The coat components are rapidly lost shortly after the vesicle buds off. (C) Fusion of vesicles with the correct target membranes. Fusion of vesicles to the correct target membranes is regulated by the small Rab GTPase proteins. Different Rab proteins are associated with one or more membrane-enclosed organelles of the secretory pathway. Once in the GTP bound state, the Rab GTPase proteins bind to specific tethering factors in the target membrane to establish the first connection between the membranes that are going to fuse. Next, the N-ethylmaleimide-sensitive factor adaptor protein receptor (SNARE)-domain containing proteins on both the vesicle and the targeting membrane dock to mediate the fusion of the two membranes. SNAREs are transmembrane proteins that exist in complementary sets. Those located in the vesicle are called v-SNAREs or R-SNAREs, and those located in the target membrane are known as t-SNAREs or Q-SNAREs. A trans-SNARE complex formed following binding of v-SNARE/R-SNARE to t-SNARE/Q-SNARE located on separate membranes catalyses the membrane fusion (Collins et al., 2003;Yun and Kwon, 2017). Figure based on Alberts et al. (1989). 1A) (Kwon et al., 2008a, b;Dodds and Rathjen, 2010;Bozkurt et al., 2011;Nomura et al., 2011;Ellinger et al., 2013). The increasing number of mutations in plant vesicular trafficking genes that show altered resistance to microbial pathogens illustrates the importance of vesicular trafficking to plant immunity (Rybak and Silke, 2019). Whereas the general understanding of these trafficking pathways has advanced, knowledge of the molecular mechanisms employed by plant cells to coordinate the transport of specific molecules through different cell compartments is still limited (Ekanayake et al., 2019). The components of vesicular trafficking do not function in isolation but form complexes. Within these complexes, a defined set of proteins are responsible for selecting and transporting specific cargo molecules in a way that is highly coordinated both temporally and spatially (Fig. 1B, C) (Rutter and Innes, 2018).
Plant pathogens are known to secrete small effector proteins some of which could specifically target components of vesicular trafficking important for plant immunity. One of these targets is the regulator protein adenosine diphosphate ribosylation factor-guanine nucleotide exchange factor (ARF-GEF) encoded by AtMin7/Ben1/Big5 in Arabidopsis. The bacterial effector HopM1, which is required for proliferation of Pseudomonas syringae pv. tomato in the apoplast of the leaf interior, has been shown to degrade MIN7 in Arabidopsis (Nomura et al., 2006). ARF-GEF proteins are involved in controlling vesicle formation by regulating the ARF-family of small GTPases (Singh and Jürgens, 2018). Another example is the Phytophthora infestans effector AvR3a, which perturbs pattern-triggered immunity responses partly by targeting Dynamin-Related Protein 2B (DRP2B) in Arabidopsis (Chaparro-Garcia et al., 2015). Dynamins are important regulators of clathrin-mediated endocytosis and are involved in the scission and release of clathrin-coated vesicles from the plasma membrane (Gu et al., 2017).
Much of the evidence regarding the role of vesicular trafficking in plant immunity comes from studies involving the model plants Arabidopsis and Nicotiana benthamiana and to a lesser extent crop species such as barley (Hordeum vulgare), and a small number of their respective adapted biotrophic or hemi-biotrophic bacterial (P. syringae), oomycete (P. infestans) or ascomycete powdery mildew pathogens (Golovinomyces cichoracearum, Blumeria graminis, and Erysiphe pisi) (Nomura et al., 2006;An et al., 2006;Wang et al., 2009;Schmidt et al., 2014;Chaparro-Garcia et al., 2015). However, little is still known about the role of plant vesicular trafficking in the interactions involving other pathogens, other crop species, and those that primarily infect non-leaf tissue.
Fusarium head blight (FHB) disease, caused by the ascomycete fungus Fusarium graminearum and related Fusarium species, causes substantial yield losses and reduced grain quality and safety in a number of major cereal crops, such as wheat, barley, maize, rye, triticale, and oat, worldwide (McMullen et al., 2012;Dean et al., 2012). Moreover, under laboratory conditions F. graminearum is able to infect floral tissue of intact Arabidopsis plants as well as detached leaves (Chen et al., 2006;Cuzick et al., 2008;Brewer and Hammond-Kosack, 2015;Wood et al., 2020). For this model plant species, a large mutant collection is readily available.
The aim of this study was to assess whether knock-out mutations of the individual components of the vesicular trafficking system in Arabidopsis previously implicated in plant immunity had any impact on the interaction with F. graminearum. Screening of the assembled collection of mutants using a detached-leaf bioassay identified two independent T-DNA insertion mutants in the AtMin7 gene, which displayed striking hypersusceptibility to F. graminearum strain PH-1 compared with the parental wild-type Arabidopsis ecotype Col-0. Utilizing a recently released high-quality fully annotated wheat genome reference sequence assembly (International Wheat Genome Sequencing Consortium, 2018) and well-established bioinformatics tools enabling identification of putative gene orthologs from different plant species (Adamski et al., 2020), we identified the three homoeologous TaMin7 genes in hexaploid wheat (Triticum aestivum). Knock-down of these genes using virus-induced gene silencing (VIGS) (Lee et al., 2012) significantly promoted FHB disease formation in this crop species.
Plant material and growth conditions
The Arabidopsis mutants (Table 1) and the corresponding wild-type parental ecotype Col-0 used in the study were obtained from the Nottingham Arabidopsis Stock Centre. The corresponding mutations were verified by PCR using the primers listed in Supplementary Table S1 and confirmed homozygous mutants selected for further study. Arabidopsis seeds were sown in Levington F2+S compost (Everris Ltd) and stratified in the dark for 4 d at 5°C before transferring to a controlled environment growth chamber operating at 20°C/17°C during day/night with a 12-h photoperiod (light intensity of approximately 80-100 µmol m −2 s −1 ).
The fully susceptible spring type bread wheat (Triticum aestivum) cv. Bobwhite was used in this study (Cuzick et al., 2008). The plants were grown in a controlled-environment growth chamber with day/night temperatures of 23°C/20°C at around 65% relative humidity and a 16-h photoperiod with light intensity of approximately 180 µmol m −2 s −1 .
Fungal growth conditions, plants inoculation, and disease assessment
The reference F. graminearum strain PH-1 was used in this study. Routine culturing of the fungus, conidiospore induction, and preparation of conidial suspensions followed essentially the same procedures as described in Brown et al. (2011). Conidiospore suspensions harvested in sterile distilled water were adjusted to a concentration of 5×10 5 or 1×10 5 conidia ml −1 for inoculation of Arabidopsis or wheat, respectively.
Detached Arabidopsis leaves were inoculated as described in Chen et al. (2006) with the following modification. Fully expanded rosette leaves were detached from the 6-week-old plants using razor blades and placed adaxial surface facing upwards on the surface of 1% water agar in 10×10 cm square sterile Petri dishes, with eight leaves per dish. Each leaf was then superficially wounded by gently puncturing over the midrib with a glass Pasteur pipette and a 5 µl droplet of F. graminearum conidiospore suspension supplemented with 20 µM deoxynivalenol (DON) was deposited onto the fresh wound. Mock inoculation was carried out using a 5 µl droplet of sterile distilled water supplemented with 20 µM DON. After inoculation, the plates were transferred to the controlled-environment growth chamber operating at 20°C/17°C during day/night and 16-h photoperiod but kept in the dark for the first 3 d following which plates were incubated under low light (40 µmol m −2 s −1 ) for a further 4 d before the disease assessment took place.
Color (RGB) photographs were taken at 6 d after inoculation using a Nikon (D90) camera and backlighting to ensure consistent illumination. Image analysis to quantify the diseased areas was conducted using the LemnaTec LemnaGrid software module (LemnaTec GmbH, Aachen, Germany). Leaf areas were segmented using a combination of a colorbased classification and thresholding after converting the images to grayscale. Filters were applied to remove misclassified pixels and to fill in gaps. Finally, a customized color-based classification was applied to score leaf-area pixels as belonging to diseased or healthy tissue.
Intact spikes of adult wheat cv. Bobwhite plants were point inoculated at the first signs of anther extrusion by depositing 5 μl of conidial suspension in the floral cavity between the palea and lemma of the outer two florets located in the upper one-third of the spike, as previously described (Brown et al., 2011). Control plants were inoculated with sterile water only. Inoculated plants were incubated in a humid chamber for 48 h of which the first 24 h were in darkness. The inoculated plants were then kept in a controlled-environment growth chamber at approximately 65% humidity, the progression of the disease was visually monitored every 3 d, and the number of bleached spikelets below the inoculated spikelet on each spike was recorded along with the total number of spikelets on each spike (Urban et al., 2003).
PCR-based confirmation of specific mutations in the T-DNA insertion mutant Arabidopsis plants obtained from the seed stock center
One leaf from each Arabidopsis plant was collected in a 2 ml microtube, frozen in liquid nitrogen, and then ground with a micro-pestle. DNA extraction was carried as described in Motteram et al. (2009). Briefly, ground tissue was added to 350 μl of TEN buffer (500 mM NaCl, 400 mM Tris-HCL, 50 mM EDTA, pH 8.0), 1% β-mercaptoethanol, 5 mM 1,10-phenanthroline, and 2% (w/v) polyvinylpyrrolidone (K30). The resulting suspension was then mixed thoroughly with 350 μl of 2% (w/v) SDS and incubated for 30 min at 65°C. Following the addition of 300 μl of ice-cold ammonium acetate (7.5 M), the sample was kept on ice for 20 min and then centrifuged at 15 000 g for 10 min. DNA was precipitated with isopropanol, washed with 70% (v/v) ethanol, and dissolved in sterile distilled water.
For genotyping an insertion line using three primers in two combinations pairs, we carried out two PCR reactions: the 'wild-type PCR' and the 'T-DNA PCR' (O'Malley et al., 2015). Primer sequences were available at the Salk Institute Genomic Analysis Laboratory (SIGnAL) database and are listed in Supplementary Table S1. The wild-type PCR reaction used gene-specific 'right primer' (RP) and 'left primer' (LP) that flank the T-DNA insertion site in the corresponding mutant and allowed amplification of DNA fragments from both wild-type plants and heterozygous mutants. In the T-DNA PCR reaction, a T-DNA left border (LB) primer and a gene-specific RP were used. This second PCR reaction selectively amplified the T-DNA-genomic DNA junction sequence and allowed amplification of DNA fragments from heterozygous and homozygous mutants. PCRs were performed using REDTaq ReadyMix PCR Reaction Mix (Sigma-Aldrich, Gillingham, UK) following the manufacturer's instruction. A 1 μl aliquot of gDNA was used in a 25 μl PCR reaction, with an annealing temperature of 60°C. Primers were added at a final concentration of 0.5 μM.
Identification of wheat Min7 genes
Domain analysis of predicted ARF-GEF proteins in the hexaploid wheat (T. aestivum) was carried out using the BioMart tool in Ensembl. Initially searches were carried out for proteins that contained the Sec7_N domain (guanine nucleotide exchange factor in Golgi transport N-terminal domain; PF12783). The wheat genome assembly IWGSC RefSeq 1.0 (International Wheat Genome Sequencing Consortium, 2018) was used in this analysis. Coding sequences of eight previously identified genes comprising a small family of ARF-GEF encoding genes in Arabidopsis (Vernoud et al., 2003) were also extracted using the BioMart tool in Ensembl. Multiple protein sequence alignment was carried out using ClustalW tool in Geneious v.10. For phylogenetic reconstruction, the TVM+I+G nucleotide substitution model was selected by Akaike information criterion in jModeltest v.2.1.10 (Posada, 2008;Darriba et al., 2012). The maximum likelihood phylogeny was reconstructed using PhyML (Guindon and Gascuel, 2003), with the substitution model selected in jModeltest; starting tree with optimized topology, length, and rate parameters; topology searching by the best of nearest neighbor interchange and subtree pruning and regrafting; and 500 bootstraps.
Vector construction for virus-induced gene silencing
Total RNA extracted from healthy wheat cv. Bobwhite leaf tissue was used as a template for an RT-PCR amplification of a 209-bp TaMin7 gene fragment using primers TaMin7-2A-seg1-R (5′-AACCACCACCACC GTAAAAGGGTCGCCTCGTCAAT-3′) and TaMin7-2A-seg1-F (5′-A AGGAAGTTTAATGTTGCAAGCAAAGGCCATC-3′). This fragment was cloned in an antisense orientation into the Barley stripe mosaic virus (BSMV) vector pCa-γbLIC using ligation-independent cloning (Yuan et al., 2011). The VIGS vector for silencing the control TaChlH gene was kindly provided by Prof. Dawei Li (China Agricultural University, Beijing, China). BSMV::mcs4D, containing a 275-nt non-coding DNA sequence), was used as a negative control (Saintenac et al., 2018). To prepare the virus inoculum for wheat inoculation, the BSMVα, BSMVβ, and recombinant BSMVγ derivatives containing mcs4D or fragments of the TaMin7 or TaChlH genes were transformed into the Agrobacterium tumefaciens strain GV3101 (pMP90). Agroinfiltration of Nicotiana benthamiana leaves was carried out as previously described (Lee et al., 2015). The agroinfiltrated N. benthamiana leaves were harvested 5-7 d post-agroinfiltration, homogenized in 10 mM Na-phosphate buffer (pH 6.8) containing 1% Celite 545 AW (Sigma-Aldrich), and the sap was mechanically inoculated onto wheat leaves just prior to appearance of a flag leaf. Fungal inoculation of wheat spikes at anthesis was then carried out as described above.
Quantification of gene expression and fungal biomass by quantitative real time PCR
For quantification of gene expression, total RNA was isolated from either Arabidopsis leaves or spike tissue of wheat plants using the TRIzol reagent (Thermo Fisher Scientific, Waltham, MA, USA) following the manufacturer's instructions. To remove any traces of gDNA contamination, RNA samples were treated with TURBO DNaseI (Thermo Fisher Scientific) using methods as described by the manufacturer. The first strand cDNA was synthesized from 1 µg of total RNA in a total volume of 20 µl using the SuperScript IV Reverse Transcriptase (Thermo Fisher Scientific) and oligo (dT) 18 primers according to the manufacturer's instructions.
Gene-specific primers were used for RT-quantitative real time PCR (qPCR) analysis of transcript levels (Supplementary Table S1). Relative transcript levels were calculated by comparative threshold cycle (∆∆C t ) and normalized to the Arabidopsis ACTIN2 gene or the wheat CDC48 gene (Lee et al., 2014;Masachis et al., 2016).
A no template control was included in each of the qPCR experiments. For quantification of fungal biomass, total genomic DNA was extracted from infected leaves at 6 d post-inoculation using DNAeasy Plant Mini Kit (Qiagen, Manchester, UK) and subjected to qPCR using the primers specific for the F. graminearum ACTIN gene (Supplementary Table S1). Relative amounts of fungal DNA were calculated by comparative ∆∆C t and normalized to the Arabidopsis ACTIN2 gene (Masachis et al., 2016).
Protein extraction and western blots
Total leaf protein preparations were made as previously described (Sainsbury et al., 2009). Samples were resolved on 8% SDS-PAGE gels (Mini-PROTEAN, Bio-Rad) and transferred on to a nitrocellulose membrane (Hybond ECL, GE Healthcare). Immunoblots were performed by standard procedures using the Arabidopsis MIN7 specific antibodies at a dilution of 1:3000 (Nomura et al., 2006). The blots were developed using ECL Plus Western Blotting Detection Kit and images were acquired using Odyssey Imaging System (LI-COR Biosciences Ltd, Cambridge, UK).
Experimental design and statistical analysis
For the following experiments, GenStat for Windows (19th Edition, 2017; VSN International) was used. For Arabidopsis leaf inoculation assays, disease was quantified by expressing the diseased leaf area relative to the total leaf area. The statistical design for Arabidopsis leaf inoculation assays consisted of randomized blocks. Twelve leaves, one from each genotype, were placed onto each of eight plates. Seventy-two plants were used in total for each experiment (six plants per genotype). Six plates were used for fungal inoculation, and two plates were inoculated with water supplemented with DON to be used as a control. Three independent experiments were performed. Disease was quantified by expressing the diseased leaf area relative to the total leaf area. Mean disease levels for each genotype were compared using a multi-stratum ANOVA. Independent mutant genotypes were compared with the wild-type plants using a Dunnett's test at the 5% (P < 0.05) level of significance using wild-type Arabidopsis Col-0 as the control test. GenStat (release 20.1, 2019; VSN International) was used for the statistical analyses.
AtMin7 expression and fungal biomass determined by qPCR were compared from three biological replicates using ANOVA. Significance of differences between calculated means was determined using least significant difference (LSD) at the 5% level of significance.
For the statistical analysis of F. graminearum disease data, ANOVA was performed on the mean of the infected spikelets below the inoculation point out of the total spikelets calculated from the control (no virus and BSMV::mcs4D treated) and TaMIN7 silenced plants of three independent experiments, and linear models were fitted using GenStat. Graphical representations were made using the ggplot2 (Wickham, 2016) package in R.
Assembling a collection of Arabidopsis mutants with defects in membrane trafficking
To investigate whether vesicular trafficking plays a role in a compatible interaction (i.e. disease formation) between the ascomycete fungus F. graminearum and its laboratory host Arabidopsis, we assembled a collection of 11 mutants containing T-DNA insertions in nine immunity-associated genes regulating different vesicular trafficking pathways ( Fig. 1A; Table 1). Homozygous mutants were obtained from the Nottingham Arabidopsis Stock Centre (NASC, UK), and each mutant was verified by PCR amplification using gene-specific and T-DNA-specific primers (Supplementary Table S1). Smaller rosettes were observed for three mutants (vamp721, atmin7-1, and atmin7-2) when compared with the corresponding wild-type Arabidopsis ecotype Col-0 plants grown under standard controlled-environment conditions. For the remaining mutants, no obvious developmental or growth defects were observed. Representative images of each mutant compared with Col-0 at two different growth stages are given in Supplementary Fig. S1.
MIN7, an ARF-GEF protein, is required to minimize F. graminearum infections in Arabidopsis
To gain insight into whether mutations in any of the selected vesicular trafficking genes increase or decrease susceptibility to the virulent F. graminearum strain PH-1, young 6-week-old Arabidopsis plants were point inoculated with F. graminearum conidial suspension supplemented with the mycotoxin DON in a detached leaf bioassay (Chen et al., 2006). At 6 d postinoculation (dpi), the inoculated leaves were photographed, and disease levels were quantified by measuring the proportion of lesioned/necrotic area compared with the total leaf area by analysing the images using the LemnaGrid software module (LemnaTec GmbH, Aachen, Germany).
Fusarium graminearum-inoculated leaves of the two independent T-DNA insertion mutants in the AtMin7 gene (At3g43300) developed extensive necrotic lesions covering up to 100% of the total leaf area and showed almost complete loss of green photosynthetic tissue, while most of the remaining mutants displayed much milder disease symptoms with smaller lesions ( Fig. 2A, B). Quantification of F. graminearum biomass by qPCR showed a markedly higher fungal burden in atmin7-1 and atmin7-2 mutants compared with wild-type Col-0 or any of the other analysed mutants at 6 dpi (Fig. 2C). These results strongly suggest that plants with knock-out mutations in the AtMin7 gene are significantly more susceptible to F. graminearum.
AtMin7 is a large gene of 5857 bp containing 33 exons, and is located on chromosome 3. The two loss of function mutants studied here, atmin7-1 and atmin7-2, carry T-DNA insertions in exon 1 and exon 18, respectively (Nomura et al., 2006). AtMin7 is a member of a small family comprising eight genes encoding ARF-GEF proteins ( Supplementary Fig. S2), which play important roles in the budding of transport vesicles from the membranes (Fig. 1A) (Steinmann et al., 1999;Mossessova et al., 2003). This vesicular trafficking component has been shown to contribute to resistance to the bacterial pathogen P. syringae pv.
Expression analysis of AtMin7 in Arabidopsis leaves infected with F. graminearum
To understand further the mechanisms by which disruption of AtMin7 led to Arabidopsis susceptibility to F. graminearum, expression of AtMin7 was measured in wild-type Col-0 leaves inoculated with fungal spores. Transcripts levels were compared with mock-inoculated leaves (water and DON). Although considerable variation in AtMin7 expression was noted from the fungal inoculated leaves between replicates, no significant differences were observed between the mock and F. graminearum treatments (Fig. 3A). Therefore, F. graminearum infection does not seem to suppress expression of AtMin7 gene and/or transcript abundance during the infection cycle on Arabidopsis leaves. We next asked if MIN7 protein levels would also remain unchanged in F. graminearum-inoculated leaves. To test this, MIN7-specific antibodies were used to detect the protein in Arabidopsis leaves inoculated with F. graminearum, mock inoculated or left untreated (Fig. 3). MIN7 was detected in untreated and mock-inoculated leaves, whereas this protein was practically undetectable in the F. graminearum-inoculated leaves (Fig. 3B). These results suggest that MIN7 is destabilized and/ or degraded during fungal infection.
Identification and expression analysis of candidate wheat TaMin7 genes
To identify homologs of AtMin7 gene in wheat, a natural crop host of F. graminearum, we used the BioMart data mining tool available through Ensembl Plants (Smedley et al., 2015). A total of 26 gene sequences were identified in the reference hexaploid wheat (Triticum aestivum) genome (2n=6x=42, AABBDD) by searching for genes encoding proteins containing the catalytic SEC7 domain (PF12783) characteristic of ARF-GEF proteins. We then aligned the proteins encoded by the identified wheat genes with all eight members of the Arabidopsis ARF-GEF family proteins and used the resulting multiple alignment for phylogenetic analysis. The constructed maximum likelihood phylogenetic tree revealed that the three closely sequencerelated wheat proteins formed a distinct clade with Arabidopsis MIN7, suggesting these proteins represent the wheat A-, Band D-genome-encoded orthologs of MIN7 (Fig. 4).
TaMin7 transcript levels were also measured in wheat spikes both inoculated and non-inoculated with F. graminearum. Wheat spikelets were point inoculated with either water or fungal spores and tissues were collected at 5 dpi for RNA extraction and gene expression analysis using qPCR. Similar to Arabidopsis AtMin7, no significant differences were observed in the expression of TaMin7 genes between mock and fungal inoculated wheat plants (Supplementary Fig. S3). Unfortunately, the lack of antibody specificity for wheat MIN7 prevented protein quantification assessments in wheat.
Silencing the candidate TaMin7 genes in wheat spikes enhances susceptibility to F. graminearum To explore the potential function for MIN7 in the F. graminearumwheat interaction, we tested the effect of silencing the three homoeologous TaMin7 genes (TraesCS2A02G202900, TraesCS2B02G230000, and TraesCS2D02G212800) using BSMV-mediated VIGS on FHB disease development (Lee et al., 2012). A 209 bp region highly conserved between coding sequences of the three TaMin7 homoeologs was selected as a target for VIGS using the si-Fi21 software (Lück et al., 2019). This target region was predicted to generate a high number of silencing-effective siRNAs (n = 91), and a very low likelihood of off-target silencing.
An important factor for successful application of VIGS is the ability of the virus to infect and spread without having any deleterious effect in the host plant. Therefore, the feasibility of using the BSMV-mediated VIGS approach to induce systemic silencing in the spike tissue of wheat cv. Bobwhite susceptible to F. graminearum PH-1 (Brown et al., 2011) was first tested by visualizing the phenotype induced by silencing the Magnesiumchelatase subunit H (TaChlH; TraesCS7A02G480700) gene. Leaves were collected at 5 dpi. The endogenous MIN7 protein, detected by using the rabbit polyclonal MIN7 antibody in mock treated leaves, was absent in leaves infected with F. graminearum. The Coomassie stained SDS-PAGE image shown below demonstrates equal protein loading.
TaChlH is involved in chlorophyll biosynthesis and is often
used as a visible marker in VIGS (Yuan et al., 2011). The recombinant BSMV carrying a 250 bp fragment of TaChlH gene in an antisense orientation and BSMV::mcs4D harboring a non-coding DNA sequence of 275 bp were inoculated onto the flag leaves of wheat plants at the early boot stage. At 13 dpi the plants infected with BSMV::asTaChlH developed yelloworange coloration of the lemma and palea of spikes indicative of the loss of chlorophyll and successful silencing of the TaChlH gene, whereas the spikes of plants infected with the control construct BSMV::mcs4D showed typical mosaic symptoms ( Supplementary Fig. S4). No visible developmental abnormalities were observed in the wheat plants challenged with either of the two VIGS constructs. Moreover, similar levels of FHB disease were observed on wheat plants pre-infected with BSMV and on virus-free plants challenged with F. graminearum, indicating that the susceptibility to the fungus was not compromised in the virus-infected wheat (Fig. 5). These results suggest that BSMV-mediated VIGS can be used to silence genes in the reproductive tissue of wheat cv. Bobwhite and the approach appeared suitable for assessing the role of TaMin7 during F. graminearum infection in wheat.
The ability of BSMV::asTaMin7 to induce silencing of the corresponding endogenous genes was confirmed using RT-qPCR. The TaMin7 transcripts were decreased in abundance by 77% in the spikes of the VIGS-treated plants compared with those inoculated with the negative control BSMV::mcs4D, and no significant difference in TaMin7 expression levels was observed in the mock-versus BSMV::mcs4Dinoculated plants. To analyse the effect of TaMin7 silencing on F. graminearum infection, spikes of VIGS-treated plants showing typical virus-induced symptoms were point inoculated with the fungal conidia suspension and observed for disease symptoms for 15 d after fungal inoculation. Reduction of TaMin7 mRNA expression levels in spikes of the BSMV::asTaMin7treated plants was associated with significantly enhanced susceptibility to F. graminearum (Fig. 5). In contrast, no effect on FHB disease development was found in mock-inoculated and BSMV::mcs4D-inoculated control plants (Fig. 5).
Discussion
In this study, we have compared disease symptom formation caused by the fungus F. graminearum on the leaves of 11 different Arabidopsis vesicle trafficking mutant lines available in the ecotype Col-0 background. In total, eight different components of the membrane trafficking system, previously demonstrated to play important role(s) in plant defense during plant-pathogen interactions, have been evaluated (Table 1) (Gu et al., 2017;Yun and Kwon, 2017;Ekanayake et al., 2019). Strikingly, the two independent atmin7 mutants were shown to be highly susceptible to F. graminearum infection. Similarly, when expression of the three orthologs of AtMin7 were knocked-down in hexaploid wheat through VIGS, these TaMin7 silenced plants displayed significantly more FHB disease formation. Quantification of AtMin7 transcript levels in Arabidopsis and TaMin7 in wheat revealed no evidence that F. graminearum infections caused a reduction in transcript abundance. Instead, immunological evidence in Arabidopsis suggested that F. graminearum infections cause a reduction in MIN7 protein levels.
Some bacterial and oomycete pathogens are known to have evolved effector proteins that are translocated into plant cells to promote disease formation by interfering with plant membrane trafficking pathways (Ben Khaled et al., 2015). One of the vesicular trafficking genes whose role during plant disease has been previously well explored in the interactions between Arabidopsis and the bacterial pathogen P. syringae pv. tomato is AtMin7 (Nomura et al., 2006(Nomura et al., , 2011. The MIN7 protein localizes to the TGN/early endosome and is involved in endocytic recycling of plasma membrane resident proteins but it has also been hypothesized to regulate secretion (Tanaka et al., 2009;LaMontagne and Heese, 2017) (Fig. 1). Mutants that lack this protein allow increased bacterial multiplication, possibly due to misregulation of membrane trafficking of the plant defense-related cargo (Nomura et al., 2006(Nomura et al., , 2011. MIN7 has also been shown to contribute to the cytosol-initiated immune responses triggered by the P. syringae pv. tomato effectors such as AvrRpt2 and AvrPphB (Nomura et al., 2011) and to the apoplast-initiated immune responses through an unknown mechanism by preventing apoplast water soaking and therefore presumably restricting the flow of nutrients to the bacteria (Xin et al., 2016). To achieve successful disease Lee et al., 2012). cDNAs of the three BSMV genomic RNAs (α, β, and γ), each of which is required for full infection, were cloned into a binary vector, pCaBS, under the control of a double CaMV 35S promoter (2×35S) and flanked by a ribozyme sequence originating from Tobacco ringspot virus satellite RNA (Rz), which allows cis-cleavage of transcribed RNA at the 3′-end of viral genomic RNA. The RNAγ genome had been modified to include a small fragment of TaMin7 protein-coding sequence in the antisense orientation immediately downstream of the BSMV γb cistron. Viral cistrons are shown as yellow rectangles. (B) Images of representative wheat spikes at 15 dpi with F. graminearum from virus-untreated (no virus) plants and those treated with the control (BSMV::mcs4D) and the VIGS construct for silencing TaMin7 (BSMV::asTaMin7). (C) TaMin7 silenced wheat plants show increased susceptibility to F. graminearum infection. The proportion of infected spikelets is shown as the number of visibly diseased spikelets divided by the total number of spikelets present per wheat spike below the inoculation point. For each treatment a minimum of 12 spikes were inoculated and three independent experiments were performed. *P < 0.05; n is number of plants. (D) RT-qPCR assessment of TaMin7 transcript abundance in wheat plants. RNA extracted prior to F. graminearum inoculation and the relative abundance of TaMin7 transcripts was calculated using the threshold cycle (ΔΔC t ) method, normalized to the wheat CDC48 (Cell division control 48) gene. Error bars represent mean ±standard error of the means of three biological replicates. Significance of difference between mean transcript levels was determined using least significant differences at the 1% level of significance; ***P < 0.001. lesion formation, P. syringae pv. tomato secretes a conserved effector protein, HopM1, which is translocated to the TGN/ early endosome of its host during infection where it mediates destabilization of MIN7 followed by its degradation via the 26S proteasome (Nomura et al., 2011). Here we clearly demonstrated that MIN7 also contributes to defense against the fungal pathogen F. graminearum because the absence of this protein in Arabidopsis resulted in a markedly enhanced disease (Fig. 2). However, whereas atmin7 mutants displayed increased susceptibility to the P. syringae pv. tomato Δcel mutant that lacks HopM1 along with several other conserved effectors including AvrE (Nomura et al., 2011), we show that these same Arabidopsis mutants are clearly and unmistakably hypersusceptible to the wild-type strain of F. graminearum (Fig. 2).
Disruption of AtMin7 may compromise trafficking of specific molecules and cargo protein. These molecules could include plant defense-related proteins and/or secondary metabolites that help minimize F. graminearum infection. For example, callose, a (1,3)-β-glucan polymer, can act as a physical barrier reducing fungal penetration. Both increased callose deposition and F. graminearum-induced callose synthase activity in the infected spikelets and rachis nodes were found to be correlated with increased disease resistance (Ribichich et al., 2000;Blümke et al., 2014). Identification of proteins and/or other molecules transported specifically by membrane vesicles regulated by MIN7 is challenging, but comparison of vesicles cargo between wild-type and atmin7 Arabidopsis mutants during F. graminearum infection could provide valuable clues to the role of MIN7 protein during fungal disease establishment.
Surprisingly, none of the other tested trafficking Arabidopsis mutants gave a distinct phenotype when detached leaves were challenged with F. graminearum spores ( Fig. 2A). Most of the tested mutants, drp2b-1, drp2b-2, vps37-1, vps28-2, lip5-1, and AtMin7, were previously reported to be involved in immune responses to bacterial infection or bacterial pathogen-associated molecular patterns. DRP2B, VPS37, and VPS28 appear to be required for the regulation of the cell surface immune receptor FLAGELLIN SENSING 2 (Spallek et al., 2013;Smith et al., 2014). Disruption of LIP5 compromises basal resistance to P. syringae (Wang et al., 2014). Therefore, it is possible that this sub-set of trafficking proteins in Arabidopsis may have specialized function(s) in response to bacterial infection, but not fungal invasion. An unexpected result was obtained with the pen1 mutant ( Fig. 2A), which encodes the first SNARE to be identified with an immune function. PENETRATION-1 (PEN1), also known as Qa-SNARE SYNTAXIN OF PLANTS 121 (SYP121), is a component of a complex of SNARE proteins that plays a role in 'point defense' against fungal invaders, and loss of PEN1 function in Arabidopsis leads to almost 90% penetration success of the spores of the non-adapted powdery mildew fungus Blumeria graminis f. sp. hordei (Collins et al., 2003). PEN1/SYP121 forms a complex with at least four other proteins, namely SYNAPTOSOMAL-ASSOCIATED PROTEIN 33 kDa (SNAP33), Qbc-SNARE, and R-SNARE proteins VESICLE-ASSOCIATED MEMBRANE PROTEIN 721 and 722 (VAMP721 and VAMP722). We also tested sensitivity of vamp721 to F. graminearum in our study and observed levels of infection undistinguished from those in the wildtype Arabidopsis plants. However, VAMP721 and VAMP722 are known to be functionally redundant. The vamp721 vamp722 double null mutant plants could not be tested in the F. graminearum leaf bioassay because of severe growth defects and sometimes seedling lethality (Kwon et al., 2008b;Yun et al., 2013). Finally, in this study of F. graminearum, the level of infection of the syp122 mutant was comparable to that in the wildtype Arabidopsis plants ( Fig. 2A). SYP122 has been shown to share an overlapping function with PEN1 during certain aspects of plant development. However, when syp122 mutant plants were tested for resistance to B. graminis f. sp. hordei, a wild-type-like resistance response was retained (Assaad et al., 2004). Collectively, these results indicate that there are differences in the function of individual vesicular trafficking proteins when defending against adapted or non-adapted fungal pathogens.
Although Arabidopsis has proven to be a very useful model organism for unraveling the key mechanisms underlying interactions with pathogens including F. graminearum (Brewer and Hammond-Kosack, 2015), some findings cannot be translated directly to crop plants. Hence, studies involving interactions between the pathogens and their natural host plants could provide more relevant information and facilitate exploration of new strategies for disease control in crops. Here we utilized a transient gene silencing approach (VIGS) to assess the role of AtMin7 homologs in wheat, which is one of the most important staple food crops whose production is regularly threatened by fungal diseases including FHB. The results obtained from the analysis of the wheat-F. graminearum floral pathosystem (Fig. 5) are consistent with those from the study of the Arabidopsis-F. graminearum leaf pathosystem (Fig. 2) and provide evidence that disruption of MIN7 function in both dicotyledonous and monocotyledonous hosts and in both floral and leaf tissues compromises the plant innate immunity resulting in more severe disease.
To investigate whether F. graminearum utilizes similar mechanisms to the bacterial pathogen P. syringae pv. tomato to suppress host immunity and promote disease formation, the abundance of the AtMin7 transcripts and MIN7 protein was determined ( Fig. 3; Supplementary Fig. S3). In the various published whole wheat spike-F. graminearum transcriptome analyses, the abundance of the TaMin7 transcripts was found to be highly variable. For example, transcriptome analysis revealed less than a 1 log2-fold change of TaMin7 in both inoculated and non-inoculated plants in fully susceptible, moderately susceptible, or resistant cultivars (Pan et al., 2018). The RT-qPCR analysis done in this study confirms that TaMin7 transcript abundance is roughly equivalent in inoculated and non-inoculated whole wheat spikes collected at 5 dpi ( Supplementary Fig. S3). However, in a previously published transcriptome study that focused on dissected out different phases of F. graminearum infection, TaMin7 was down-regulated in infected tissue but only during the later symptomatic phase of disease formation (Dilks et al., 2019). In contrast, western blot analysis with anti-MIN7 antibodies provided clear evidence that MIN7 protein levels decrease following F. graminearum infection of Arabidopsis leaves (Fig. 3). Therefore, it is tempting to speculate that F. graminearum may contain effector(s) functionally similar to the P. syringae pv. tomato effector HopM1 that destabilizes MIN7 to suppress host immunity and hence to promote disease. Fusarium graminearum does not appear to possess a homolog of HopM1, and therefore further studies would be necessary to prove or disprove the above hypothesis.
Arabidopsis MIN7 has been shown to play a role in polar localization and dynamic repolarization of the PIN (PINformed) efflux carrier proteins enabling the directional transport of auxin in the tissues (Tanaka et al., 2013). Elevated levels of reactive oxygen species induced during stress responses in Arabidopsis affect MIN7-dependent PIN endocytic recycling resulting in increased accumulation of auxin in the affected tissues (Zwiewka et al., 2019). A recent study demonstrated that higher levels of auxin are accumulated during F. graminearum infection in a susceptible wheat cv. Roblin compared with the moderately resistant cultivars Wuhan 1 and Nyubai, indicating that auxin may promote susceptibility to this fungal pathogen (Brauer et al., 2019). However, prior exogenous application of auxin increased resistance to both floral and root Fusarium diseases whilst cytokinin applications increased both tissues' susceptibility (Petti et al., 2012, Haidoulis andNicholson, 2020). Collectively, the data from these previous studies together with findings from this study form the foundations of an alternative hypothesis regarding the mechanisms employed by F. graminearum for achieving successful infection. That is, it is conceivable that F. graminearum upon infection induces temporally coordinated waves of gene expression that regulate MIN7-dependent distribution and accumulation of auxin during infection, whereas the artificial elevation of auxin levels prior to infection significantly disrupts the establishment of this subtle F. graminearum controlled hormonal changes. Further studies are necessary to confirm or refute this hypothesis.
In this study, the initial vesicular trafficking mutant screen was done using Arabidopsis leaf infections. This approach has many advantages but also some drawbacks. For example, could some of the interaction phenotypes and mechanisms specific to F. graminearum infection of wheat spike tissues have been missed by the experimental approach taken? In the last three years considerable advances have been made in the resources and technologies now available to the global wheat research community. For example, fully sequenced wheat genome and transcriptomes are available for the reference wheat genotype Chinese Spring as well as multiple wheat cultivars (International Wheat Genome Sequencing Consortium, 2018;Walkowiak et al., 2020). In addition, mutant targeting induced local lesions in genomes (TILLING) populations and genome editing technologies can now be used in addition to VIGS for functional analyses in both hexaploid and tetraploid wheat species (Krasileva et al., 2017). In the near future, by selecting and purifying the most appropriate lines from these new resources it should be possible to re-evaluate in both tetraploid and hexaploid wheat the various role(s) of the full spectrum of vesicular trafficking mutants against a range of diverse pathogens with different in planta lifestyles that also infect different host niches.
Elucidating the mechanisms by which membrane trafficking regulates plant immune responses and acquiring an enhanced understanding of the membrane trafficking components and pathways manipulated by microbial pathogens to promote disease will provide fundamental new knowledge for the development of novel methods of disease intervention.
Supplementary data
The following supplementary data are available at JXB online. Fig. S1. Representative photos of Arabidopsis mutants and wild-type Col-0 used in this study. Fig. S2. Maximum likelihood phylogenetic tree indicating the relationship among Arabidopsis ARF-GEF encoding genes (coding sequences only). Fig. S3. Expression analysis of TaMin7 homoeologous genes in wheat spikes mock and F. graminearum inoculated by RT-qPCR. Fig. S4. Silencing of TaChlH (Mg-chelatase subunit H) gene in wheat spikes. Table S1. Primers used in this study for genotyping the various Arabidopsis mutants and for PCR analysis.
Funding
This work was supported by the UK Biotechnology and Biological Sciences Research Council (BBSRC) through the Institute Strategic Program grant Designing Future Wheat (BB/P016855/1) and the bilateral BBSRC-EMBRAPA grant (BB/N018095/1).
Data availability
All data supporting the findings of this study are available within the paper and within its supplementary data published online. The BSMV VIGS constructs used in this study are available on reasonable request from the corresponding author. | 9,751 | 2020-03-18T00:00:00.000 | [
"Biology"
] |
Swelling of ferrogels in uniform magnetic field – A theoretical approach
Magnetic field sensitive gels (ferrogels or magnetoelasts) are three-dimensional cross-linked networks of flexible polymers swollen by ferrofluids or magnetic fluids. The influence of external magnetic field on the equilibrium swelling degree is the subject of this study. Using thermodynamic arguments it is shown that uniform external field may result in deswelling of the ferrogels at high field intensities.
Introduction
A new type of magnetoelastic or magnetostrictive materials has been developed recently by introducing finely distributed colloidal particles into chemically cross-linked swollen polymer network .Magnetic field sensitive gels, generally referred as ferrogels are soft composite systems consisting of a rubbery polymer matrix (chemically cross-linked network) loaded with finely dispersed ferro-ferri-or superparamegnetic particles having Langevin type magnetisation.The magnetic particles are fixed to the network chains by strong adsorptive forces.Their motion is due to the fluctuation of network chains.No macroscopic migration can occur.
A comprehensive study of the effect of uniform field on the swelling behaviour is still missing.It is therefore a major objective of this work to build a significant understanding of the swelling behaviour of ferrogels under the action of uniform external magnetic field.We consider here a highly swollen chemically crosslinked network swollen in charge free organic liquid under good solvent condition.The gel contains randomly distributed magnetic particles showing superparamagnetic behaviour.
The swelling equilibrium under uniform magnetic field
In the absence of an external magnetic field, a ferrogel presents a swelling behaviour very close to that of a swollen filler-loaded network.The chemical potential of the swelling agent (denoted by index 1), µ 1 can be expressed as the sum of mixing-, µ 1,mi x elastic, µ 1,el contributions: These quantities can be derived from free energy of the elasticand mixing interactions [23]. (2) where P represents the volume fraction of the polymer in the gel, χ H stands for the Huggins interaction parameter, q 0 is the so Swelling of ferrogels in uniform magnetic field -A theoretical approach 93 called memory term, which is often identified as concentration of the polymer solution during cross-linking and ν * means the concentration of the elastically active network chains in the dry state.A is used as a model parameter with a value of 1 or 1/2.R and T is the gas constant and temperature, respectively.Fig. 1 shows the dependence of chemical potentials µ 1,mi x , µ 1,el and µ 1 on the volume fraction of the polymer.In equilibrium with pure solvent Eq.1 can be written as µ 1 = 0.Thus where e denotes the volume fraction of the polymer in swelling equilibrium.The solution of Eq.4 for e gives the dependence of swelling degree (q V = 1/ e ) on different quantities, like χ H (T ) and ν * .
A description of the effect of magnetic field on the thermodynamic properties requires the adoption of the magnetic energy as additional interaction energy.We consider here a piece of ferrogel under the action of a homogeneous magnetic field.The magnetic induction B, the magnetic field strength H and the magnetic moment per unit volume m are all parallel.The Gibbs free energy can be expressed as: where M = V • m is the total magnetic moment in the gel of volume V .In order to study the effect of external magnetic field on the swelling equilibrium we rewrite Eq.5 by introducing a new function G − µ o H M, which is a Legendre transformation of the Gibbs free energy function of G.
We also assume that the saturation magnetization occurs at very high magnetic field intensities.Taking into account Eq.6.with constant temperature and pressure, a Maxwell relation gives where χ m represents the molar magnetic susceptibility and the subcript 1 stands for the swelling agent.The magnetic susceptibility of ferrogel samples was found to be linearly dependent on the concentration of magnetic particles [9].
where m stands for the volume fraction of the magnetite in the whole gel, v m and v p denotes the volume of the magnetic material and the polymer in the gel, respectively.The quantity k χ was found to be 0.338 for magnetite loaded hydrogels [9].The quantities in Eq. ( 7) (V , n 1 and χ m ) can be related to the volume fraction P of the polymer in the gel.
where V 1 denotes the partial molar volume of the solvent which is considered to be constant.Combination of Eqs. ( 7) and ( 9) results in where µ 1 represents the magnetic contribution of the chemical potential of ferro fluid.After integration we have for the magnetic contribution of the swelling agent: This equation says that the magnetic interaction increases the chemical potential of the swelling agent.A linear dependence of µ 1,magn on the volume fraction of the polymer has been obtained, as shown in Fig. 2.
The dependence of the chemical potential of the swelling agent on the network parameter and on the magnetic field strength can be expressed as: Fig. 3 shows the effect of magnetic field intensity on the dependence of µ 1 on the polymer concentration.
The condition of swelling equilibrium under uniform magnetic field can be expressed as follows: Numerical solution of the above equation provides the equilibrium concentration as a function of magnetic field intensity.This is shown in Fig. 4.Not only the equilibrium volume fraction, e but also the swelling degree defined as q V = 1/ e is shown in the figure.
On the basis of these figures it can be concluded that significant effect of magnetic field on the equilibrium swelling degree can be expected at high field intensities.At small field intensities (0 ≤ B ≤ 300mT ) the change in the equilibrium swelling degree is comparable with the experimental accuracy.As the field intensity increases (B ≥ 300mT ), significant decrease of the swelling degree is expected.Swelling experiments have shown that in the range of (0 ≤ B ≤ 300mT ), no volume change was detected.
Fig. 1 .
Fig. 1.Components of the chemical potential of the swelling agent as a function of volume fraction of the polymer.For the calculation χ H = 0.3 and Aν * q −2/3 o = 2.15 • 10 −3 was used.
Fig. 2 .
Fig. 2. Dependence of magnetic chemical potential on the volume fraction of the polymer at two field intensities given in the Figure in A/m unit.For the calculation
Fig. 3 .
Fig. 3.The influence of magnetic field on the chemical potential.The magnetic field strength varies from left to right as 10 −5 • H =0, 5, 10 and 15 A/m.
Fig. 4 .
Fig. 4. The influence of magnetic induction on the equilibrium volume fraction (a), as well as the equilibrium swelling degree (b) of the ferrogel. | 1,562.4 | 2009-01-01T00:00:00.000 | [
"Materials Science"
] |
Single-center experience in 127 adult patients, mono or dual artificial liver support therapy, in patients with acute liver failure
Background Acute liver failure (ALF) is a serious condition characterized by sudden liver dysfunction, jaundice and hepatic encephalopathy. Its mortality rate of approximately 80% underscores the urgent need for effective treatments. Supportive extracorporeal therapies (SET), which temporarily support liver function and remove toxins, have shown promise in improving outcomes in acute liver failure (ALF). The aim of this study was to compare the outcomes of dual supportive extracorporeal therapy (SET) and mono supportive extracorporeal therapy in patients with acute liver failure. Methods A total of 127 patients with acute liver failure were included in this retrospective, single-center study. Of these, 62 patients received dual supportive extracorporeal therapy and 65 patients received mono supportive extracorporeal therapy. Primary endpoints were survival without the need for liver transplantation and mortality. Secondary endpoints included resolution of encephalopathy and normalization of International Normalized Ratio (INR). Results In the dual supportive extracorporeal therapy group, 59.6% of patients survived without the need for liver transplantation, while 27.4% achieved recovery with liver transplantation. The mortality rate in this group was 12.9%. Significant regression of encephalopathy grade was observed in 87% of patients, and the 1 year mortality rate for liver transplant recipients was 10.7%. In the mono supportive extracorporeal therapy group, 61.5% of patients experienced a successful recovery without the need for liver transplantation, with a mortality rate of 29.2%. Significant improvement in the grade of encephalopathy was observed in 70.7% of patients. Conclusion Both dual supportive extracorporeal therapy (CVVHDF and PE) and mono supportive extracorporeal therapy (PE) were associated with significant improvements in renal and hepatic biochemical parameters, blood ammonia levels, and neurological status in patients with acute liver failure associated with grade III-IV hepatic encephalopathy. In particular, dual support was associated with improved hemodynamic stability, lactic acidosis and acid–base balance. Survival in acute liver failure in our retrospective cohort using a protocolized approach to extracorporeal therapies is higher compared to previously published large ALF studies. This protocolized approach warrants further prospective studies.
Introduction
Acute liver failure (ALF) is characterized by the sudden onset of jaundice, impaired synthesis of liver proteins, and hepatic encephalopathy in individuals without a preexisting liver disorder.It is a grave and intricate condition that arises from the abrupt and extensive destruction of liver cells (1)(2)(3).Acute liver failure carries a grim prognosis, as it is associated with an approximate mortality rate of 80% (4).However, through enhanced comprehension of the underlying factors contributing to ALF, targeted supportive extracorporeal therapies (SET), advancements in intensive care practices, and the accessibility of liver transplantation (LT), the prognosis for ALF patients has significantly improved (5).Presently, among patients with ALF, over 43% manage to survive with SET without requiring a liver transplant, while approximately 28% do not survive the condition, and roughly 29% undergo a liver transplantation procedure.In addition, individuals who undergo a liver transplant exhibit a 1 year survival rate of around 60-90% (6).Acute liver failure is a rare condition, occurring in only 1-8 instances per million individuals, and it contributes to 6% of liver disease-related deaths and up to 7-8% of liver transplantations.The progression of cerebral swelling, sepsis, and failure of multiple organs are the primary factors leading to mortality (7)(8)(9).
Supportive extracorporeal therapy is a medical procedure that offers temporary and partial substitution of liver function, alongside the elimination of detrimental substances and provision of advantageous biological elements.This supportive extracorporeal therapy aims to facilitate the revitalization and functional recuperation of the patient's liver cells (10,11).Continuous venovenous hemodiafiltration (CVVHDF) and plasma exchange (PE) are used as mono or dual SET, both for bridge to liver transplant or Recovery in ALF patients (11)(12)(13).
This 15 years retrospective study aimed to evaluate supportive extracorporeal therapy (SET), including dual (CVVHDF and PE) and mono (PE) therapies, for 127 adults with acute liver failure.
Dual supportive extracorporeal therapy
Dual supportive extracorporeal therapy (SET) involves the concurrent use of plasma exchange and continuous venovenous hemodiafiltration.This treatment regimen entails performing one or two plasma exchange sessions per day while simultaneously continuing with continuous venovenous hemodiafiltration.
Patients
A retrospective analysis of the medical records of 127 adult patients followed up in the Memorial Sisli Hospital Organ Transplant Center, Istanbul, Turkey, between January 2006 and December 2020 was included in this study.It consisted of two groups, 65 patients receiving mono SET-PE and 62 patients receiving dual SET-PE and CVVHDF (CRRT).The hospital performed an average of 100 liver transplants per year during this period, and all patients in the study were selected from those followed in the Intensive Care Unit.Patients also received conventional hepatic failure and hepatic encephalopathy (HE) medical treatment options.
Acute liver failure was characterized on the basis of the following conditions: (1) the absence of known chronic liver disease; (2) the presence of biochemical indicators of acute liver failure, such as elevated transaminase levels, within a period of less than 8 weeks; (3) the presence of liver-related coagulopathy, as indicated by a prothrombin time (PT) of 15 s or higher or an international normalized ratio (INR) of 1. 5 or higher that does not improve with vitamin K administration, together with clinical evidence of hepatic encephalopathy (HE), or a PT of 20 s or higher or an INR of 2.0 or higher, regardless of the presence of HE (14).
In patients with acute liver failure (ALF), the decision for liver transplantation was based on the End Stage Liver Disease Model-Na (MELD-Na) score.Mono SET with plasma exchange (PE) was considered for inclusion if the patient had high PT/INR levels or high PT/INR and ammonia levels (grade 3-4 encephalopaty).Dual SET with continuous venovenous hemodiafiltration (CVVHDF) and PE was included if the patient had high PT/INR and ammonia levels (grade 3-4 encephalopathy) or developed renal failure such as hepatorenal syndrome.The primary objective of these therapies was to serve as a bridge to liver transplantation or promote recovery.Patients who did not have ALF or did not receive supportive extracorporeal therapy were excluded from the study (Figure 1; Table 1).
SET protocol
We used the protocol published by Ocak (15) for the indication of mono or dual supportive extracorporeal therapy and liver transplantation.Our apheresis technicians and nurses performed the supportive extracorporeal treatment in our unit in accordance with this protocol.The grade of hepatic encephalopathy was assessed using the West Haven classification.
CVVHDF (CRRT) protocol
We employed a renal replacement device and hemodiafiltration kit manufactured by Fresenius Medical Care, based in Bad Homburg, Germany, for the purpose of conducting continuous venovenous hemodiafiltration.Throughout the day, we consistently administered continuous citrate-calcium anticoagulation, maintaining blood flow rates between 3 and 5 mL per kilogram per minute, along with dialysate flow rates ranging from 180 to 300 mL per kilogram per hour.The dialysate and replacement solutions employed encompassed multibic, multiplus, citrate-calcium dialysate, citrate-calcium dialysate-potassium 2 plus, and 4% sodium citrate.exchange Kit.The treatment was administered twice daily for a duration of 2-6 h per session.The flow rate for each session was calculated at 10-30 cc/min, and the volume of sessions was determined as 50 cc/kg.Additionally, 1.5 volumes of fresh frozen plasma were used to replace an equivalent volume without the use of anticoagulant treatment.The study encompassed the analysis of laboratory values and monitoring of vital signs both before and after the supportive extracorporeal therapy.It also examined the duration and frequency of the plasma exchange treatments.
Ethics approval
The retrospective study was approved by the Institutional Review Board of Memorial Sisli Hospital with the date 03/06/2022 and number 522/22.In light of the retrospective nature of the study, Informed consent was not required.
Statistical analyses
The statistical analysis was performed using the Statistical Package for Social Sciences version 26.0 (IBM Corp.; Armonk, New York, United States).To assess the normality of the study data, the Kolmogorov-Smirnov analysis was employed.For normally distributed data, the mean values were utilized, whereas non-normally distributed data was represented using the median (interquartile range).To compare the pre-and post-session laboratory values for supportive extracorporeal therapy, the Wilcoxon test was utilized.For this study, a significance level of less than 0.05 (p < 0.05) was considered statistically significant.
Results
Inclusion and exclusion criteria, demographic information, etiolgy, the Acute Physiology and Chronic Health Evaluation 2 score, the Model for End-stage Liver Disease-Na score, and the etiology were all documented when adult patients were admitted to the Intensive Care Unit (Table 1).
Dual and mono SET results
A group of 62 dual SET patients received dual supportive extracorporeal therapy for an average of 9 days.Among these patients, all 62 received plasma exchange treatments twice daily.The number of sessions varied from 6 to 36, with an average of 17.98.In addition, the average duration of continuous venovenous hemodiafiltration was 230 h (equivalent to 9.58 days), ranging from 71 to 434 h.
In the group of 65 mono SET patients, mono supportive extracorporeal therapy was administered for an average of 7 days.Among these patients, all 65 received twice daily plasma exchange treatments.The number of sessions ranged from 4 to 28, with an average of 14.11.
Laboratory values of before and after SET
Prior to the initial implementation of dual supportive extracorporeal therapy, the levels of total bilirubin in the serum of patients who underwent liver transplants were significantly higher compared to those patients who did not receive liver transplants.However, ALT and AST levels were substantially lower.Following the application of dual supportive extracorporeal therapy, the patients who did not undergo liver transplants exhibited notably better results in terms of serum ammonia, PT/INR, and total bilirubin measurements (Table 2).After the last dual SET, both patients with and without liver transplants showed significantly lower levels of total bilirubin, ALT, AST, ammonia, creatinine, and PT/INR compared to their initial levels before the dual SET.Additionally, there were significant improvements in blood gas parameters such as pH, bicarbonate, and lactate.The platelet count showed a significant increase, indicating better blood clotting.Moreover, there were improvements in mean arterial pressure (MAP) and heart rate, suggesting better cardiovascular stability.A significant decrease in the creatinine level also shows that it can prevent the negative effects of renal dysfunction (Table 3).After the last mono SET, the serum levels of total bilirubin, ALT, AST, ammonia, and PT/INR showed a significant decrease compared to the initial levels before mono SET in all patients.However, there was no significant improvement observed in the pH, bicarbonate, and lactate levels in the blood gas analysis.Furthermore, there was no significant improvement in the platelet count and creatinine level.Similarly, there was no significant improvement in the mean arterial pressure (MAP) and heart rate (Table 4).Due to the small number of patients who underwent liver transplantation and mono SET, biochemical comparisons were not made.
Comparison of dual SET and mono SET results
Comparing the effects of mono SET and dual SET, both therapy approaches resulted in significant improvements in various indicators of organ recovery.In the case of dual SET, which involved patients with and without liver transplants, there were notable reductions in total bilirubin, ALT, AST, ammonia, creatinine, and PT/INR levels compared to their initial values.These reductions may represent clearance effects of both therapies or improvement intrinsic organ function.Additionally, blood gas parameters such as pH, bicarbonate, and lactate showed significant improvements, indicating improved acid-base balance.The increase in platelet count suggests improved blood clotting, while the improvements in mean arterial pressure (MAP) and heart rate point towards better cardiovascular stability.On the other hand, mono SET led to significant decreases in total bilirubin, ALT, AST, ammonia, and PT/INR levels in all patients.These reductions may represent clearance effects of mono SET or improvement intrinsic organ function, similar to Dual SET.However, the blood gas analysis did not show significant improvements in pH, bicarbonate, and lactate levels, suggesting that acid-base balance might not have been as effectively regulated by Mono SET.Additionally, there were no significant improvements in platelet count and creatinine levels, suggesting that blood clotting and kidney function may not have been benefited significantly by this treatment approach.Similarly, there were no significant improvements in mean arterial pressure (MAP) and heart rate, indicating that cardiovascular stability might not have been as positively influenced by mono SET compared to dual SET.In summary, while both mono SET and dual SET showed improvements in liver function, Dual SET appeared to have more comprehensive effects, including better acid-base balance, improved blood clotting, and cardiovascular stability.
Adverse effects of SET
During the use of dual supportive extracorporeal therapy, hypernatremia developed in 3 patients, metabolic alkalosis in 3 patients, and hypocalcemia in 2 patients.Nevertheless, the introduction of hemodiafiltration as part of the supportive extracorporeal therapy provided beneficial results by alleviating these conditions.In addition, five individuals experienced a superficial allergic reaction due to the use of fresh frozen plasma during plasma exchange.As a precaution, the procedure was temporarily halted and a new batch of fresh frozen plasma was used.After resolution of the allergic reaction, the procedure was continued.During mono supportive extracorporeal therapy, hypervolemia developed in 4 patients, hypernatremia in 5 patients, metabolic alkalosis in 6 patients, and hypocalcemia in 3 patients during plasma exchange.However, appropriate supportive care was provided and these conditions improved.In addition, six subjects experienced a superficial allergic reaction due to the use of fresh frozen plasma during plasma exchange.Again, the procedure was temporarily suspended.After resolution of the allergic reaction, the procedure was resumed.
Despite the use of local citrate in CVVHDF application, side effects such as electrolyte disturbances did not develop due to balanced antidote (calcium) and dialysate solutions.This was controlled by monitoring electrolytes and blood gases every 2 hours.Macro-and micronutrient deficiencies also did not develop.
Mortality
Of the 62 patients who received dual supportive extracorporeal therapy (SET), 37 patients (59.6%) survived without requiring liver transplantation.In addition, 17 patients (27.4%) survived but required liver transplantation.Mortality rate in this group was 12.9% (8 patients), with all deaths occurring within the first 18 days of dual SET.In addition, patients who underwent liver transplantation had a 1 year mortality rate of 10.7%.In contrast, 40 (61.5%) of 65 patients who underwent mono supported extracorporeal therapy had a successful recovery, and 6 patients (9.2%) survived but required liver transplantation.However, mortality rate was higher in this group at 29.2% (19 patients), with all deaths occurring within the first 14 days of mono SET.
Discussion of dual SET and mono SET findings
In this study, we evaluated two groups of patients with acute liver failure who were followed in the intensive care unit, consisting of 62 patients receiving dual supportive extracorporeal therapy and 65 patients who received mono supportive extracorporeal therapy.When comparing the outcomes of patients who received dual supportive extracorporeal therapy (SET) with those who received mono-supportive extracorporeal therapy, significant differences were observed.In the case of dual SET, out of 62 patients, a majority of 37 individuals (59.6%) were able to survive without the need for liver transplantation.Seventeen (27.4%) patients recovered with liver transplantation.However, it should be noted that the mortality rate for this group was 12.9% (8 patients).Of note, all deaths occurred within the first 18 days of dual SET.A remarkable 87% resolution or reduction in the grade of encephalopathy was also noted.In addition, the 1 year mortality rate for patients who received a liver transplant was 10.7%.Among the group of 65 patients who received mono-SET, a remarkable proportion of 40 individuals (equivalent to 61.5%) experienced a successful recovery without the need for liver transplantation.In addition, 6 patients (9.2%) achieved recovery with the use of liver transplantation.A remarkable 70.7% recovery in the grade of encephalopathy was also noted.However, the mortality rate for this group was relatively higher at 29.2% (19 patients).When comparing the two regimens, dual SET (11.3%) resulted in a lower mortality compared to mono SET (29.2%).However, the rate of successful recovery without the need for liver transplantation was similar in mono SET (61.5%) and dual-SET (59.6%).There was significant regression and improvement in all laboratory values in 8 patients who died in the dual SET group of 62 patients in this study.However, we found that the grade of encephalopathy could not be permanently regressed and the INR could not be permanently normalized.Although these patients survived for approximately 18 days, liver transplantation could not be performed because a suitable donor could not be found.We found that in 37 adult patients who recovered clinically, the encephalopathy grade regressed to 1 and below, while the INR was permanently normalized.In addition, mean arterial pressure increased significantly, vital signs stabilized, and fluid, electrolyte, and acid-base balance were preserved.In this group, liver transplantation was performed in 17 patients who did not have sufficient improvement in encephalopathy and continuous normalization of INR.However, bridge-to-transplant was performed with dual SET.Recovery was achieved by liver transplantation.In the mono SET group, which consisted of 65 patients, 19 patients died, although there was a significant decrease in all liver laboratory values, there was no significant improvement in renal laboratory values, hemodynamic parameters, and platelet count.In addition, it was found that the grade of encephalopathy was not permanently reduced and the INR was not permanently normalized in the patients who died in the mono SET group.Although these patients survived up to 14 days, liver
Comparison of dual SET and mono SET findings
When we compared the groups in our study, the side effects in both groups were mostly due to the use of fresh frozen plasma (FFP).Reversibility was achieved with supportive care.In both groups, patients without permanent regression of encephalopathy grade and INR stability either underwent liver transplantation or died.In addition, dual SET had a favorable effect on the improvement of hemodynamic stability and biochemical parameters.There was also a significant improvement in cerebral function in the Dual SET group.This effect may be associated with the observed reduction in mortality and morbidity.Adverse effects in these two groups were associated with the use of FFP for replacement.
Recent studies have shown that dual liver support therapies (PE + CRRT) in adult (17-19) and pediatric (12,15,16,20).ALF patients improve hepatic biochemical parameters, neurological status, and hemodynamic stability.In addition, they have been found to provide a bridge to liver transplantation.Similar to these studies, neurological status and hemodynamic stability improved in our study.Regression was observed in encephalopathy grade.Also bridge to transplantation was performed.In our study, the mortality rate was 12.9% and the liver transplantation rate was 27.4%.
In recent studies by Maiwall et al. (21, 22) (mortality rate 25%), and Larsen et al. (7,23) (mortality rate 41.3%) in ALF patients, it was shown that mono liver support therapies (PE) improved liver biochemical parameters and neurological status.In addition, they showed that they provided a bridge to transplantation.In our study, similar to these studies, neurological status was improved.Also provided a bridge to transplantation.In our study, the mortality rate was 29.2% and the liver transplantation rate was 9.2%.It should be noted that at the end of dual or mono SET, accessibility to liver transplantation has a significant positive effect on survival.
Discussion of the mechanism of action of dual SET and mono SET
Acute liver failure is a catastrophic, complex pathophysiological process that can lead to rapid death in MOF.The primary goal of an ideal treatment should be to stop the cascade leading to this devastating process by removing circulating blood (24).Due to the nature of the disease, plasma products used to correct coagulopathy increase protein load and exacerbate hyperammonemia (24, 25).Ammonia is involved in the pathogenesis of central nervous system toxicity in ALF, and high ammonia levels have been shown to be a poor prognostic factor for herniation and cerebral edema.One of the most effective methods of extracorporeal therapy to reduce ammonia is CRRT (26)(27)(28).Therefore, the use of dual SET (PE + CRRT) is reasonable and may provide a successful bridge to liver transplantation (29,30).Plasma exchange (mono SET) removes plasma cytokines and mediators of the systemic inflammatory cascade and provides repeat factors synthesized by the liver.Plasma exchange can be performed in patients who are in poor condition and can be used as supportive therapy for the patient until spontaneous recovery occurs or liver transplantation is possible.Plasma exchange is an extracorporeal treatment modality used in acute liver failure (31).High volume plasma exchange is recommended in the American Society for Apheresis (ASFA) guidelines as Category I and Grade 1A in the management of acute liver failure (32).Plasma exchange can be used as a supportive therapy until spontaneous recovery or liver transplantation.
Hypothesis
Dual supportive extracorporeal therapy (SET) is associated with lower mortality and improved outcomes compared with mono supportive extracorporeal therapy in patients with acute liver failure.The results of our study showed significant differences in outcomes between patients who received dual SET and those who received mono SET for the treatment of acute liver failure.The dual SET group had a lower mortality rate (12.9%) compared to the mono SET group (29.2%).In addition, a higher proportion of patients in the dual SET group recovered without the need for liver transplantation (59.6% vs. 61.5%).The observed lower mortality rate in the dual SET group suggests that the combination of supportive therapies used in this approach may have a synergistic effect in improving patient outcomes.The dual SET group also showed a remarkable resolution or reduction in the grade of encephalopathy (87%), indicating improved neurological function.In contrast, the mono SET group had a lower rate of improvement in encephalopathy (70.7%), which may have contributed to the higher mortality rate observed in this group.
In addition, the dual SET group had significant improvements in laboratory values, mean arterial pressure, vital signs, and fluid, electrolyte, and acid-base balance.These findings suggest that dual SET may have a more comprehensive effect on multiple organ systems, leading to improved hemodynamics and overall patient stability.
It is worth noting that both groups experienced limitations in performing liver transplantation due to the unavailability of suitable donors.However, in cases where liver transplantation was performed, the 1 year mortality rate was relatively low (10.7% for dual-SET and 9.2% for mono-SET), indicating the efficacy of transplantation in improving long-term survival.
The results of our study support the hypothesis that dual supportive extracorporeal therapy is associated with lower mortality and improved outcomes compared with mono supportive extracorporeal therapy in patients with acute liver failure.The combination of supportive therapies in dual SET appears to have a synergistic effect, resulting in better neurological function, improved hemodynamics and overall patient stability.
Limitations
Single center, retrospective nonrandomized study.Outcomes were not statistically compared between intervention groups due to limited number an variability in transplantation rates in both groups.Inferences in difference in outcomes between therapies are meant to be speculative and hypothesis generating.However survival outcomes from our center are higher than previously published studies.
Conclusion
Both dual supportive extracorporeal therapy (CVVHDF and PE) and mono supportive extracorporeal therapy (PE) were associated with significant improvements in renal and hepatic biochemical parameters, blood ammonia levels, and neurological status in patients with acute liver failure associated with grade III-IV hepatic encephalopathy.Dual supportive in particular was associated with improved hemodynamic stability, lactic acidosis and acid base balance.Survival in ALF in our retrospective cohort using a protocolized approach to extracorporeal therapies is higher compared to previously published large ALF studies.This protocolized approach warrant further prospective studies.
FIGURE 1 Flow
FIGURE 1Flow diagram of patients in the study.
TABLE 1
Data on acute liver failure patients monitored in the intensive care unit.
TABLE 2
Laboratory values in patients with acute liver failure with or without liver transplant before the start of dual supportive extracorporeal therapy (SET) and after the final of dual SET.
TABLE 3
Dual supportive extracorporeal therapy (SET) laboratory values before the start of dual SET and after the final of dual SET.
TABLE 4
Mono supportive extracorporeal therapy (SET) laboratory values before the start of mono SET and after the final of mono SET. could not be performed because a suitable donor could not be found.However, 40 clinically recovered adult patients in this group also improved to grade 1 or less encephalopathy and achieved sustained normalization of INR.In this group, liver transplantation was performed in 6 patients who did not have sufficient improvement in encephalopathy and continuous normalization of INR.In addition, although drug toxicity was the predominant etiology in the mono SET group, there was a similar recovery in the dual SET group.The mortality rate was found to be higher in the mono SET group (mortality rate 29.2%) compared to the dual SET group (mortality rate 12.9%).The high mortality rate may be due to the insufficient effect of Mono SET on non-hepatic organs and hemodynamics, as well as the lack of suitable donors for liver transplantation in this group.There was no significant difference between patients who died and those who survived in terms of the scales used to calculate the severity of liver disease (MELD-Na, APACHE 2 scores) (16). | 5,689.6 | 2023-09-22T00:00:00.000 | [
"Medicine",
"Biology"
] |
Performance and Microbial Community of Different Biofilm Membrane Bioreactors Treating Antibiotic-Containing Synthetic Mariculture Wastewater
The performance of pollutant removals, tetracycline (TC) and norfloxacin (NOR) removals, membrane fouling mitigation and the microbial community of three Anoxic/Oxic membrane bioreactors (AO-MBRs), including a moving bed biofilm MBR (MBRa), a fixed biofilm MBR (MBRb) and an AO-MBR (MBRc) for control, were compared in treating antibiotic-containing synthetic mariculture wastewater. The results showed that MBRb had the best effect on antibiotic removal and membrane fouling mitigation compared to the other two bioreactors. The maximum removal rate of TC reached 91.65% and the maximum removal rate of NOR reached 45.46% in MBRb. The addition of antibiotics had little effect on the removal of chemical oxygen demand (COD) and ammonia nitrogen (NH4+-N)—both maintained more than 90% removal rate during the entire operation. High-throughput sequencing demonstrated that TC and NOR resulted in a significant decrease in the microbial diversity and the microbial richness MBRs. Flavobacteriia, Firmicutes and Azoarcus, regarded as drug-resistant bacteria, might play a crucial part in the removal of antibiotics. In addition, the dynamics of microbial community had a great change, which included the accumulation of resistant microorganisms and the gradual reduction or disappearance of other microorganisms under antibiotic pressure. The research provides an insight into the antibiotic-containing mariculture wastewater treatment and has certain reference value.
Introduction
In recent years, mariculture has become a fast-developing industry with increasing global population and seafood demand [1]. China is the world's largest mariculture country and is accompanied by the abuse of a large number of antibiotics [2]. In mariculture wastewater, numerous antibiotics are overused to prevent bacterial contamination, cure diseases and promote fish growth [3][4][5]. Nevertheless, only 20-30% of antibiotics used in mariculture systems are absorbed by mariculture products, while residual antibiotics (>75%) are left over in the feeding water and accumulate in the sediment [6]. The improper treatment of mariculture wastewater may cause the deterioration of the surrounding estuary ecosystem [7]. Studies have shown that the antibiotics in mariculture wastewater could affect the ecotoxicity of aquatic organisms in the surrounding estuarine ecosystems [8,9].
Inoculated Sludge and Wastewater Composition
The test sludge was inoculated from a sewage disposal plant in Ningbo, China. In the experiment, the synthetic mariculture wastewater was introduced by an influent pump into the MBRs. The composition of the synthetic mariculture wastewater was listed in the document [20] and 30 g/L of salinity was selected, the usual salinity level in mariculture wastewater. The influent concentrations of COD, NH4 + -N and NO3 --N were 100-140, 8-10 and 3.3-4.2 mg/L, respectively. The prepared TC and NOR standard stock solutions with concentrations of 100 mg/L were stored in a refrigerator at 4°C, protected from light. The appropriate amount of standard storage solution (its initial concentration was 100 mg/L and diluted to 200 μg/L) were added to the influent, which was slightly higher than the concentration of antibiotics contained in the Xiangshan mariculture wastewater.
To study the effect of antibiotics on the MBRs process in mariculture wastewater, the experiment was divided into 3 stages: no antibiotics were added in the influent in phase 0 (P0) (0-11 day), then TC at the concentration of 200 μg/L was spiked into the influent in phase 1 (P1) (12-27 day), finally in order to explore the coexistence of different antibiotics the NOR was added to the influent with TC with the concentration of 200 μg/L in phase 2 (P2) (28-52 day), respectively.
Analytical Methods
The samples were selected daily and each sample was analyzed in three replicates. All the water samples were analyzed immediately (within 2 h) for parameters, including those with COD, NH4 + -N, NO3 --N and NO2 --N with the Standard Methods [21] using UV-Vis Spectrophotometer (D500, Hach, Loveland, Co, USA).
Solid phase extraction (SPE) (SPEQ-24B, Shanghai, China) was used as the pretreatment method of samples and the methodology of sample pretreatment was adopted from earlier studies [22,23]. The TC and NOR were quantified using high-performance liquid chromatography (HPCL, Hitachi CM5000, Tokyo, Japan) with ultraviolet detection at 270 nm and 280 nm, respectively, which was equipped with an Agilent Eclipse XDB-C18 chromatography column (4.6 × 150 mm 2 , 5 μm). The
Inoculated Sludge and Wastewater Composition
The test sludge was inoculated from a sewage disposal plant in Ningbo, China. In the experiment, the synthetic mariculture wastewater was introduced by an influent pump into the MBRs. The composition of the synthetic mariculture wastewater was listed in the document [20] and 30 g/L of salinity was selected, the usual salinity level in mariculture wastewater. The influent concentrations of COD, NH 4 + -N and NO 3 − -N were 100-140, 8-10 and 3.3-4.2 mg/L, respectively. The prepared TC and NOR standard stock solutions with concentrations of 100 mg/L were stored in a refrigerator at 4 • C, protected from light. The appropriate amount of standard storage solution (its initial concentration was 100 mg/L and diluted to 200 µg/L) were added to the influent, which was slightly higher than the concentration of antibiotics contained in the Xiangshan mariculture wastewater.
To study the effect of antibiotics on the MBRs process in mariculture wastewater, the experiment was divided into 3 stages: no antibiotics were added in the influent in phase 0 (P0) (0-11 day), then TC at the concentration of 200 µg/L was spiked into the influent in phase 1 (P1) (12-27 day), finally in order to explore the coexistence of different antibiotics the NOR was added to the influent with TC with the concentration of 200 µg/L in phase 2 (P2) (28-52 day), respectively.
Analytical Methods
The samples were selected daily and each sample was analyzed in three replicates. All the water samples were analyzed immediately (within 2 h) for parameters, including those with COD, NH 4 + -N, NO 3 − -N and NO 2 − -N with the Standard Methods [21] using UV-Vis Spectrophotometer (D500, Hach, Loveland, CO, USA). Solid phase extraction (SPE) (SPEQ-24B, Shanghai, China) was used as the pretreatment method of samples and the methodology of sample pretreatment was adopted from earlier studies [22,23]. The TC and NOR were quantified using high-performance liquid chromatography (HPCL, Hitachi CM5000, Tokyo, Japan) with ultraviolet detection at 270 nm and 280 nm, respectively, which was equipped with an Agilent Eclipse XDB-C18 chromatography column (4.6 × 150 mm 2 , 5 µm). The mobile phase for TC consisted of 81%:19% (v/v) acetonitrile and 0.1% formic acid at a flow rate of 1 mL/min. The detailed information of analysis conditions of HPLC for NOR was described before [24].
In addition, a comprehensive analysis of microbial communities under different stages by 16S rRNA sequencing were performed. First, activated sludge in the aerobic tanks of MBRa, MBRb, and MBRc were sampled when their removal performances were stable at each stage. The E.Z.N.A. ® Soil DNA Kits (Omega Bio-tek, Norcross, GA, USA) were used to extract DNA from the sludge samples. High-throughput sequencing was selected by an Illumina MiSeq platform in accordance with the report [20].
Removal of Bulk Pollutants
As shown in Figure 2a, the addition of TC and NOR had little effect on the COD removal compared to the reactor performance in phase 0 (without antibiotics). The average COD removal rate was maintained at 91.24 ± 1.35%, 95.13 ± 0.66% and 90.21 ± 1.66% in phase 0, and 88.89 ± 1.32%, 95.57 ± 1.82% and 88.01 ± 2.18% in phase 1, and 90.29 ± 1.40%, 95.05 ± 1.47% and 88.57 ± 1.95% in phase 2 in MBRa, MBRb, and MBRc during the entire operation, respectively. The results indicate that all reactors had the high removal efficiency of organic matter, and the COD removal efficiency of the MBRb reactor was a bit higher than that of the MBRa reactor and MBRc reactor throughout the operation. The results were consistent with those of previous studies, indicating that ≤20 mg/L antibiotics had no effect on the elimination of COD [25].
The antibiotics effects on the NH 4 + -N removal rate in the MBRa, MBRb, and MBRc system are shown in Figure 2b. Before antibiotics were added (0−11 day), the NH 4 + -N removal rate of MBRa and MBRc was similar (95.55 ± 3.03% MBRa and 94.91 ± 2.96% MBRc, P > 0.05), while NH 4 + -N removal rate MBRb (97.03 ± 2.05% MBRb, P > 0.05) was slightly higher than those of MBRa and MBRc. After adding 200 µg/L TC in the influent, the removal rate of NH 4 + -N in effluent fluctuated obviously in a short period of time, even fell below 0%, then recovered quickly and declined to 91.5 ± 1.45% in MBRa, 93.33 ± 1.32% in MBRb and 90.17 ± 2.28% in MBRc, respectively. The literature shows that high concentrations of tetracycline did not have a significant negative effect on dehydrogenase activity and the tetracycline inhibits the microbial biomass of NOB [26]. The internal organism nitrogen is released into the solution, increasing the concentration of ammonia nitrogen [27]. When NOR was added at 200 µg/L in the influent, which already contained TC, the removal rate of NH 4 + -N was greatly affected. This may be that the subsequent denitrifying flora was inhibited from the beginning and gradually restored its activity as the running time increased. The final removal rate of NH 4 + -N was maintained at 88.7 ± 2.79% MBRa, 91.47 ± 2.62% MBRb and 88.46 ± 2.35% MBRc, respectively. Additionally, the effluent concentrations of NO 2 − -N ( Figure 2c) rose gradually in the reactors, which might be related to the presence of TC and NOR that led to nitrite accumulation [28]. MBRb and MBRa had better NO 3 − -N removal rate (above 50%) (Figure 2d) in the presence of antibiotics than MBRc because the thicker biofilm further enhanced denitrification capacity. These results indicated that carbon and nitrogen shared similar trends at every stable stage, which means that the 200 µg/L concentration of TC and NOR tested did not affect organic matter removal and nitrogen removal efficiency. However, the concentration of TC and NOR reported to affect the nitrification performance was much higher than that reported in mariculture wastewater (ng/L to µg/L) and used in this study [29,30].
MBRa, MBRb, and MBRc during the entire operation, respectively. The results indicate that all reactors had the high removal efficiency of organic matter, and the COD removal efficiency of the MBRb reactor was a bit higher than that of the MBRa reactor and MBRc reactor throughout the operation. The results were consistent with those of previous studies, indicating that ≤20 mg/L antibiotics had no effect on the elimination of COD [25].
Removal of Antibiotics
After a brief period of acclimatization, the water quality indexes of the effluent tended to relatively stable values. When antibiotics were added to the three reactors, some quantities of antibiotics were decomposed, some quantities of antibiotics remained in the wastewater, and some quantities of antibiotics entered the activated sludge due to adsorption. Figure 3 showed the removal of antibiotics in the three reactors at different operating stages. The three reactors shared a similar trend. The removal rates of TC first increased from 73.86% to 89.77% in MBRa, 78.15% to 91.65% in MBRb and 62.36% to 81.07% in MBRc at 16 days, and then quickly decreased to 78.0% in MBRa, 83.01% in MBRb and 63.25% in MBRc at 22 days. Note that the removal rates of TC rose sharply in the first 10 days. The reason might be that adsorption played a main role in the early process. The adsorption of TC occurred quickly at the start and almost achieved the maximum adsorption capacity after 10 days [31]. With the increase in time, microorganisms gradually adapted to TC in the system, and then its biodegradation dominated later. Subsequently, the removal rate of TC decreased with the addition of NOR. The performance of MBRa and MBRb was superior to MBRc, and MBRb showed the best effect on TC removal. The importance of biodegradation on the removal of this antibiotic was also shown [32], since they suggested that the removal of TC was characterized by a rapid adsorption and slow biodegradation process. These systems were operated by having very long SRT and acclimation potential, which might contribute to the degradation process of TC. The removal rate of TC was very high during the whole experiment. Membranes 2020, 10, x FOR PEER REVIEW 6 of 12 The effluent concentration of NOR changed greatly during the whole operation period. At the initial stage of adding NOR, the removal rate of NOR was higher due to the adsorption of NOR by sludge. However, with the prolongation of time, the active sites of sludge were gradually occupied, activated sludge adsorption gradually reached an equilibrium, the removal rate of NOR began to decrease, and the final removal rates remained at 40.36 ± 0.2% of MBRa, 46.46 ± 0.11% of MBRb and 28.65 ± 0.18% of MBRc, P < 0.05, which indicated that the reactors still had a certain removal ability of NOR. Kummerer et al. [33] examined the effects of broad-spectrum antibiotics on microorganisms in activated sludge. He found that only a small fraction of bacteria in sludge were affected. This was because the main removal of the quinolone antibiotics in MBRs was through the adsorption and biodegradation of activated sludge, and mainly based on the adsorption of sludge [34]. The removal rate of NOR was much lower than TC, which was likely because the fact that the adapted sludge had been saturated with TC and thus decreased their adsorption potentials.
Membrane Fouling Behavior during Continuous Operation
As an important indicator of membrane fouling propensity, the development of the transmembrane pressure (TMP) was monitored during the operating period. The time course changes of TMP in each MBRs were illustrated in Figure 4. Physical cleaning of the membranes (manually wiping with a sponge) was performed when TMP exceeded 35 kPa.
As shown in Figure 4, the MBRa had nine-times TMP up to a total of 35 kPa, which was far more than that of MBRb (two times) and MBRc (four times) throughout the operation. It was revealed that the MBRb using fiber bundle bio-carriers could reduce membrane fouling and the membrane fouling rate of MBRa was even more serious than that of MBRc. This finding was consistent with Yang et al. [35], who reported that the bioreactor with suspended carriers (MB-MBR) showed a higher cake layer resistance than conventional MBR (CMBR) due to the presence of a large amount of filamentous bacteria inhabited in suspended solids in MB-MBR, resulting in the membrane fouling rate of MB-MBR about three times that in CMBR. The TMPs of MBRb increased slowly in the first 10 d, followed by a plateau where the TMP stabilized around 8.06 kPa for over 9 d and eventually rose to 35 kPa on day 26. The membrane filtration cycle was about eight times longer than that of MBRa. The operation of another membrane filtration cycle was performed on the MBRb and similar TMP development was observed. This might be due to the fact that fiber bundle biologically thicker biofilm carrier provided a better ability to resist antibiotic impact, creating a more abundant biodiversity and more stable environment, so as to improve the degradation of the membrane fouling agent. Therefore, it was presumed that the MBRb had a better control in alleviating membrane fouling. The effluent concentration of NOR changed greatly during the whole operation period. At the initial stage of adding NOR, the removal rate of NOR was higher due to the adsorption of NOR by sludge. However, with the prolongation of time, the active sites of sludge were gradually occupied, activated sludge adsorption gradually reached an equilibrium, the removal rate of NOR began to decrease, and the final removal rates remained at 40.36 ± 0.2% of MBRa, 46.46 ± 0.11% of MBRb and 28.65 ± 0.18% of MBRc, P < 0.05, which indicated that the reactors still had a certain removal ability of NOR. Kummerer et al. [33] examined the effects of broad-spectrum antibiotics on microorganisms in activated sludge. He found that only a small fraction of bacteria in sludge were affected. This was because the main removal of the quinolone antibiotics in MBRs was through the adsorption and biodegradation of activated sludge, and mainly based on the adsorption of sludge [34]. The removal rate of NOR was much lower than TC, which was likely because the fact that the adapted sludge had been saturated with TC and thus decreased their adsorption potentials.
Membrane Fouling Behavior during Continuous Operation
As an important indicator of membrane fouling propensity, the development of the transmembrane pressure (TMP) was monitored during the operating period. The time course changes of TMP in each MBRs were illustrated in Figure 4. Physical cleaning of the membranes (manually wiping with a sponge) was performed when TMP exceeded 35 kPa.
Microbial Community Dynamics
The activated sludge of properties and microbial community determined the stability of system and performance of treatment. Thus, the microbial community structures of the sludge in the reactor were analyzed.
Microbial Diversity and Richness in the three MBRs
The microbial sludge communities' diversity and richness of MBRs during the operation phase As shown in Figure 4, the MBRa had nine-times TMP up to a total of 35 kPa, which was far more than that of MBRb (two times) and MBRc (four times) throughout the operation. It was revealed that the MBRb using fiber bundle bio-carriers could reduce membrane fouling and the membrane fouling rate of MBRa was even more serious than that of MBRc. This finding was consistent with Yang et al. [35], who reported that the bioreactor with suspended carriers (MB-MBR) showed a higher cake layer resistance than conventional MBR (CMBR) due to the presence of a large amount of filamentous bacteria inhabited in suspended solids in MB-MBR, resulting in the membrane fouling rate of MB-MBR about three times that in CMBR. The TMPs of MBRb increased slowly in the first 10 d, followed by a plateau where the TMP stabilized around 8.06 kPa for over 9 d and eventually rose to 35 kPa on day 26. The membrane filtration cycle was about eight times longer than that of MBRa. The operation of another membrane filtration cycle was performed on the MBRb and similar TMP development was observed. This might be due to the fact that fiber bundle biologically thicker biofilm carrier provided a better ability to resist antibiotic impact, creating a more abundant biodiversity and more stable environment, so as to improve the degradation of the membrane fouling agent. Therefore, it was presumed that the MBRb had a better control in alleviating membrane fouling.
Microbial Community Dynamics
The activated sludge of properties and microbial community determined the stability of system and performance of treatment. Thus, the microbial community structures of the sludge in the reactor were analyzed.
Microbial Diversity and Richness in the Three MBRs
The microbial sludge communities' diversity and richness of MBRs during the operation phase were analyzed by high-throughput sequencing. Good's coverage of each sample was over 0.99, meaning that the obtained sequence libraries covered the microbial diversity of MBRs. As shown in Table 1, the Shannon and Chao1 index values in MBRb were higher than those in the MBRa and MBRc during the entire operation. The Chao1 indexes could reflect the richness of the microbes, and the Shannon indexes could reveal the diversity of microbes [36]. It demonstrated that the thicker fixed biofilm in MBRb was more conducive to develop a stable living environment for various microorganisms. [37,38]. Although the first addition of TC caused a sharp decline in microbial diversity, the richness of the species varied slightly with the extension of exposure time and the addition of NOR, which indicated that the microbial community was no longer as susceptible as the initial one. More simply, the community became more adaptive to antibiotics, which was similar to previous studies [39,40].
Microbial Community Structure Analysis
The microbial community structure of the samples was analyzed in three stages. Sample C represented the activated sludge without adding antibiotics in MBRc, and samples MBRa-1, MBRb-1, MBRc-1, MBRa-2, MBRb-2, and MBRc-2 represented the activated sludge with (1) TC and (2) TC and NOR of the three reactors.
At the phylum level, it revealed that the two predominate phyla were Proteobacteria (70.99%, 52.42%, 49.01%, 37.75%, 57.3%, 55.36% and 51.5%) and Bacteroidetes (13.32%, 38.88%, 30.84%, 37.36%, 30.55%, 22.39% and 33.99%) in MBRa-1, MBRb-1, MBRc-1, MBRa-2, MBRb-2, and MBRc-2, respectively (Figure 5a). Despite the fluctuation, total relative abundance of Proteobacteria and Bacteroidetes in the communities increased dramatically after TC and NOR addition, indicating that members from these predominant lineages largely made up the resistant species proliferated in the MBRs. However, the number of Proteobacteria decreased in phase 2 was smaller to that in the phase 1, meaning that it had resistance to the antibiotics with the increase in operation time. On the contrary, the Acidobacteria was inhibited by the antibiotics and, in the activated sludge after the addition of the TC and NOR, the Acidobacteria gradually disappeared, manifesting that the Acidobacteria could not be adapted to an antibiotic-containing environment. The other two microbial phyla, Actinobacteria and Planctomycetes, seemed to be sensitive to the presence of antibiotics, when NOR was added, the relative abundance of Actinobacteria and Planctomycetes decreased from 2.4%, 13.37% and 3.87%, 17.53% in MBRb-1 and MBRc-1 to 2.16%, 11.33% and 1.05%, 9.91% in MBRb-2 and MBRc-2, respectively, except for MBRa. It was worth noting that Firmicutes in samples MBRb-1 and MBRb-2 was much higher than other MBRs. This demonstrated the Firmicutes was capable of adapting the antibiotics and was favored in the activation of sludge for resisting antibiotics. As previously reported on the microbial communities, Firmicutes had a key part in the process of complex substances [41,42].
Microbial Community Structure Analysis
The microbial community structure of the samples was analyzed in three stages. Sample C represented the activated sludge without adding antibiotics in MBRc, and samples MBRa-1, MBRb-1, MBRc-1, MBRa-2, MBRb-2, and MBRc-2 represented the activated sludge with (1) TC and (2) TC and NOR of the three reactors.
At the phylum level, it revealed that the two predominate phyla were Proteobacteria (70.99%, 52.42%, 49.01%, 37.75%, 57.3%, 55.36% and 51.5%) and Bacteroidetes (13.32%, 38.88%, 30.84%, 37.36%, 30.55%, 22.39% and 33.99%) in MBRa-1, MBRb-1, MBRc-1, MBRa-2, MBRb-2, and MBRc-2, respectively (Figure 5a). Despite the fluctuation, total relative abundance of Proteobacteria and Bacteroidetes in the communities increased dramatically after TC and NOR addition, indicating that members from these predominant lineages largely made up the resistant species proliferated in the MBRs. However, the number of Proteobacteria decreased in phase 2 was smaller to that in the phase 1, meaning that it had resistance to the antibiotics with the increase in operation time. On the contrary, the Acidobacteria was inhibited by the antibiotics and, in the activated sludge after the addition of the TC and NOR, the Acidobacteria gradually disappeared, manifesting that the Acidobacteria could not be adapted to an antibiotic-containing environment. The other two microbial phyla, Actinobacteria and Planctomycetes, seemed to be sensitive to the presence of antibiotics, when NOR was added, the relative abundance of Actinobacteria and Planctomycetes decreased from 2.4%, 13.37% and 3.87%, 17.53% in MBRb-1 and MBRc-1 to 2.16%, 11.33% and 1.05%, 9.91% in MBRb-2 and MBRc-2, respectively, except for MBRa. It was worth noting that Firmicutes in samples MBRb-1 and MBRb-2 was much higher than other MBRs. This demonstrated the Firmicutes was capable of adapting the antibiotics and was favored in the activation of sludge for resisting antibiotics. As previously reported on the microbial communities, Firmicutes had a key part in the process of complex substances [41,42]. The changes in structure and relative abundance of microorganisms on the class level are shown in Figure 5b. The dominant class varied among samples, the two predominating classes were Flavobacteriia (22.01%, 22.16%) and Betaproteobacteria (21.5%, 32.36%) in MBRa-1 and MBRa-2, respectively, Flavobacteriia (19.01%, 28.92%) and Gammaproteobacteria (19.28%, 20.69%) in MBRb-1 and MBRc-2, respectively, Flavobacteriia (27.41%) and Alphaproteobacteria (19.73%) in MBRc-1 and Alphaproteobacteria (22.22%) and Gammaproteobacteria (15.66%) in MBRb-2. Previous results have shown that at higher concentrations of antibiotics, these microbes had a greater proportion of relative abundance, indicating that they had drug-resistance [43,44]. In past studies, Alphaproteobacteria were able to carry on the sulfur metabolism, remove organic matter and nitrogen, which were the main functions of biofilters in maricultural recirculation systems [45] and Betaproteobacteria played a significant role in the removal of nitrogen [46,47]. The abundance of Flavobacteriia and Gammaproteobacteria in reactors fed with wastewater containing antibiotics was significantly higher than those in the P0. Pollet et al. [48] found that Flavobacteriia might be the key actor in the functioning of marine biofilms. Moreover, Li et al. [49] found that the tetracycline-resistant bacteria isolated from the treatment of oxytetracycline production wastewater by a sewage treatment plant were mainly Gammaproteobacteria, followed by Alphaproteobacteria and Betaproteobacteria.
Conclusions
The results revealed that, in the presence of antibiotics, all three MBRs were able to maintain a good removal in COD and NH 4 + -N. TC and NOR were removed through different removal mechanisms; however, MBRb was more advantageous compared to the other two reactors under the same antibiotics level and had better performance on membrane fouling mitigation. In addition, the existence of antibiotics resulted in a significant decrease in the microbial diversity and the microbial richness, which showed some obvious changes at different stages in different MBRs. Flavobacteriia, Firmicutes and Azoarcus, regarded as drug-resistant bacteria, might play a crucial part in the removal of antibiotics. In addition, three different levels (phylum, class and genus) of the dynamics of microbial community had a great change, which included the accumulation of resistant microorganisms and the gradual reduction in or disappearance of other microorganisms under antibiotic pressure.
Conflicts of Interest:
The authors declare no conflict of interest. | 6,007.4 | 2020-10-01T00:00:00.000 | [
"Engineering"
] |
Inactivation of NPC1L1 Causes Multiple Lipid Transport Defects and Protects against Diet-induced Hypercholesterolemia*
NPC1L1, a recently identified relative of Niemann-Pick C1, was characterized to determine its subcellular location and potential function(s). NPC1L1 was highly expressed in HepG2 cells and localized in a subcellular vesicular compartment rich in the small GTPase Rab5. mRNA expression profiling revealed significant differences between mouse and man with highest expression found in human liver and significant expression in the small intestine. In contrast, liver expression in mouse was extremely low with mouse small intestine exhibiting the highest NPC1L1 expression. A mouse knock-out model of NPC1L1 was generated and revealed that mice lacking a functional NPC1L1 have multiple lipid transport defects. Surprisingly, lack of NPC1L1 exerts a protective effect against diet-induced hyperlipidemia. Further characterization of cell lines generated from wild-type and knock-out mice revealed that in contrast to wild-type cells, NPC1L1 cells exhibit aberrant plasma membrane uptake and subsequent transport of various lipids, including cholesterol and sphingolipids. Furthermore, lack of NPC1L1 activity causes a deregulation of caveolin transport and localization, suggesting that the observed lipid transport defects may be the indirect result of an inability of NPC1L1 null cells to properly target and/or regulate caveolin expression.
From the Departments of ‡Human Genetics and §Pediatrics, Mount Sinai School of Medicine, New York, New York 10029 NPC1L1, a recently identified relative of Niemann-Pick C1, was characterized to determine its subcellular location and potential function(s). NPC1L1 was highly expressed in HepG2 cells and localized in a subcellular vesicular compartment rich in the small GTPase Rab5. mRNA expression profiling revealed significant differences between mouse and man with highest expression found in human liver and significant expression in the small intestine. In contrast, liver expression in mouse was extremely low with mouse small intestine exhibiting the highest NPC1L1 expression. A mouse knock-out model of NPC1L1 was generated and revealed that mice lacking a functional NPC1L1 have multiple lipid transport defects. Surprisingly, lack of NPC1L1 exerts a protective effect against diet-induced hyperlipidemia. Further characterization of cell lines generated from wildtype and knock-out mice revealed that in contrast to wild-type cells, NPC1L1 cells exhibit aberrant plasma membrane uptake and subsequent transport of various lipids, including cholesterol and sphingolipids. Furthermore, lack of NPC1L1 activity causes a deregulation of caveolin transport and localization, suggesting that the observed lipid transport defects may be the indirect result of an inability of NPC1L1 null cells to properly target and/or regulate caveolin expression.
Niemann Pick C1-like 1 protein (NPC1L1) 1 was previously identified based on its high degree of similarity, 42% amino acid identity and 51% similarity to the polytopic, late endosome-resident protein, NPC1. Both possess a putative sterolsensing domain, suggesting roles in sterol/lipid transport (1), and they also have an amino-terminal "NPC1 domain" (2). Based on this homology and preliminary data, we hypothesized that NPC1L1 has a lipid permease function similar to that of NPC1 (3). In contrast, however, the two proteins have variant targeting signals and thus are predicted to function similarly but at different intracellular locations.
To gain a further understanding of the function of this family of proteins, we have carried out cell and molecular studies to determine the location and tissue expression of NPC1L1. In addition, since no known disorders map at 7p13, the chromosomal location of human NPC1L1 (1), we have generated a mouse knock-out of NPC1L1. Our results are in contrast to a published report suggesting that NPC1L1 resides at the plasma membrane (4) and indicate that this protein is predominantly intracellular and colocalizes with the small GTPase Rab5. In addition, the expression profile of human NPC1L1 shows this protein to be highly enriched in liver. Finally, inactivation of NPC1L1 leads to multiple lipid transport defects including cholesterol and sphingolipids, suggesting that NPC1L1 plays a critical role in lipid homeostasis and transport in support of our original hypothesis.
MATERIALS AND METHODS
Tissue Culture, Transfection, and Immunofluorescence Studies-All cells, including COS7, HepG2, and Caco-2 cells, were obtained from ATCC (Manassas, VA). Cells were maintained at 37°C in a humidified environment with 5% CO 2 in Dulbecco's modified Eagle's medium containing 2 mM glutamine, 10% fetal bovine serum, and 10 g/ml gentamicin. HepG2 cells and Caco-2 cells were grown on glass coverslips for 2 days before staining. All other cells were grown overnight before transfection using Lipofectamine and Plus reagents (Invitrogen), according to the manufacturer's instructions. Unless indicated otherwise, cells were fixed using methanol at 4°C for 6 min and then processed for indirect immunofluorescence staining using the appropriate anti-IgG secondary antibodies that were tagged with either Alexa 488 or Alexa 594 (Molecular Probes).
For coimmunofluorescence with transferrin-Alexa 568, the cells were incubated with 50 g/ml transferrin for 25 min followed by a 15-min chase period. They were subsequently washed, fixed with methanol, and stained as above. Cells were photographed using a Nikon Eclipse microscope equipped with a CCD camera. Images were deconvoluted using the MetaMorph Software package (Universal Imaging).
Antibodies-Monoclonal antibodies for the Golgi markers GS15, GS28, GM130, Vti1b, GS27, and p230 and those for Rab8, calnexin, clathrin, and EEA1 were purchased from Pharmingen. Goat polyclonal antibodies for ABCD3, Rab11, and calnexin and rabbit polyclonal for Rab5A were obtained from Santa Cruz Biotechnology. Transferrin-Alexa 568 and Golgin 97 were from Molecular Probes. The Alexa Fluor 594 labeling kit (Molecular Probes) was used to directly label the affinity-purified NPC1L1 rabbit polyclonal antibody with Alexa 594, enabling it to be used for colocalization of NPC1L1 with other rabbit polyclonal antibody markers.
The MLN64 rabbit polyclonal antibodies were generated against the carboxyl terminus region of MLN64, spanning amino acids 239 -444. The antibodies were purified by affinity chromatography using Affi-Gel resin (Bio-Rad) coupled to the MLN64 polypeptide. The anti-Rab9 polyclonal antibodies were generated and purified in a similar manner.
Generation of Anti-NPC1L1 Polyclonal Antibodies-Histidine-tagged fragments of human NPC1L1 (accession number AY515256) amino acids 416 -635 and amino acids 1276 -1332 were expressed in Esche-richia coli and purified using nickel affinity chromatography. These proteins were used to immunize two rabbits each, and polyclonal antisera, MS42 and MS44, respectively, were collected and purified using a Protein A-Sepharose column (Amersham Biosciences). In addition, a peptide antibody against the sequence GCSRFMAYHKPLKNSQDYTE (aa 1047-1064), Bsn4052, was produced in rabbits by Bio-Synthesis Inc. (Lewisville, TX). Bsn4052 was affinity-purified by conjugating the above peptide to an Affi-Gel resin according to the manufacturer's recommendations (Pierce).
Vector Construction-Monomeric (m) YFP and CFP were generated using eYFP and eCFP plasmids (Clontech) as templates. The L221K and Q69M mutations for mYFP and the L221K mutation in mCFP were created using the megaprimer PCR mutagenesis method (5) and verified by sequencing. To generate mYFP and mCFP fusions with NPC1L1, the stop codon of the human NPC1L1 sequence (GenBank TM accession number AY515256) (1) was removed by PCR amplification, and the resulting cDNA was verified by sequencing and fused to the mYFP and mCFP cDNAs. To introduce a FLAG tag into NPC1L1, an adapter encoding the FLAG tag amino acid sequence DYKDDDDK was ligated in-frame into the NPC1L1 at the unique BsmI restriction site.
Real-time PCR-Human multiple tissue cDNA panels that had been normalized to four different control genes (-actin, ␣-tubulin, G3PDH, phospholipase A2) by the manufacturer (Clontech) and mouse multiple tissue cDNAs normalized for -actin were amplified to detect only the full-length form of NPC1L1. Real-time PCR amplification was achieved using the Lightcycler 2 (Roche Applied Sciences). Data analysis was carried out using the accompanying software (version 4.0). The primers used for amplifying mouse NPC1L1 were: 5Ј-GCTTCTTCCGCAA-GATATACACTCCC-3Ј and 5Ј-GAGGATGCAGCAATAGCCACATAA-GAC-3Ј. The primers used for human NPC1L1 were 5Ј-TATCTTCCCT-GGTTCCTGAACGAC-3Ј and 5Ј-CCGCAGAGCTTCTGTGTAATCC-3Ј. For both, the amplification cycles used were 95°C for 10 s, 58°C for 20 s, and 72°C for 20 s.
Real-time PCR analyses were also carried out for ABCG5 and for the control gene, -actin, essentially as described for NPC1L1, except that different primers and amplification conditions were used. To quantitate -actin, the primers 5Ј-TGGTGGGAATGGGTCAGA-3Ј and 5Ј-AGG-GAGGAAGAGGATGCG-3Ј were used to amplify the mouse sequence, and for human b-actin, the primers were 5Ј-GCATGGGTCAGAAG-GAT-3Ј and 5Ј-CCAATGGTGATGACCTG-3Ј. The amplification cycles used were 95°C for 10 s, 55°C for 20 s ,and 72°C for 20 s for the mouse sequence and 95°C for 10 s, 52°C for 20 s, and 72°C for 25 s for the human samples.
For ABCG5, the primers used to amplify the mouse sequence were 5Ј-TGGATCCAACACCTCTATGCTAAA-3Ј and 5Ј-GGCAGGTTTTCTC-GATGAACTG-3Ј, and those used for the human sequence were 5Ј-TGTGAATCTGTTTCCCGTGCTG-3Ј and 5Ј-TCGGGCAACCTCAG-GATGTAAG-3Ј. The amplification cycles used were 95°C for 10 s, 58°C for 20 s, and 72°C for 10 s for the mouse sequence and 95°C for 10 s, 60°C for 20 s, and 72°C for 12 s for the human samples.
Relative quantitation was carried out using external standards and a linear fit method, and each sample was amplified in three separate experiments. All statistical calculations were obtained using Microsoft Excel.
Plasma Membrane Labeling and Protease Protection Assays-COS7 cells transfected with either FLAG-tagged NPC1L1 or CD32 (6) were labeled for 1 h at 37°C with 100 Ci of [ 35 S]Met/[ 35 S]Cys in cell medium deficient in these amino acids. Following a 2-h chase period, cells were removed and split equally into two samples. 2 g of anti-FLAG or anti-CD32 antibodies were added to half the samples and incubated on a rotating mixer at 4°C for 30 min. Cells were washed twice with cold phosphate-buffered saline, and all samples were lysed in 500 l of lysis buffer (NPC1L1, 100 mM sodium phosphate, pH 7.5, 150 mM NaCl, 2 mM EDTA, 1% IGEPAL, 0.01% SDS; CD32, 50 mM Tris, pH 7.4, 120 mM NaCl, 25 mM KCl, 0.2% Triton X-100) containing protease inhibitor mixture (Sigma) for 1 h and 30 min at 4°C. Lysates were cleared by centrifugation at 20,000 ϫ g for 10 min at 4°C. Samples previously incubated with antibody were transferred to tubes containing 20 l of protein G-agarose beads (Roche Applied Science) and incubated overnight at 4°C. Remaining samples were incubated at 4°C for 1 h with 2 g of anti-FLAG/anti-CD32 antibodies, after which they were transferred to tubes containing protein G-agarose and incubated overnight at 4°C. Samples were washed four times in CD32 lysis buffer and once in NET1 buffer (50 mM Tris, pH 7.4, 0.5 M NaCl, 1 mM EDTA, 0.1% IGEPAL, 0.25% gelatin, 0.02% sodium azide) and electrophoresed through a 4 -20% bis-tris NuPAGE gel (Invitrogen) using the MOPS buffer system, until adequate separation was achieved. Gels were fixed in a solution of 10% acetic acid, 20% methanol for 10 min and immersed in Amplify solution (Amersham Biosciences) for 15 min before drying and exposing to film.
For protease protection assays, HepG2 cells were plated in 100-mm dishes and grown overnight. The assay was carried out essentially as described (7). Briefly, cells were washed twice with phosphate-buffered saline, and plasma membrane proteins were biotinylated for 15 min on ice using 1 mg/ml N-hydroxysuccinimide (NHS)-biotin (Pierce). Cells were washed as above to remove unreacted biotin. Half of the dishes were then treated with 200 g/ml trypsin on ice for 30 min. Cells were washed three times with growth medium containing fetal calf serum to inactivate the trypsin and subsequently lysed in the presence of protease inhibitors as above. Samples were processed for immunoblotting as above and probed either with the Bsn4052 anti-NPC1L1 antibody or with streptavidin-HRP (Vector laboratories) to detect biotinylated proteins.
Generation of NPC1L1 Knock-out Mice-The genomic databases for bacterial artificial chromosomes containing the mouse genomic sequence were searched, and one clone that contained the mouse NPC1L1 promoter and entire coding region was identified (RP23-64P22 from a C57BL6/J mouse; accession number AC079435). A plasmid-based construct was engineered to contain nucleotides 84689 -96003 spanning the promoter region to intron 6. The gene was disrupted at the unique AfeI restriction enzyme site in exon 2 (at 91263) by insertion of a PGK-neo cassette in an antisense direction. This disrupts the coding sequence after cDNA nucleotide 601; thus, the expression of all alternatively spliced forms of the gene is abrogated.
Homologous recombination using C57BL6 ES cells (Taconic, Germantown, NY) was carried out by Cell and Molecular Technologies (Phillipsburg, NJ). About 150 neo-resistant ES clones were obtained, 4 of which were correctly targeted by homologous recombination. These were identified by PCR screening using two sets of primers, each containing one primer outside the NPC1L1 targeting cassette and one within the neomycin gene hybrid.
Chimeric mice were created by injecting knock-out clone 13 C57BL6 ES cells into blastocysts that were then implanted into pseudopregnant BALB/c mice. Chimeric males were identified by coat color and one male that gave almost 100% germ-line transmission of ES cell-derived material was crossed with wild-type C57BL6 females.
Animal Care-All mice were housed in the Mount Sinai animal care facility according to protocols approved by the Institutional Animal Care and Use Committee. For colony maintenance, the mice were given a regular chow diet (LabDiet rodent diet 20, PMI Nutritional International, Richmond, IN) and water ad libitum. For studying the effects of an atherogenic diet, the Paigen high cholesterol, high fat diet (8) was administered (Research Diets, catalog number D12336) and contained 12.5 g% cholesterol, 5 g% sodium cholic acid, and a fat content of 35 kcal%. The matched low fat diet (catalog number D12337) contained 0.3 g% cholesterol, no cholic acid, and a fat content of 10 kcal%.
Generation of SV40-immortalized Cell Lines-Wild-type and NPC1L1 knock-out mice that were 3-6 days old were euthanized in a sterile environment, and liver tissue was removed and minced into 3-4-mm pieces. These were washed in phosphate-buffered saline, transferred to 1 ml of ice-cold 0.25% trypsin/100 mg of tissue, and incubated at 4°C for 16 h. Cells were dispersed by pipetting and then kept in culture until they began to proliferate. Cells were transfected with the pTTKneo plasmid as described previously (9). Clones of SV40transformed cells were picked, and expression of the SV40 antigen was confirmed by immunofluorescence analysis using an anti-SV40 T antigen monoclonal antibody (BD Biosciences).
SRE Dual-Luciferase Reporter and LDL Cholesterol Esterification
Assays-The mouse wild-type (WT) and NPC1L1 knock-out (L1) cell lines were grown in 12-well dishes, and each was cotransfected with 1 g of SRE-Renilla plasmid and 50 ng of pGL3-control luciferase vector (Promega), using 2 l of Lipofectamine and 5 l of Plus reagent. At 5 h after transfection, the medium was replaced, and the cells were incubated overnight in the presence or absence of 2 mg/ml U18666A, medium containing LDL (10% fetal calf serum), LDL-deficient medium, or medium containing 10 g of cholesterol complexed with cyclodextrin. They were then washed with phosphate-buffered saline and processed for analysis using the Dual-Luciferase assay kit as recommended (Promega) to measure SRE promoter induction of Renilla expression. The Renilla values were normalized to the control luciferase activity measurements to compensate for variations in cell state and transfection efficiency between wells. All measurements were carried out in triplicate. LDL cholesterol esterification was carried out essentially as described previously (9).
Cholesterol Uptake Assays-Cholesterol uptake was carried out as follows. [ 3 H]Cholesterol was solubilized using cyclodextrin essentially as described (10) NBD Cholesterol and NBD LacCer Uptake-The fluorescent sphingolipid NBD lactosylceramide (LacCer) was obtained complexed to bovine serum albumin (Molecular Probes) and incubated with subconfluent cultures in serum-free media for 5-10 min. The fluorescent probe was removed, and fresh medium containing serum was added. Cells were imaged live using a fluorescence microscope equipped with a CCD camera. NBD cholesterol was complexed with cyclodextrin as described above for [ 3 H]cholesterol. The cholesterol-cyclodextrin complex was added to cells as described above for NBD LacCer. Cells were processed and imaged as above.
Plasma Lipid Assays-For plasma lipid assays, mice were given the high and low cholesterol diets for 14 weeks and then fasted for 16 h. They were euthanized using a lethal dose of the anesthetic Avertin, and total body blood was withdrawn from the inferior vena cava. Four male and four female mice were used for each diet. Plasma levels of glucose, total cholesterol, HDL cholesterol, and triglycerides were determined by the clinical chemistry laboratory at the Mount Sinai School of Medicine.
FIG. 1. Tissue distribution of human and mouse NPC1L1. Relative quantitation real-time PCR was used to detect full-length NPC1L1 mRNA transcripts in human (A and B) and mouse (D) normalized cDNA tissue panels. Relative expression values (arbitrary units) were calculated as a percentage of the highest average expression value obtained for each panel. A, in human tissues, NPC1L1 is predominantly expressed in liver with detectable expression in pancreas, kidney, lung, and heart. B, in the gastrointestinal tract, NPC1L1 expression can be detected in the small intestine at 2-4% of the liver expression. C, the expression of human ABCG5 was quantitated for the same gastrointestinal tract panel and liver as in B and appears to mimic that of NPC1L1. D, in mouse tissues, the highest NPC1L1 expression is detected in the small intestine with significant expression in the stomach and muscle, along with detectable expression in lung, heart, brain, testis, and skin at about 1-5% of the expression seen in the small intestine. E, similar to the human tissues, expression of mouse ABCG5 mimics that of mouse NPC1L1 with the exception of liver. F, expression of human NPC1L1 in liver HepG2 cells and in colon-derived Caco-2 cells offer further support for the liver-specific expression of NPC1L1.
NPC1L1 mRNA Is Highest in Human
Liver-To further our functional studies of NPC1L1, we evaluated the tissue distribution of NPC1L1 mRNA in both human and mouse tissues. In human tissues, NPC1L1 is predominantly expressed in liver with detectable levels in lung, heart, brain, pancreas, and kidney, ranging in expression from about 0.5 to 3% of liver expression (Fig. 1A). Since it has been reported that mouse NPC1L1 is predominantly expressed in the small intestine (4), analyses using a human panel of digestive tract tissues were also carried out. Human NPClL1 is expressed in the small intestine at 1-4% of the levels expressed in liver (Fig. 1B), suggesting that there are significant differences between the expression of human and mouse NPC1L1. Interestingly, the expression of human NPC1L1 mirrors that of the ABC phytosterol transporter ABCG5 (Fig. 1C). In contrast, mouse NPC1L1 was not highly expressed in liver but was expressed at high levels in the small intestine and was detectable in lung, heart, brain, testis, skin, and liver with significant expression also detected in muscle and the stomach (Fig. 1D). Similar to the human tissues, expression of the ABCG5 transporter in mouse tissues was highest in liver and small intestine (Fig. 1E).
Further support for the expression of NPC1L1 in human tissues was provided by analyzing the expression of this gene in the colorectal adenocarcinoma cell line Caco-2, which displays characteristics of enterocytes, and in the liver-derived hepato-cellular carcinoma cell line, HepG2. In agreement with the results of the expression profile, human NPC1L1 is expressed at much higher levels in the liver-derived HepG2 cells than in Caco-2 cells (Fig. 1F). Growth of HepG2 cells in the presence of LDL cholesterol causes a slight increase in the expression of this gene (Fig. 1F).
NPC1L1 Localizes to Internal Membranes and Colocalizes with Rab5-Since the mRNA profiling results above indicated that HepG2 and Caco-2 cells express detectable levels of NPC1L1 mRNA, we initially carried out Western blotting analyses using cellular extracts from these cells. In complete agreement with the mRNA analysis results, HepG2 cells express higher levels of NPC1L1 protein than Caco-2 cells (Fig. 2A, Ϫ peptide), and this signal can be completely blocked in the presence of the immunogen peptide ( Fig. 2A, ϩ peptide). Therefore, since HepG2 cells express significant amounts of NPC1L1 protein, we carried out immunofluorescence analysis of endogenous NPC1L1 protein in these cells. Staining with the Bsn4052 antibody revealed a perinuclear, vesicular localization, and this staining was abolished in the presence of the competing peptide immunogen (Fig. 2, B and C). Expression of FLAG-tagged NPC1L1 in COS7 cells (Fig. 2D) and NPC1L1 fused to mYFP in Caco-2 cells (Fig. 2E) provided further confirmation of the subcellular location of NPC1L1. As can be clearly seen in the HepG2 endogenous staining and in the FLAG-tagged NPC1L1 in COS7 cells, the NPC1L1 protein FIG. 2. Anti-NPC1L1 antibodies detect a ϳ150-kDa protein on Western blots and label intracellular vesicles. A, Western blot analysis of NPC1L1 using HepG2 and Caco-2 cell extracts. In support of the mRNA expression analysis (Fig. 1F), HepG2 cells express more protein than Caco-2 cells. Incubation of the Bsn4052 anti-NPC1L1 antibody with the NPC1L1 peptide used for immunization (ϩ lanes) completely blocks the NPC1L1 signal. B, immunofluorescence detection of endogenous NPC1L1 in HepG2 cells, using the Bsn4052 antibody. Large intracellular vesicles are labeled with this antibody, and this signal can be completely blocked by preincubating with the peptide antigen (C). D, immunofluorescence detection of FLAG-tagged NPC1L1 in transiently transfected COS7 cells. E, live detection of an NPC1L1-mYFP fusion protein in transiently transfected Caco-2 cells. Scale bar, 1 m.
decorates large vesicular structures to give them a beaded appearance (Fig. 2, B and D). Similar results were obtained using antibodies MS42 and MS44 (data not shown).
These results are in an apparent disagreement with a recent suggestion that NPC1L1 resides at the plasma membrane (4). To determine how much of the protein, if any, may be located at the plasma membrane, we carried out a plasma membrane labeling assay in COS7 cells that were transiently transfected with the FLAG-tagged NPC1L1. As shown in Fig. 4A, very little, if any, NPC1L1 can be labeled on the plasma membrane, indicating that the location of this protein is predominantly intracellular, in agreement with our subcellular localization analyses described above. However, to further confirm the lack of NPC1L1 at the plasma membrane, we also carried out a protease protection assay in HepG2 cells. Treatment of these cells with trypsin failed to digest the NPC1L1 protein, indicating that NPC1L1 is not located at the plasma membrane (Fig. 4B). Trypsin digestion, however, was able to significantly decrease biotinylated plasma membrane proteins (Fig. 4B). Taken together, these results indicate that NPC1L1 localizes to internal membranes and co-localizes with Rab5.
Generation of NPC1L1 Null C57BL6 Mice-Since no known human disease resulting from defects in this gene is currently known, we chose to further our studies of NPC1L1 function by generating C57BL6 mice with a disrupted NPC1L1 gene. Chi-meric C57BL6 ES cell/BALBc mice were successfully generated and crossed with C57BL6 females. Homozygous NPC1L1 Ϫ/Ϫ mice were identified by long range PCR amplification to verify that the neomycin/NPC1L1 gene knock-out cassette was correctly inserted by homologous recombination (Fig. 5A). Mice were routinely screened by PCR to determine their genotype (Fig. 5B); the resulting NPC1L1 Ϫ/Ϫ mice were found to breed normally and showed no obvious phenotype when compared with their wild-type NPC1L1 ϩ/ϩ counterparts. This was surprising considering that mice lacking NPC1 are generally sterile and exhibit severe neurodegeneration that leads to death at about 2.5 months of age (11).
NPC1L1 Null Cells Have Multiple Lipid Transport Defects-To further characterize the role of NPC1L1 in lipid transport, mouse fibroblasts were isolated from NPC1L1 ϩ/ϩ (WT) and NPC1L11 Ϫ/Ϫ (L1) mice and were immortalized by expression of the SV40 large T antigen (9). To characterize the response of these cells to changing lipid levels, we constructed vectors in which the expression of firefly luciferase is controlled by a dual SRE (6). Expression of this construct in the WT and L1 cells indicated that the L1 cells have a 10-fold higher SRE expression in the presence of LDL cholesterol (Fig. 6A). This 4. NPC1L1 does not reside at the plasma membranes. A, a plasma membrane labeling assay was carried out to confirm the intracellular location of NPC1L1. The amount of NPC1L1 found at the plasma membrane (PM) is significantly lower than the total amount of NPC1L1 (Total) that can be labeled following cell lysis (Ctr; control immunoprecipitation of NPC1L1). Mw, molecular size marker. B, protease protection assay of endogenous NPC1L1 in HepG2 cells. Plasma membrane-resident proteins were biotinylated as described under "Materials and Methods" prior to treatment with trypsin. Cellular extracts were immunoblotted and probed for NPC1L1 (left panel) or streptavidin to visualize biotinylated proteins (right panel).
FIG. 5.
A, long range PCR was used to amplify the 5Ј and 3Ј regions (as indicated) of the NPC1L1 knock-out gene allele, producing a 9-and 5.5-kb product, respectively. Mw, 1 kb Plus DNA marker set (Invitrogen). B, multiplex PCR products from routine genotype analysis of the NPC1L1 knock-out mice were amplified using one neomycin primer and two NPC1L1 primers flanking the insertion to amplify the 815-and 601-bp mutant and wild-type alleles, respectively, in homozygous knock-out (Ϫ/Ϫ), heterozygote (Ϫ/ϩ), and wild-type (ϩ/ϩ) mice. The molecular weight marker is set as in a.
SRE response was greatly amplified when sterol transport was inhibited with U18666A. However, the 4-fold induction of SRE response in the presence of U18666A was similar between the WT and L1 cells. To determine whether the L1 cells were more sensitive to a lack of LDL cholesterol from the endosomal/ lysosomal system, these cells were transfected with the SREluciferase construct in the presence or absence of LDL cholesterol. In the presence of LDL cholesterol, the L1 cells were able to down-regulate their SRE response (Fig. 6A, L1ϩLDL) when compared with their response in the absence of LDL (Fig. 6A, L1ϪLDL), suggesting that they do not appear to have a block in LDL cholesterol transport. Similarly, they were also able to down-regulate their SRE response in the presence of cholesterol-cyclodextrin (Fig. 6A, L1ϩCD), albeit not as effectively as in the presence of LDL cholesterol, which may reflect a partial inhibition of plasma membrane-derived cholesterol endocytosis (Fig. 7). Cholesterol esterification assays indicated that there was no statistically significant difference between WT and L1 FIG. 7. Lack of NPC1L1 results in impaired uptake of multiple lipids, as shown from transport studies using WT and L1 mouse cells. A, WT and L1 cells were incubated with [ 14 C]cholesterol complexed with cyclodextrin. *, p Ͻ 0.05; **, p Ͻ 0.01. L1 cells exhibit a decrease in the uptake of cholesterol (about 30%) when compared with WT cells. *, p Ͻ 0.05; **, p Ͻ 0.005. Uptake of the fluorescent lipid analogues NBD cholesterol complexed with methyl--cyclodextrin (B) and NBD LacCer complexed to bovine serum albumin (C) by WT and L1 cells. Cholesterol and LacCer decorate the plasma membrane of both WT and L1 cells initially; however, at later time points, the two lipids are found predominantly in the Golgi of WT cells in contrast to L1 cells that are unable to process these lipids and retain them in punctate structures throughout the cytosol. cells in their ability to transport and esterify LDL-derived cholesterol from their endosomal/lysosomal system (Fig. 6B). These results indicate that the higher level of SRE response seen in the L1 cells is not due to an inability to transport endosome-derived LDL cholesterol and may reflect changes in the SREBP processing machinery due to other lipid changes in these cells. This hypothesis is currently under investigation.
To evaluate the extent of this potential transport defect, we next determined whether the absorption and endocytosis of lipids at the plasma membrane was also altered. To assess cholesterol influx rates, radiolabeled cholesterol was incubated with cells for 0 -40 min. Both cell lines exhibited saturable uptake, but transport into the L1 cells was reduced by 30% (Fig. 7A). Next, cells were labeled as above with a fluorescent cholesterol analog and chased for various lengths of time. Initially, cholesterol decorates the plasma membrane of both WT and L1 cells in a punctate manner (Fig. 7B). However, by 180 min, in WT cells, NBD cholesterol was localized at a single intracellular site, presumably the Golgi apparatus, whereas in the L1 cells, cholesterol accumulated in multiple intracellular pools (Fig. 7B). It should be noted that transport of NBD cholesterol might not occur in an identical manner to native cholesterol in some systems (12); however, these results support the conclusions derived from the native cholesterol absorption studies shown above (Fig. 7A). Interestingly, incubation with the fluorescent sphingolipid NBD-lactosylceramide indicated that in addition to differences in the transport of cholesterol, L1 cells also have defects in sphingolipid transport. As shown in Fig. 7C, following 15 min of chase, NBD-lactosylceramide localized to the Golgi apparatus of WT cells, and this localization was complete by 40 min (Fig. 7C). However, in L1 cells, NBD-lactosylceramide was trapped in intracellular vesicular structures and did not reach the Golgi complex even after 120 min of chase (Fig. 7C). Intriguingly, this phenotype has recently been described in NPC1-defective cells (13), lending further support to the notion that NPC1 and NPC1L1 may perform similar functions.
Loss of NPC1L1 Affects Caveolin Endocytosis-The differences in lipid endocytosis between WT and L1 cells suggested that the lack of NPC1L1 activity causes a generalized lipid transport block that may involve deregulation of caveolae formation and/or internalization (14). Expression of a mYFP-caveolin construct showed that in WT cells, caveolin localizes in a perinuclear Golgi area and in ring structures located close to the plasma membrane (15,16) (Fig. 8A, WT). In striking contrast, the caveolin in L1 cells appears to be trapped at the plasma membrane (Fig. 8A, L1), suggesting that lack of NPC1L1 activity causes its aberrant trafficking or mislocalization. To determine whether this increased plasma membrane localization of caveolin in the L1 cells is due to a lack of NPC1L1 activity, these cells were transfected as above with the YFP-caveolin construct and a construct encoding NPC1L1 fused to CFP. L1 cells transfected with NPC1L1 no longer exhibited the plasma membrane caveolin phenotype and appeared similar to the WT cells (Fig. 8B), further suggesting that caveolin mislocalization is affected by a lack of NPC1L1 activity. The inability of L1 cells to endocytose caveolae may partially explain their multiple lipid transport defects. To determine whether NPC1L1 is active in caveolae, we carried out co-localization studies between mYFP-caveolin and NPC1L1-mCFP. No significant co-localization between the two proteins was detected (data not shown), suggesting that the effects seen in L1 cells are not a direct effect of the lack of NPC1L1 activity in caveolae.
NPC1L1 Null Mice Are Protected from Diet-induced Hyperlipidemia-To further evaluate the role of NPC1L1 in lipid transport and/or metabolism, we placed NPC1L1 ϩ/ϩ and NPC1L1 Ϫ/Ϫ mice on a high cholesterol diet for 14 weeks. When serum lipid levels from these mice were evaluated, no significant differences were observed between NPC1L1 ϩ/ϩ and NPC1L1 Ϫ/Ϫ mice on normal low cholesterol diet (Fig. 9). As expected, WT mice on the high fat diet exhibited an increase in total cholesterol and LDL cholesterol and a decrease in their triglycerides, whereas HDL cholesterol levels were similar to those of animals kept on the low fat diet (Fig. 9). However, the NPC1L1 Ϫ/Ϫ mice given a high fat diet showed no elevation in total and LDL cholesterol and in fact showed a significant decrease in total cholesterol (Fig. 9). These animals had a decrease in HDL levels and had similar triglyceride levels to mice kept on the low fat diet (Fig. 9). In addition, NPC1L1 Ϫ/Ϫ mice on the high fat diet had a significant decrease in plasma glucose when compared with NPC1L1 ϩ/ϩ mice, which has a small but significant increase in plasma glucose (assayed following overnight fasting; Fig. 9).
Histochemical analysis of liver tissues from these animals showed that NPC1L1 ϩ/ϩ mice on the high fat diet had larger, fat-laden livers, whereas livers from the knock-out mice were normal but smaller than the WT high fat livers, indicating that these animals resisted the diet-induced fatty liver (Fig. 10A). Liver sections from NPC1L1 ϩ/ϩ and NPC1L1 Ϫ/Ϫ mice confirmed the lipid-laden status of the NPC1L1 ϩ/ϩ livers and the resistance of NPC1L1 Ϫ/Ϫ animals to this diet-induced lipid accumulation (Fig. 10B). Also, gall bladders from WT and NPC1L1 Ϫ/Ϫ mice on the high fat diet were dramatically different with NPC1L1 ϩ/ϩ gall bladder tissues, showing obvious signs of lipid-induced cholestasis that were absent in the NPC1L1 Ϫ/Ϫ mouse (Fig. 10C). DISCUSSION In these studies, we have extended our characterization of NPC1L1 function by determining its subcellular location and by generating an NPC1L1 null mouse by homologous recombination. The NPC1L1 protein co-localizes predominantly with the small GTPase Rab5, in contrast to a recent report suggesting that NPC1L1 resides at the plasma membrane (4). Knowledge of the correct NPC1L1 location is critical in providing clues as to the potential function(s) of this protein. Thus, subcellular localization studies, using endogenously expressed NPC1L1 in HepG2 cells, were carried out. The Rab5 co-local- ization of this protein was consistently observed in these studies using a number of different polyclonal anti-NPC1L1 antibodies. To further confirm that NPC1L1 does not reside at the plasma membrane, labeling studies were carried out to quantify the amount of NPC1L1 protein transported to the plasma membrane. The results of these labeling studies indicate that less than 5% of the protein is found at the plasma membrane, most probably representing mislocalized protein. In addition, the lack of NPC1L1 protein at the plasma membrane was confirmed by a protease protection study using endogenous expression of NPC1L1 in HepG2 cells.
The expression profile of human NPC1L1 was similar to the one that we reported previously (1), with the highest expression observed in liver. In contrast, mouse NPC1L1 showed the highest expression in the small intestine with minimal liver expression. It has been suggested that in mouse, NPC1L1 expression is confined to the small intestine, and thus, the function of this protein is to regulate cholesterol absorption at that site (4). Our results, however, suggest that NPC1L1 may have a role in other tissues such as pancreas and kidney and has lower expression in lung and heart. In contrast to the mouse expression pattern, as mentioned above, human NPC1L1 is predominantly expressed in liver, whereas the small intestine expression is only about 2-4% of that found in the liver. Thus, NPC1L1 does not function solely in the small intestine.
Generation of a mouse knock-out of NPC1L1 yielded unexpected results. These mice appeared to be phenotypically normal and did not exhibit any of the symptoms of the NPC1 null mice. By utilizing cell lines established from WT and NPC1L1 null mice, however, our studies have revealed marked defects in the transport of a number of lipids including cholesterol and sphingolipids. Interestingly, the sphingolipid transport phenotype was indistinguishable from that recently described for NPC1-deficient cells and cells from patients with sphingolipidoses (13). Both the uptake of cholesterol and sphingolipids by NPC1L1 null cells appeared to be inhibited at an endosomal step that prevented these lipids from reaching the Golgi apparatus. Intriguingly, a recent study has demonstrated that interaction of cholesterol with sphingolipids such as sphingosine affects intestinal cholesterol absorption (17). To further characterize this defect, we examined the movement of caveolin in these cells. Caveolin internalization is inhibited in the NPC1L1 null cells, suggesting that NPC1L1 may affect lipid transport by interfering with and/or regulating caveolin movement. Such inhibition of caveolin internalization has recently been shown FIG. 9. The C57BL6 NPC1L1 knockout mice show marked resistance to hypercholesterolemia when fed a high cholesterol diet. The Paigen atherogenic diet was given to NPC1L1 ϩ/ϩ and NPC1L1 Ϫ/Ϫ mice (High); an equal number of mice were maintained on the equivalent low cholesterol diet (Low). After 14 weeks of feeding, plasma assays were carried out for glucose, triglycerides, total cholesterol, and HDL cholesterol; LDL cholesterol was calculated from each fraction.
to lead to increased cholesterol efflux (18). A mechanism in which efflux rather than uptake is increased by plasma membrane caveolin may explain the reduced intestinal cholesterol absorption observed in the NPC1L1 null mice.
Finally, the NPC1L1 null mice were placed on a high cholesterol diet to determine whether an absence of NPC1L1 has an effect on circulating lipid levels. Surprisingly, the knock-out mice were completely protected from the diet-induced hypercholesterolemia found in WT C57BL6 mice, as determined by their plasma lipid levels, liver, and gall bladder morphology and liver histology. These results suggest that NPC1L1 has a function in the transport of multiple lipids and their homeostasis. Inactivation of this protein clearly has a protective effect against diet-induced hypercholesterolemia in these animals FIG. 10. Loss of NPC1L1 expression protects against diet-induced hyperlipidemia. A, livers from NPC1L1 ϩ/ϩ and NPC1L1 Ϫ/Ϫ were paraffin-embedded, sectioned (0.5 mm), and stained with eosin and hematoxylin. Scale bars: top panel, 100 mm; lower panel, 25 mm. The livers from NPC1L1 ϩ/ϩ show a dramatic lipid accumulation under low (top panel) and high (lower panel) magnification in contrast to NPC1L1 Ϫ/Ϫ livers that appear completely normal. B, representative whole liver tissue isolated from animals described in the legend for Fig. 9 show a complete lack of lipid accumulation in contrast to their NPC1L1 ϩ/ϩ counterparts, which exhibit a clear enlargement and lipid accumulation. C, in addition, the gall bladders from these mice indicate that in NPC1L1 ϩ/ϩ , they are cholestatic, whereas NPC1L1 Ϫ/Ϫ mice do not share this phenotype and appear normal. and suggests that NPC1L1 plays a critical role in regulating lipid metabolism. However, the paradoxical observations of aberrant multiple lipid transport and caveolin mislocalization caused by a lack of NPC1L1 activity require further study. Finally, as discussed above, there are significant differences in the mRNA tissue distribution between mouse and man, and thus, any conclusion regarding the exact role of NPC1L1 in lipid metabolism and transport should be appropriately interpreted and will also require further characterization. | 8,695.4 | 2005-04-01T00:00:00.000 | [
"Biology",
"Medicine"
] |
Estimation of Seismic Hazard Potential and Attendant Potential Human Fatalities from a Scenario Earthquake on the Sanchiao Fault in Northern Taiwan
In this article, the seismic hazard potential in northern Taiwan, including Taipei City, New Taipei City, Keelung City and northern Taoyuan areas are estimated in the form of peak ground acceleration, peak ground velocity and Modified Mercalli Intensity as well as to assess attendant potential human fatalities from a scenario earthquake on the Sanchiao active fault in these areas. By using ground motion prediction equation method in a case of Mw6.88 resulting in the ShakeMap patterns of ground motion, showed the areas of PGA above 400 gals are located in the regions inside the yellow lines of the PGA contour map. Furthermore, the areas of PGA greater than 637 gal are located in the northern Bali and the border area of Sinjhuang and Shulin. Likewise, the high PGV area greater than 60 cm/s are located in the border area of Sinjhuang, Taishan and Shulin. In addition, from estimation of potential human fatalities for a scenario earthquake on the Sanchiao active fault, it is noted that potential fatalities increase rapidly in people above age 45. Total fatalities reach a high peak in age groups of 55– 64. Another to pay special attention by Taipei City Government is the number and percentage of fatalities above age 85 are more in Taipei City with values of 419 and 8.54% than New than Taipei City with values of 319 and 5.02%. In addition, it is surprising that the number and percentage of fatalities are 1234 and 9.75%, respectively in Taoyuan City. Overall, the results of this paper will enable both local and central governments in Taiwan to take notice of potential earthquake threat in these areas, as well as to improve decision making with respect to emergency preparedness, response, and recovery activities for earthquakes in northern Taiwan.
Introduction
Taiwan is located on the boundary of the Eurasian continental plate and the Philippine Sea plate, so seismic activity is very frequent. Historically, there were several damaging earthquakes had occurred in northern Taiwan during the last four hundred years. Some of these earthquakes had resulted in heavy loss of human lives, such as 1694 Taipei earthquake, 1867 Keeling earthquake, 1986 Hualien earthquake and 1999 Chi-Chi earthquake. After 2010, the Central Geological Survey (CGS) upgraded the Sanchiao active fault from suspected fault to Category II, the assessment of potential seismic hazards has been more attentive in northern Taiwan, including Taipei City, New Taipei City, Keelung City and northern Taoyuan areas [1]. Accordingly, a high seismic disaster potential due to a damaged earthquake most likely occur on the Sanchiao active fault. Hence, the central and local government needs to put in more efforts on earthquake disaster prevention in these areas to reduce probably earthquake losses.
To effectively assess the potential risk of earthquakes and possible disasters and losses, and apply them to the risk assessment and management of government disaster prevention, the National Center for Research on Earthquake Engineering (NCREE) of Taiwan developed an Earthquake Loss Estimation System (TELES) to promote research on seismic hazard analysis [2]. In addition, some studies estimated potential seismic hazards and assessed potential human fatalities from scenario earthquakes on the corresponding active faults in these areas. Particularly, the site response factor is considerable in their ground motion prediction models in order to obtain more realistic seismic ground motion estimates for assessment of potential seismic hazards [3][4][5][6][7].
Seismic intensity has traditionally been used worldwide as a method for quantifying the shaking pattern and the extent of damage for earthquake [8]. In Taiwan, the intensity scale used by the Central Weather Bureau (CWB) is conducted and depended on the peak ground acceleration. In contrast, the ShakeMap developed by the United States Geological Survey (USGS) provides a means of generating not only peak ground acceleration and velocity maps, but also a Modified Mercalli Intensity (MMI) map [8]. Liu et al., [4] estimated the seismic hazard potential in Taiwan based on ShakeMaps, showed the areas of MMI intensity greater than VIII are located in the Chianan plains. In addition, Liu and Tsai [9] estimated the potential death tolls due to large future earthquakes in Chianan area by using a formula established by Tsai et al, [10] that relate the human fatality rate with age, together with the age distribution of the population that could be affected by scenario earthquakes on the Meishan, Chukou and Hsinhua active faults.
Overall, I first find out the high seismic hazard areas in northern Taiwan in term of PGA, PGV and MMI. Furthermore, I will assess potential death tolls due to a large future earthquake occurring on the Sanchiao active fault. The results of this study will show areas with higher earthquake disaster potential in northern Taiwan. They can serve as critical information for emergency response planning. They will also provide valuable information for site evaluation of critical facilities in high earthquake hazard regions.
The Study Area and Data Used
The area of this study, northern Taiwan covers these jurisdictions of Taipei City, New Taipei City, Keelung City and the northern Taoyuan City (Figure 1). The Taipei city and the suburbs of a typical basin, the surrounding terrain with southeast of many hills, northeast more mountains, the northwest is flat, the west of the Danshuei river. Overall, the terrain dipped from north to south, altitude between 20 meters to 1,100 meters. The exposed formations in Taipei City are dominated by sedimentary rock, and the Datun volcano complex in the northwest is the eruption of the andesite flow and Tuff breccia. The alluvial layer is distributed in the Taipei Basin, the river channel and the coastal area. The Taipei metropolitan area is centered on the flat-terrain Taipei Basin, which gradually spreads to hilly areas, volcanic clusters and terraces around, and is filled with Late Pleistocene and Holocene alluvial layers. The flat ground formed by these unsolid sediments is the focus for the development of the Taipei metropolitan area [11]. New Taipei City is located around Taipei City and Keelung City, forming a large Taipei metropolitan area, living together, and with Taoyuan City, Ilan county border. New Taipei City is 68.4 km long in the east-west direction, with a length of 69.1 km in the north-south direction. The city is also facing the sea on the north and east sides, along the boundary with Ilan County in southern and Taoyuan City in western. The total length of the coastline is more than 120 km. The terrain of the New Taipei City is composed of four main terrains, such as Taipei Basin, Datun Volcano Group, Linkou Tableland and alpine hills. The northern part is the volcanic terrain of Datun Mountain, the eastern and southern mountains are the mountainous and hilly terrain of the Snowy Mountains, and the Linkou in the southwest is the terrain of Tableland. The area of the Banciao, Sanchong and Sinjhuang Districts, located in the western part of the Taipei Basin, belongs to the alluvial distribution. [12].
Furthermore, Taoyuan City has 13 jurisdiction districts with a total population of 2,054,260 [13]. The numbers and names of 13 jurisdiction districts are as follows: 1 Lujhu, 2 Gueishan, 3 Taoyuan, 4 Bade, 5 Dasi, 6 Fusing, 7 Dayuan, 8 Jhongli, 9 Pingjhen, 10 Longtan, 11 Guanyin, 12 Sinwu, and 13 Yangmei. Topographic map of the northern Taiwan and these administrative districts as well as the Sanchiao active fault (mapped by the Taiwan CGS) [1] (CGS, 2014) are also shown in Figure 1. The administrative districts of high population density between 20,000 and 41,000 per km 2 can be seen in Songshan, Datong, Wanhua, Jhongjheng, Daan, Sinyi, Lujhou, Sanchong, Sinjhuang, Yonghe, Jhonghe, and Banciao districts, all located in Taipei basin. Areas of high population density between 10,000 and 20,000 per km 2 can be seen in Jhongshan, Renai and Taoyuan districts. The major active structure of the Taipei Domain is the Shanchiao fault distributes in the northwestern of Taipei area, which separates the Taipei Basin and the Linkou Tableland. The Sanchiao active fault belongs to Type II, namely late Pleistocene active fault [1]. The observation of numerous triangular facets along the eastern foothills of the Linkou Tableland led to the discovery of the fault many decades ago [14]. NW-SE extension across the Taipei Domain is concentrated on one principal normal fault, across which the long-term rate of extension appears to be at least 1 mm/yr. Motion across this structure, the Shanchiao fault, has been producing the Taipei Basin half graben for the past few hundred thousand years. Seismic slip on the fault may have produced a marine incursion into the Taipei Basin in 1694. History records a very interesting occurrence that is quite relevant to understand the relevance of the Shanchiao fault to seismic hazard assessment. In 1694, historical documents indicate an abrupt subsidence in the Taipei region, with the formation of a brackish water lake that inundated at least a third of the basin [14,15], Apparently, Taipei area has high seismic hazard potential. Not only population increase, but also the slow rebuilding of old buildings, a giant earthquake is likely to cause severe damages. Hence, effective earthquake disaster prevention measures in the metropolitan areas will be required in order to reduce future earthquake loss [16][17][18][19].
The Sanchiao fault is a normal fault with a length of 34 km, divided into two segments: The northern section ranged southward from Jinshan District of New Taipei City to Beitou District of Taipei City with a length of 21 km. The southern section ranged southward from the Beitou District of Taipei City to Shulin District of New Taipei City with a length of 13 km. [1]. The estimated magnitude value for Sanchiao fault according the empirical relationships between the magnitude and rupture length of fault developed by Wells and Coppersmith [20], would be Mw6.88 corresponding to a fault length of 34 km. Furthermore, based on the information from TELES developed by the NCREE [2] and CGS [1], the focal depth of the scenario earthquakes on Sanchiao fault was assumed to be 10km. Accordingly, Mw6.88 will use to estimate the PGA, PGV and MMI and attendant potential human fatalities in northern Taiwan.
In addition, the site response factor at each grid is as the site effect parameter included in the ground motion prediction model. These predictive relationships are obtained by using the Taiwan Strong Motion Instrumentation Program (TSMIP) network data operated by the CWB of Taiwan to estimate peak ground motion at all grid points [6, 21, and 22]. These numerous high-quality instrumental recordings of TSMIP provide an excellent database for making various earthquake engineering and seismological studies. [4,5,23].
Maximum Ground Motion Parameters
Attenuation relationships, or "Ground Motion Prediction Equations (GMPEs)", provide an efficient means for predicting the level of ground shaking at any given location, and for use in seismic hazard analyses. An attenuation relationship is a mathematical equation that relates PGA and PGV to a number of seismological parameters, such as the earthquake source, the wave propagation path between the source and the site, and the site condition. In this study, to obtain ShakeMap, I use the attenuation relationship provided by Liu and Tsai [6,22] to calculate the PGA and PGV. Furthermore, an MMI map also has uses in combination by PGA and PGV. It makes easier to relate the recorded ground motions to the shaking intensity and attendant damage by using the MMI map [8].
The maximum ground motion parameters inside a block provide a means to assess the potential earthquake hazard in a region. [9] At first, I use these predictive relationship of Liu and Tsai [6] to estimate PGA and PGV for each grid point with a block size of 0.01° × 0.01° (or roughly 1 km × 1 km). In this step, the Sanchiao active fault with a length of 34 km was used as a line source to calculate the seismic ground motion. Next, to correct the amplitude at that location using a site response factor determined by Liu and Tsai [6,22], as shown in Figures 3 and 4. Examination of the residuals, site response factor, for sites with qualitative soil categories is a useful method for sets of records. The site response factor r, is defined as the difference between the logarithms of the observed and the predicted ground motion. The site amplification values can be calculated from exp (r) [6]. Finally, I combine above results with the estimated PGA and PGV into MMI maps.
In this study, three levels of ground shaking from the Taiwan intensity scale used by the Central Weather Bureau of Taiwan (CWBI) and MMI intensity scales are considered to be of interest: CWBI V represents a threshold for "minor damage", and CWBI VI and CWBI VII the thresholds for "moderate damage" and "severe damage", respectively. For the MMI intensity scale, MMI VI, MMI VII and MMI VIII represent the thresholds for "light", "moderate" and "heavy" damage, respectively. The CWBI and MMI scale are given in Tables 2 (URL http://www.cwb.gov.tw/ in/seismic/quake preparedness.htm) and 3 (URL http://earthquake.usgs.gov/eqcenter/shakemap/background.p hp), respectively.
Assessment of Human Fatality
Human safety is a primary goal of most modern earthquake protection programs. It is necessary to be an effective earthquake protection program to include reliable estimation of life loss in future earthquakes. However, document including the data of fatalities in past earthquakes are relatively rare [10,24]. Tsai et al., [10] made a correlation between age and the human fatality rate caused by the 1999 Chi-Chi earthquake in Taiwan. Their results showed a clear age dependence of the fatality rate was observed independently based on demographic data from the two hardest-hit Nantou and Taichung counties by the Chi-Chi earthquake. The empirical data sets for both counties show nearly identical behavior and can be represented by almost the same regression formula. Overall, the estimation of total human fatalities in individual townships located inside the seismic intensity greater than 250 gals can be made by using the following equation [7,9,10,19,25]: Where Y% is the age-group fatality rate in percentage, and X represents age.
The age dependence of human fatality rate used in above equation to calculate the number of fatalities is conducted from the Chi-Chi earthquake. The fatality rate model in this study should be more suitable for night time because the Chi-Chi earthquake occurred at midnight, almost all residents were at home. The building collapse became the most dominant cause of fatalities [10]. The situation was consistent with the study result of Pai et al., that the primary cause of death of the victims of the Chi-Chi earthquake was structural failure and the building types [26]. On the other hand, the corresponding fatality rate should be reduced due to a better building quality is expected for building code revisions after 1999.
Maximum Ground Motion Parameters
At first, to contour the ShakeMaps, I use a magnitude value of Mw6.88 to estimate the maximum ground motions at each grid point of the study area. Figure 5 shows the PGA ShakeMap for an Mw6.88 scenario earthquake on the Sanchiao active fault in northern Taiwan. Locations of the 12 administrative districts of Taipei City, 29 administrative districts of the New Taipei City, 7 administrative districts of Keelung City and 7 administrative districts of northern Taoyuan as well as Sanchiao active fault are also shown. The results reveal that high PGA areas greater than 400 gals, corresponding to CWB intensity greater than VII (referred to Table 2), as shown in the regions inside the yellow lines in Figure 5 are located in the following regions: Eastern and southern Beitou, Shihlin, northern Neihu, Jhongshan, Songshan, Datong, Wanhua, Jhongjheng, western Daan and northwestern Sinyi in the Taipei City. Similarly, high PGA areas greater than 400 gals are also located in southern Shihmen, southern Sanjhih, western Danshuei, Bali, northeastern Lujhou, northern Wugu, Linkou, eastern and southern Sanchong, Sinjhuang, southern Taishan, northern Yonghe, Jhonghe, Banciao, northeastern Tucheng, northern Shulin, Jinshan, western Wanli and northwestern Sijhih in the New Taipei City as well as eastern Lujhu, Gueishan and northeastern Taoyuan in the Taoyuan City. Furthermore, the areas of PGA above 500 gals are as shown in the regions filled with purple in Figure 5. The high PGA areas greater than 637 gal, corresponding to MMI intensity greater than IX (referred to Table 3), are located in the northern Bali and the border area of Sinjhuang and Shulin. Similarly, the PGV ShakeMap is shown in Figure 6. It can be seen that the areal patterns of high PGV greater than 31 cm/s, corresponding to MMI intensity greater than VIII (referred to Table 3), are similar to that of the PGA. Furthermore, the high PGV areas greater than 60 cm/s, corresponding to MMI intensity greater than IX, are located in the border area of Sinjhuang, Taishan and Shulin.
In addition to CWB intensity of Taiwan, the MMI is widely used all over the world to represent the level of ground shaking following a damaging earthquake [8]. Hence, I obtain an MMI intensity map, based on a combination of estimated maximum value for PGA and PGV, as shown in Figure 7. It can be seen that the patterns of high MMI greater than VIII, are similar to the contour pattern of the PGV greater than 31 cm/s as shown in Figure 6. In summary, the ShapeMaps for PGA, PGV and MMI, respectively shown in Figures 5-7 can provide critical information to assess potential earthquake hazards in northern Taiwan.
From Figures 2 to 7 mentioned above, I can find the following features: (1) The areas with PGA greater than 400 gals, corresponding to CWB intensity VII and PGV greater than 31 cm/s, corresponding to MMI intensity greater than VIII is due to the combined effects of the large site response factors and Sanchiao fault. For instance, in the border area of Sinjhuang and Shulin can be found the high site amplification factors of 1.65 and 1.82 for PGA and PGV, respectively, as shown in Figures 3 and 4. (2) In addition, not always the highest PGA values distributed in the fault rupture areas due to the effect of low site response factors as shown in Figure 5. For instance, in northwestern Beitou can be found the low site response amplification values of 0.61 and 0.74 for PGA and PGV, respectively, are as shown in Figures 3 and 4. As a result, the Sanchiao fault is not entirely dominated the seismic hazard in term of PGA and PGV in the vicinity of fault as shown in Figures 5 and 6. This study indicated that the site effect plays an important role in seismic hazard assessment results. (3) Not only CWB intensity, but also MMI, is used in this study to represent the level of ground shaking. The MMI intensity maps are based on a combination of estimated maximum value of the PGA and PGV, the patterns of high MMI greater than VIII in Figure 7 are similar to that of the PGV as shown in Figure 6.
Estimation of Potential Human Fatalities from a Scenario Earthquake
Potential human fatality estimates were performed using the empirical function for human fatality rate age dependence for large earthquake scenarios in northern Taiwan obtained by Tsai et al., [10]. For this purpose, I used a scenario earthquake with Mw 6.88 on the Sanchiao fault. The ground motion PGA ShakeMap was calculated for an Mw 6.88 earthquake on the Sanchiao active fault by using the empirical attenuation relationships by Liu and Tsai [6,22], incorporating the site response factor in the predictive model, as shown in Figure 5. Next, the age dependent fatality rate in equation 1 was combined with the impacted population data from the demographic summary [13] to calculate the number of potential fatalities, as shown in Figures 8 to 11 for Taipei City, new Taipei City, Keelung City and Taoyuan City, respectively.
The top panels in Figures 8-11 show the fatality rates for individual age groups. The middle panels in Figures 8-11 show the age distributions for a total population of 2,238,028, 3,403,061, 79,640 and 689,252 in the towns with estimated seismic intensity PGA greater than 250 gals in Taipei City, new Taipei City, Keelung City and Taoyuan City, respectively as shown in Figure 5. These figures indicate that the population numbers start to decrease steadily above age 55. Finally, the bottom panels in Figures 8-11 and Table 4 show the age distributions for 4904, 6360, 161 and 1234 fatalities in Taipei City, new Taipei City, Keelung City and Taoyuan City, respectively. For Taipei City, as shown in Figure 8 (c), the numbers of fatalities stay flat at an average of 93 for people below age 35. The fatalities then increase rapidly for those above age 45 and reach a high peak of 591 in the 60-64 age groups. The number of fatalities then drops rapidly back to 419 for those above age 85. For New Taipei City, as shown in Figure 9 (c), the numbers of fatalities stay flat at an average of 150 for people below age 35. The fatalities then increase rapidly for those above age 45 and reach a high peak of 792 in the 60-64 age groups. The number of fatalities then drops rapidly back to 319 for those above age 85. In Keelung City, as shown in Figure 10 (c), the numbers of fatalities stay flat at an average of 3 for people below age 35. The fatalities then increase rapidly for those above age 45 and reach a high peak of 20 in the 55-59 age groups. The number of fatalities then drops rapidly back to 11 for those above age 85. In Taoyuan City, as shown in Figure 11 (c), the numbers of fatalities stay flat at an average of 32 for people below age 35. The fatalities then increase rapidly for those above age 45 and reach a high peak of 139 in the 55-59 age groups. The number of fatalities then drops rapidly back to 68 for those above age 85. In summary, the earthquake scenarios using Mw 6.88 on the Sanchiao fault to estimate potential human casualties. As a result, from Figure 2 and Figures 8-11 mentioned above, I can find the following features: (1) the fatalities are 4904, 6360, 161 and 1234 in Taipei City, New Taipei City, Keelung City and Taoyuan City, respectively for the Mw 6.88 scenarios earthquake. Although the all number of fatalities are more in New Taipei City than Taipei City. The number of fatalities above age 85 is 419 and 319 in Taipei City and New Taipei City, respectively. It is just the opposite that the number and percentage of fatalities above age 85 are more in Taipei City with values 419 and 8.54% than New than Taipei City with values of 319 and 5.02%. The Taipei City Government should pay more attention in emergency plans for earthquake for those elder people ages above 85. (2) The total number fatalities are 12,659 for the Mw 6.88 scenarios earthquake in northern Taiwan. The structural failure and the building types were the primary cause of death for the victims of the Chi-Chi earthquake. Pai et al. [26] indicated the main cause lies in the difference was the capacity of the different building types to resist strong shaking. When a great earthquake strikes, these old houses are vulnerable to collapse. In spite of building code revisions after 1999, better building quality is expected and corresponding fatality rate should be reduced. Unfortunately, in northern Taiwan, these households whose residences are over 40 years old, including bungalows and 2-3 stories houses. Many of them are still in use in these metropolitan area where population density is above 20,000 per km 2 . Many person concern and worry about the capacity of old buildings to resist strong shaking. In case of a big earthquake, the consequences would be inconceivable. (3) It is not expected that the number and percentage of fatalities are 1234 and 9.75%, respectively in Taoyuan City. However, considering the residents of 885,217 live in Lujhu, Gueishan, Taoyuan and Bade of Taoyuan City. The distances from the above-mentioned regions to Sanchiao fault are no more than 20 km. The higher number of fatalities in Taoyuan City is considered reasonable.
Finally, the results of my study can provide a valuable database for site evaluation of critical facilities in relatively high potential earthquake hazard regions. They also will be useful for land planning. Furthermore, the results will enable both local and central governments in Taiwan to take notice of potential earthquake threat in these areas, as well as to improve decision making with respect to emergency preparedness, response, and recovery activities for earthquakes.
Conclusions
According to above results and discussion, my findings are summarized as follows: (1) From the PGA contour map for an Mw6.88 scenario earthquake on the Sanchiao active fault in northern Taiwan, the results reveal that high PGA areas greater than 400 gals are located in the regions inside the yellow lines as shown in Figure 5. Furthermore, the areas of PGA above 500 gals are as shown in the regions filled with purple in Figure 5. The areas of high PGA greater than 637 gal are located in the northern Bali and the border area of Sinjhuang and Shulin. Similarly, the areal patterns of high PGV greater than 31 cm/s are similar to that of the PGA. In addition, the high PGV area greater than 60 cm/s are located in the border area of Sinjhuang, Taishan and Shulin. The pattern of high MMI greater than VIII, is similar to the contour pattern of the PGV greater than 31 cm/s. In summary, the ShapeMaps shown in Figures 5-7 can provide critical information to assess potential earthquake hazards in northern Taiwan. This study indicated that the site effects play an important role in seismic hazard assessment results. (3) In addition, the potential human fatalities were estimated by assuming a scenario Mw 6.88 earthquake on the Sanchiao active fault in northern Taiwan. As a result, the numbers of fatalities tend to increase rapidly for people above age 45 for four cities. The fatalities reached a high peak in age groups of 60-64 for Taipei City and New Taipei City as well as in age groups of 55-59 for Keelung City and Taoyuan City. Moreover, the fatalities are 4904, 6360, 161 and 1234 in Taipei City, New Taipei City, Keelung City and Taoyuan City, respectively for the scenarios earthquake. The Taipei City Government should pay more attention that the number and percentage of fatalities above age 85 are more in Taipei City with values of 419 and 8.54% than New than Taipei City with values of 319 and 5.02%. (4) It is surprising that the number and percentage of fatalities are 1234 and 9.75%, respectively in Taoyuan City. However, considering the residents of 885,217 live in Lujhu, Gueishan, Taoyuan and Bade of Taoyuan City. The distances from the above-mentioned regions to Sanchiao fault are no more than 20 km. The higher number of fatalities in Taoyuan City is considered reasonable. Finally, the results of this paper will enable both local and central governments in Taiwan to take notice of potential earthquake threat in these areas, as well as to improve decision making with respect to emergency preparedness, response, and recovery activities for earthquakes in northern Taiwan. | 6,360.2 | 2020-01-09T00:00:00.000 | [
"Geology"
] |
Impact of Computerized Accounting Systems on the Quality of Financial Reports in the Banking Sector of Ghana
The ongoing advancement of information technology has affected accounting information systems; PCs become smaller, quicker, simpler to utilize and more affordable prompting the computerization of accounting information systems. This research is therefore designed to examined the impact of computerized accounting systems on quality financial reports of banks in Ghana. The instrument of data collection was the survey method. The study population comprised of all banks listed on the Ghana Stock Exchange. The quantitative research approach was adopted for the study and data processed using Statistical Package for Social Sciences (SPSS) programming version 21. Findings from the study discovered that taking all other autonomous factors at zero, a unit increment in automated computerized accounting system will bring about 0.50 increment in the quality of financial reports of banks. The implication of this study is that, for banks to have quality financial reports efforts must be made to invest in computerized accountings systems so as to improve the speed, practicality, accuracy and relevance of the financial reports of their operations. Keywords : Financial Reports, Banks, Computerized Accounting, Quality Reports, Information Technology DOI: 10.7176/EJBM/12-17-12 Publication date: June 30th 2020
Introduction
Accounting is the basic foundation of any business, large or small proprietors, profit making or non-benefit making associations. Several small businesses do their bookkeeping manually and they are fulfilled. Others might be thinking about utilizing a mechanized framework, since accounting programming is much affordable. Manual and modernized accounting frameworks perform essentially similar procedures, accounting standards and ideas are the equivalent with contrasts lying in the details of the procedure. In spite of the fact that automated accounting framework is costly, its points of interest lie on speed and having the option to store data.
According to Sugut (2012) accountability refers to a condition under which a role holder renders account to another so that judgment may be made about the adequacy of performance. Vance (2015), equate accountability not only to reporting but also to the justification of performance, they continue to describe accountability as the implicit and explicit expectations that anyone may be called upon to justify one's belief, feelings and actions to others. Computerization saves time on transaction hence leading to quality of financial reporting for instance timely, accurate and reliable information can be generated Alfred (2014). As information technologies grow more progressively, the manual accounting systems have become gradually inadequate for decision needs Brecht and Martin, (2013).
Consequently, public and private sector firms for that matter banking industries in both developing and developed economies view computerization as an automobile mechanism to ensure effective and efficient information flow in the recording, processing, and analysis of financial data. Effective and efficient information flow enhances managerial decision-making, thereby increasing the firm's ability to achieve corporate and business strategy objectives Manson, McCartney, and Sherer, (2001).
This study is to evaluate and analyse the influence of computerized accounting systems to the corporate entity profitability and how an organisation can use computerized accounting systems as a strategic mechanism to take competitive advantage in the industry. Also to establish the effect of computerized accounting systems on the quality of financial reports of banks European Journal of Business and Management www.iiste.org ISSN 2222-1905(Paper) ISSN 2222-2839(Online) Vol.12, No.17, 2020 2.0 Review of Literature 2.1 Theoretical Review This section dealt with the theories that were important to the subject of this study. The theories included systems theory, positive accounting theory and resource-based review theory. Kaufmann (2015) developed systems to explain historical development as a dynamic process and was more fully developed by biologist Bertalanffy (2016). Bertalanffy argued that everything is interconnected and therefore, we should study the interconnectedness as a means of understanding the world. The systems theory method of analysis involves, first the deconstruction of what is to be explained that is the phenomenon under consideration, secondly, the formulation of explanation that account for the behaviour of properties of the component separately and finally the synthesis of these explanations into an aggregate understanding of the whole. General systems theory like other innovative frameworks of thought passes through phases of ridicule and neglect. It has benefited, however, from the parallel emergence and rise to importance of computing and information theory. Systems theory is relevant to this study because the methods proposed by the theory is to model complex entities created by multiple interaction of components by abstracting from certain details of structure and component and concentrating on the dynamics that define the characteristics functions, properties and relationships that are internal or external to the system, Computerized Accounting System is a computer based system, which combines accounting principles concepts as well as the concept of information system to record, process, analyse and produce financial information to its users to make economic decisions Gelinas et al, (2005). The illustrative figure below relates the CAS to systems theory since it involves multiple components which interact to generate usable results these are input, processing storage, users and output.
Computerised Accounting Systems
A computerized accounting system involves the computerization of accounting information systems which is established in order to facilitate decision making Manson, McCartney, and Sherer, (2001). These are associated with number of benefits like speed of carrying out routine transactions, timeliness, quick analysis, accuracy and reporting. Effective and efficient information flow enhances managerial decision-making, thereby increasing the firm's ability to achieve corporate and business strategy objectives Manson, McCartney, and Sherer, (2001). This in turn, may increase the prospects of the firm's survival Platt and Platt, (2012). This can be evaluated by the procedures, accounting records and tools used Keating and Frumkin (2003).
Empirical Review
This section discussed the empirical review both international and local evidence of studies that had been carried out bykjhgf other researchers. Alshebeil (2010) aimed to identify the role of accounting information systems in having competitive advantage for Jordanian commercial banks, and his findings were that there is a statistically significant impact for accounting information systems on achieving the dimensions of competitive advantage by improving the pricing process for banking services, reducing costs of banking services, increasing the speed of providing services, and increasing market share. Amveko (2011) in which she aimed to identify the impact of accounting information systems on financial reporting in Kampala, the financial reports generated conform to some of the quality attributes of good financial European Journal of Business and Management www.iiste.org ISSN 2222-1905(Paper) ISSN 2222-2839(Online) Vol.12, No.17, 2020 116 information. This was emphasized by a positive correlation of response on quality attributes of timeliness and accuracy; though it was on a low scale her findings were that computerized accounting system actually has an influence on the quality of financial reports for publication purposes.
International Evidence
El-Dalabeeh (2012) aimed to identify the role of computerized accounting information systems in reducing the costs of medical services at King Abdullah University Hospital, and his findings were that computerized accounting information systems play an important role in reducing the costs of medical services at King Abdullah University Hospital compared with non-computerized systems, which usually require bigger costs and do not contribute to reduce the costs of medical services.
Local Evidence
A study conducted by Otieno and Oima (2013) they studied the Effect of Computerised Accounting Systems on Audit Risk Management in Public Enterprises, the study reflected that only 36% of the institutions reported that they had a regular program or equivalent in place while another 24% were in the process of implementation of the computerised system. More than 40% of the participating institutions lacked computerized audit implementation plan.
Research Methodology
This study adopted the survey method as a research design. The study was conducted in Ghana and the population made up of all banks listed on the Ghana Stock Exchange. The researcher engaged 300 respondents from the twelve listed banks in the Ghana Stock Exchange using the purposive sampling technique. This was informed by Saunders et al, (2007), Zikmud (2001). The quantitative research approach was explored due to the nature of the study objective.
Methods of Data Collection
This study used primary data and secondary data. Primary data are those which are collected at fresh and for the first time Kothari (2005). We obtained these data for the first time through questionnaires and observations. Secondary data are data that are already available and refer to data that have already been collected and analysed by someone else Kothari (2005). Secondary data were obtained through documentary review, which included published and unpublished documents, and different reports. Questionnaire: In this study the questionnaire was the main mechanism for data collection. We used the questionnaire because it is fast, and it gives the respondents enough time to mirror on the questions. Since each respondent was asked to respond to the same set of questions, it provided an efficient way of collecting replies from a large sample prior to measurable analysis Saunders et al, (2007). Observation: Some data will be acquired from non-participatory observation. We predicted some of the information concerning computerised accounting systems in the municipality and to the country as a whole.
Analysis and Presentation
The collected data was processed using the statistical package for social sciences (SPSS). Data were presented in tables and bar charts. Descriptive statistics will be used to analyses data for the purpose of understanding the main characteristics of the research variables. Cross tabulation was used to determine the relationships between variables. These techniques of data presentation and analysis were chosen because they are easily applicable and understandable.
RESULTS AND DISCUSSION OF FINDINGS 4.1 Descriptive Analysis of Computerize Accounting Systems
The researcher further needed to know the effects of computerized accounting systems on the quality of financial reports European Journal of Business and Management www.iiste.org ISSN 2222-1905(Paper) ISSN 2222-2839(Online) Vol.12, No.17, 2020 shows whether CAS facilitate financial management in the bank, Out of the 300 (100%) of the respondents. 50% of the respondents strongly agreed, 42% of them agreed, 2.5% were uncertain and 5% of them strongly disagreed. Henceforth, there is enough evidence for us to confirm that, CAS facilitate financial management in banking industries. Figure 4.5; depicts that out 100% of responses, 50% of the respondents strongly agreed, 20% agreed, 10% disagreed and 20% of them strongly disagreed that, CAS improves quality of financial report in the banks. Based on these result, we can conclude with the level of 50% and 20% that CAS improve quality of financial report in the bank. ISSN 2222-1905(Paper) ISSN 2222-2839(Online) Vol.12, No.17, 2020 118 Table 4.5; shows some of the software packages the banks use and the extent to the usage of those software in the bank.
Quality of Financial Reports
The researchers sought to know the NGOs responses on the quality of financial reports. shows that all the 300 (100%) of respondents, agreed to the response YES CAS is part of the bank business activities. Thus we have enough evidence to justify that, the bank uses CAS in its business activities with 100% level of confidence. www.iiste.org ISSN 2222-1905(Paper) ISSN 2222-2839(Online) Vol.12, No.17, 2020 Table 4; illustrates whether CAS report provide relevant financial information to stakeholders for decision making and planning. The table presented that out of 300 (100%), 40% of the respondents strongly agreed, 45% of them agreed, 10% of them disagreed and 5% of the respondents strongly disagreed.
For that matter, we have 45% and 40% level of confidence to say the CAS provides relevant financial information to stakeholders for decision making and planning.
Summary and Conclusion
The study showed that quality of computerized accounting systems affects the quality of financial reports of banks to a great extent. The aspects of computerized accounting systems affect the quality of reports of the bank to a great extent include timeliness, speed, accuracy and quality of package used. It was observed that, the quality of the financial reports are good with the majority agreeing that the information in the reports are accurate, helps in accountability, improve quality of financial report in the bank and relevant.
This finding agrees with what Amveko (2011) studied in which she aimed to identify the impact of computerized accounting information systems on financial reporting in Kampala, the financial reports generated conform to some of the quality attributes of good financial information. This was emphasized by a positive correlation of response on quality attributes of timeliness and accuracy though it was on a low scale her findings were that computerized. The study concludes that computerized accounting systems factoring in its speed, timeliness, accuracy reliability and the possibility of producing quality data affect the quality of financial reports of the banks in Ghana.
Recommendations for Policy
From the study findings, it was clear that computerized accounting system in terms of its speed, timeliness, accuracy and quality of reports generated, affects the quality of financial reports of the bank. The study therefore recommends that in order to ensure that the bank have quality understandable reports; they should invest in computerized accounting system since it is seen to affect the financial reports to a great extent | 3,025.4 | 2020-06-01T00:00:00.000 | [
"Economics",
"Business"
] |
Molecular Rigidity/Flexibility Dependence of Mesomorphism
: A novel chalconyl homologous series of liquid crystalline derivatives; RO - C 6 H 4 - CH : CH - COO - C 6 H 4 -CO - CH : CH - C 6 H 4 - OC 8 H 17 (n) (para) have been synthesized and studied with a view to correlate the thermotropic liquid crystal (LC) behavioural properties and the molecular structure of a substance. Present novel series consisted of eleven homologue members (C 1 to C 16 ) whose, only nematogenic mesomorphism commences from C 3 homologue and continued upto C 16 homologue in enantiotropic manner with absence of smectogenic character. Transition temperatures and textures of nematic phase were determined using an optical polarizing microscopy equipped with a heating stage (POM). Transition curve Cr-N/I behaved in normal manner. N-I transition curve exhibited odd-even effect and deviated from its normal descending tendency from and beyond C 8 homologue and adopted serpantile shape from C 8 to C 16 homologue in deviating manner. Textures of the nematic phase are threaded or schlieren.
INTRODUCTION
Thermotropically liquid crystalline (LC) [1] novel homologues of chalconyl derivatives are important from the point of view of their applicability [2,3,4,5,6,7] in the manufacture of LC devices to be operated at desired or room temperature and their bioactivities to be exploited as anticancer, antimalarial, antibacterial etc in the benefit of mankind. Therefore present investigation was planned to synthesize novel chalconyl ester derivatives which can be useful to all scientific and technological research investigators working on LC state with different aims, objects and views with different angle. The present aim of investigation is fixed with a view to understand and establish the effect of molecular structure [8,9,10,11,12,13] on properties of thermotropic LC substances, which includes even a minor change in molecular structure can bring about major change in LC behaviour as a consequence of changing molecular rigidity and/or flexibility [14,15,16,17]. Numbers of chalconyl ester or azoester or simple esters have been reported till the date [18,19,20,21,22,23,24]. The synthesis of novel homologues of proposed investigation after their due characterisation will be compared with other structurally similar analogous series and then group efficiency order will be derived with respect to thermal stability, early commencement of mesophase and the degree of mesomorphism.
Synthesis:
4-Hydroxy benzaldehyde was alkylated by usual established method [25a]. n-alkoxy benzaldehydes were treated with malonic acid to convert them into 4-n-alkoxy cinnamic acids (A) [25b]. n-alkoxy cinnamic acids were condensed with α-4 hydroxy benzoyl -4' octyloxy phenyl ethelene [26] [B] (m.p. 117 0 C ) by usual established method. Components A and B were condensed [27] to give final products. Synthetic route to usual series is mentioned below as scheme-1. Final products were individually decomposed, filtered, washed, dried and purified till the constant transition temperatures obtained.
The chemicals 4-hydroxyl benzaldehyde, melonic acid, alkyl halides, 4-hydroxy acetophenone, 4decyloxy benzaldehyde, potassium Hydroxide, hydrochloric acid etc. required for synthesis were used as received except solvents which were dried and distilled prior to synthesis Scheme-1: Synthetic route to the series-1
Characterization:
Some selected members of the titled series were characterized by elemental analysis, 1 HNMR spectra and IR spectra, Textures of mesophases were characterized by miscibility method. Microanalysis for C,H,N, elements was performed on Perkin Elmer PE 2400 analyzer (Table-1). 1 HNMR spectra were obtained on Bruker spectrometer using CDCl 3 as solvent. IR spectra were recorded on a Perkin-Elmer spectrum GX. Transition temperatures and liquid crystal properties were investigated using an optical polarizing microscope equipped with a heating stage.
RESULTS AND DISCUSSION:
Novel chalconyl ester derivatives are synthesized by the condensation of dimeric trans n-alkoxy cinnamic acids and α-4-Hydroxy benzoyl β-4'-n-octyloxy phenyl ethylene of whose transition temperatures are lower as compared to the transition temperatures of the corresponding n-alkoxy cinnamic acids. All the members of a novel series except C 1 and C 2 are nematogenic without exhibition of smectic property. The transition temperatures as determined (table-2) from an optical polarizing microscopy (POM) are plotted versus the number of carbon atoms present in n-alkyl chain (R) of left terminal -OR. The Transition curves Cr-I/N and N-I are obtained by linking like or related points which shows phase behaviours of series as depicted in a phase diagram as shown in figure-1. Cr-N/I transition curve adopted a zigzag path of rising and falling with overall descending tendency. Cr-N/I transition curve rises and falls as light wave or appears like a serpant, instead of normal descending behaviour. The deviation from normal descending behaviours commences from an unique C 8 homologue [R=R' i.e. H 17 C 8 O-= -OC 8 H 17 end group ] and it passes through C 10 , C 12 , C 14 and C 16 homologues in more or less or negligible proportions; as shown by dotted lines in N-I transition curve showing expected descending tendency. N-I transition curve is extrapolated in left to the C 1 and C 2 nonmesogenic homologues to predict their hypothetically latent transition temperatures (LTT) and to highlight the appearance of odd-even effect of N-I transition curve. Oddeven effect disappears from and beyond C 8 homologue where the N-I curves for odd and even homologues prior to C 8 are merging into each other and then a single transition curve (N-I) is prolonged for higher homologues of longer n-alkyl chain. The LC properties vary from homologue to homologue in the same present series with changing number of carbon atoms in n-alkyl chain 'R' of -OR; keeping -OC 8 H 17 tail end unchanged throughout the series under discussion.
The lowering of transition temperatures of novel homologues as compared to corresponding dimeric trans-n-alkoxy cinnamic acids is attributed to breaking of hydrogen bonding by esterification process. Odd-even effect observed for N-I transition curve is due to sequentially added methylene unit in n-alkyl chain 'R' of -OR. The exhibition of nematogenic character from C 3 to C 16 homologues is attributed to the suitable magnitudes of anisotropic forces of end to end dispersion forces, dipole-dipole interactions and permanent dipolemoment across the long molecular axis as a consequence of favourable molecular rigidity and flexibility as depended on molecular structure; which facilitated the molecules of homologues (C 3 to C 16 ) to float on the surface with statistically parallel orientational order to cause nematic mesophase formation. Inexhibition of smectogenic mesophase formation is attributed to the absence of lamellar packing of molecules in the preoccupied crystal lattices which eliminates the possibility of facilitating sliding layered molecular arrangement in floating condition for all of the homologues of a novel series. The nonmesomorphic behaviour of C 1 and C 2 homologue is attributed to their high crystallising tendency which arises from low magnitudes of intermolecular end to end or lateral dispersion forces and low dipole-dipole interactions, which disallows the formation of LC state and encourage high crystallising tendency. All the homologues of present series transforms into isotropic state at their isotropic temperature and then from and beyond isotropic temperature, the molecules are randomly oriented in all possible directions with high order of disorder or randomness or high entropy (∆S=∆H/T) in uncontrolled manner. But on cooling the same carefully, the nematic mesophase reappeared from and below isotropic temperature at which nematic phase was appeared on heating in reversible manner. However none of the nematogenic homologues have showed smectic phase or nonmesomorphic homologues C 1 and C 2 showed nematic mesophase (LC) in irreversible manner in monotropic condition. The extrapolated L.T.T values [28,29,30,31] from N-I transition curve for C 1 and C 2 are 89.0 0 C and 86.0 0 C respectively, but, these values are far below the isotropic temperatures of corresponding homologues C 1 and C 2 . Therefore, before they show mesophase formation at LTT, the isotropic mass undergoes to crystallisation and hence solidifies. The changing trend in LC behaviours and properties from homologue to homologue in the same series is attributed to the progressively and sequentially added methylene unit or units at the left n-alkoxy -OR group. The disappearance of odd-even effect from and beyond merging of N-I transition curves International Letters of Chemistry, Physics and Astronomy Vol. 60 for odd and even initial homologues, is attributed to the longer n-alkyl chain 'R' which may coil or bend or flex or couple to lie with the principal axis of the core structure. The observed deviations from and beyond C 8 unique homologue is attributed to the uncertainity in the status of n-alkyl chain 'R' of -OR and tail end group -OC 8 H 17 or -OC 14 H 29 , which affects the suitable magnitudes of molecular rigidity and flexibility as depended on unusual status of molecular structure, under the influence of exposed thermal vibrations. Some LC properties of presently investigated novel series-1 are compared with the structurally similar analogous series X [32] and Y [33] as mentioned below in figure-2.
Figure-2: Structurally similar series.
Homologous series 1, X and Y are identical with respect to three phenyl rings, a central bridge -CO-CH=CH-linking middle and third tail phenyl ring and left n-alkoxy group -OR for the same homologue from series to series. But they differ with respect to a central bridge linking first and middle phenyl rings in case of series 1 and X, as well as tail end groups -OC 8 C 17 and -OC 14 H 29 in case of series 1,X, and Y. Thus, combined effect of molecular rigidity and flexibility creates differing features, which causes variations in LC properties and the degree of mesomorphism among the series 1, X and Y under and, among the homologues of same series. Following table-3 represents some relative thermometric properties for the series under comparison. Table-3 clearly indicates that, All the homologous series 1, X and Y under comparison are only nematogenic without exhibition of smectogenic property. Nematogenic mesomorphism commences identically from C 3 homologue of the series-1 and X, but it commences late from C 6 homologue of a series-Y. Thermal stability for the series X and Y under comparison are almost nearer (98.88~99.75) or equivalent whereas it is higher (112.66) for a present series-1. The lower mesophaselenths (nematic) are in increasing order whereas, upper mesophaselenths are in the decreasing order of magnitudes, from series 1 to series-X to series-Y. Mesomorphic -isotropic transition curves of series 1, X, and Y in their respective phase diagrams exhibited odd-even effect with more or less or negligible deviation from its expected descending tendency.
The exhibition of only nematic property by the series 1, X and Y is attributed to their identical geometric shapes, aromaticity including one or both central bridges, tail end groups except -OC 14 H 29 , etc. which causes the end to end and lateral intermolecular dispersion forces of suitable and of different magnitudes which resists exposed thermal vibrations to induce nematic mesophase formation for different range of temperatures. However the magnitudes of intermolecular dispersion forces of cohesion and closeness are incapable of inducing lamellar packings of molecules in the crystal lattices of homologues, belonging to series 1, X and Y which eliminates the possibilities of sliding layered molecular arrangement in floating condition and avoids the facilitating possibility of smectogenic mesophase formation. Early commencement from C 3 homologue for series 1 and X is attributed to the equivalent extent of molecular noncoplanarity irrespective of changing a central bridge -COO-or -CH=CH-COO-linking first and middle phenyl ring and a commonly present tail end group -OC 8 H 17 and second central bridge -CO-CH=CH-linking middle and third phenyl ring. Thus, presence of same tail ends and same chalconyl second central bridge containing multiple double bond reduces effect on the extent of molecular noncoplanarity irrespective of -COO-or -CO-CH=CH-first central bridge. However on changing tail end group from -OC 8 H 17 to -C 14 H 29 , the extent of molecular noncoplanarity vary to such an extent in case of series-Y that, the commencement of nematic phase takes place later from C 6 homologue. However thermal stabilities for nematic adopted decreasing order from series-1 to almost equivalent thermally stable series-X and Y; because, the energy stored by the molecules (∆H) at constant pressure is relatively higher for presently investigated series-1, which resisted exposed thermal vibrations with wider range of temperature. Hence, relative enthalpy value (∆H) or the energy stored in the homologue molecules of series-1 raises transition temperatures and thermal resistivity, resulting into highering of thermal stability and the upper mesophaselength as compared to series-X and Y. Deviations observed in mesomorphic -Isotopic transition curves, instead of their adoption of normal descending behaviours, is attributed to the unusual status of n-alkyl chain on both terminal end groups.
Conclusions:
Chalconyl ester novel homologous series of present investigation is enantiotropically nematogenic with absence of smectic property, whose thermal stability is 112.66 and considerable degree of mesomorphism with its middle ordered melting type and exhibited more or less or negligible deviation in N-I transition curve. The group efficiency order derived for nematic on the basis of (a) thermal stability (b) early commencement of nematic phase and (c) upper and lower degree of mesomorphism is as under. (a) Nematic: Series-1 > Series-X ~ Series-Y (b) Nematic: Series-1 = Series-X > Series-Y (c) Nematic: Lower Degree of mesomorphism : Series-Y > Series-X > Series-1 Upper Degree of mesomorphism : Series-1 > Series-X > Series-Y Chalconyl LC derivatives may be useful for the study of binary system for LC Devices to be operated at desired temperature.
Chalconyl derivatives being bioactive molecules can be studied as anticancer, antimalarial, antibacterial etc. Mesomorphism is very sensitive and susceptible to molecular structure as a consequence of molecular rigidity and flexibility. Present investigation supports and raises the credibility to conclusions drawn earlier.
Acknowledgement:
Authors acknowledge thanks to the Dr. N.N.Vyas, the head of chemistry department and the principal Dr. M.B.Patel of the college for their supportive view and providing research facility of present investigation. Authors are also thankful to Dr. A.V.Doshi, Ex. Principal, M.V.M. Science and Home. Sc. College, Rajkot for his valuable co operation and support as and when needed throughout this present investigation. Authors acknowledge thanks to dept. of chemistry, S. P. University, Vidhyanagar for analytical and spectral services. | 3,295.6 | 2015-09-30T00:00:00.000 | [
"Chemistry",
"Materials Science"
] |
Epistemic Blame and the Normativity of Evidence
The normative force of evidence can seem puzzling. It seems that having conclusive evidence for a proposition does not, by itself, make it true that one ought to believe the proposition. But spelling out the condition that evidence must meet in order to provide us with genuine normative reasons for belief seems to lead us into a dilemma: the condition either fails to explain the normative significance of epistemic reasons or it renders the content of epistemic norms practical. The first aim of this paper is to spell out this challenge for the normativity of evidence. I argue that the challenge rests on a plausible assumption about the conceptual connection between normative reasons and blameworthiness. The second aim of the paper is to show how we can meet the challenge by spelling out a concept of epistemic blameworthiness. Drawing on recent accounts of doxastic responsibility and epistemic blame, I suggest that the normativity of evidence is revealed in our practice of suspending epistemic trust in response to impaired epistemic relationships. Recognizing suspension of trust as a form of epistemic blame allows us to make sense of a purely epistemic kind of normativity the existence of which has recently been called into doubt by certain versions of pragmatism and instrumentalism.
Introduction
Do epistemic norms provide us with normative reasons for compliance? Such norms tell us, very roughly, that we should believe what we have sufficient evidence for, and that we should refrain from believing what we lack sufficient evidence for. Recently, epistemologists have questioned that epistemic norms have genuine normative significance. Susanna Rinard, for instance, argues "that only pragmatic considerations are genuine reasons for belief. That is, purely evidential considerations-evidential considerations that are not also pragmatic reasons-do not constitute reasons for belief" (2015,219). To illustrate this view, consider a case in which you happen to come across the newest celebrity gossip in a magazine that you know to be reliable. Assume that you know that having a true belief about the gossip is not, nor will ever be, of any practical value for you, and that you are not curious about such gossip at all. Now consider the following questions: • Should you believe the gossip? • Are you blameworthy or criticizable if you fail to believe the gossip?
Or consider a slightly altered case in which you happen to believe some celebrity gossip although you are aware that the magazine in which you came across it is not reliable. Your belief is not based on sufficient evidence. We can again stipulate that you know that nothing bad will ever come from having such an ill-based belief about this unimportant matter that is of no interest to you. Now consider the following question: • Are you blameworthy or criticizable for having this belief?
The view under consideration in this paper would reply with "no" to all these questions. Let us call this view "anti-normativism about evidence" (short: ANE). Proponents of ANE argue that mere evidence does never provide us, by itself, with a (normative) reason for belief. Next to Rinard's view, recent instrumentalists about reasons for belief commit to ANE. Asbjørn Steglich-Petersen and Mattias Skipper argue "that evidence for p speaks in favor of believing p only in context where there is a practical reason to pursue the aim of coming to a true belief as to whether p" (2019,9), and that therefore "it is strictly speaking false to say that evidence by itself constitutes a normative reason for belief" (2020,114). Similarly, Maguire and Woods (2020) have recently denied that purely epistemic norms provide us with reasons. 1 They compare epistemic norms with rules of games: we only have a reason to comply with each if we have a practical (prudential or moral) reason to engage in the relevant practice. That is, I have a reason to move a chess piece according to the rules only if I have a practical reason to play chess; analogously, they argue that I have a reason to believe that p only if I have a practical reason to play what Maguire and Woods call "the game of belief". 2 1 In their terminology, epistemic norms are just not authoritatively normative. However, according to their view, also the rules of chess count as (non-authoritatively) normative. In my terminology, norms of chess are not normative in the sense that they do not provide us with reasons for compliance. I follow Kiesewetter (2017, 3-4) in this use of "normative". In Maguire's/Wood's terminology, I am interested in authoritative norms and reasons. While I use the term "norm" as including also non-normative rules or standards, I use "reasons" exclusively in a normative sense. I do not think there are non-normative reasons (except for explanatory ones). So my question is: "Do epistemic norms provide us with reasons?" Cf. Hofmann (2020) on some unpacking of the idea that some norms "provide" us with reasons-on which I cannot elaborate within the scope of this paper. 2 For recent accounts with similar implications, cf. Bondy (2018), Cowie (2014), Mantel (2019), McCormick (2015McCormick ( , 2020, Papineau (2013). Of these, only McCormick identifies explicitly as a pragmatist (like Rinard). Instrumentalists argue that they can avoid a commitment to pragmatism-i.e., to the existence of practical reasons for belief per se-by saying that it is always evidence that motivates our beliefs (rather than practical reasons). Instrumentalists merely claim that evidence gains its normative The normativity of evidence is at stake in contemporary epistemology. What could possibly count as a satisfying reply to ANE? This paper is devoted to answering this question. I argue that, in order to get clear about the normative significance of evidence, we need to think about the reactive attitudes that are appropriate towards violations of purely epistemic norms. I reach this claim by first spelling out the dilemma of explaining why epistemic norms matter without thereby rendering them practical (Sect. 2). This dilemma will allow us to pin down a challenge for normativism about evidence: finding a satisfying conception of a distinctively epistemic kind of blame (Sect. 3). I then propose, in outline, a reply to this challenge (Sect. 4). I suggest that we hold each other answerable to epistemic norms by showing reactive attitudes towards each other's epistemic failures-mainly suspension of epistemic trust (cf. Boult, 2020Boult, , 2021. The normativity of evidence can become intelligible by understanding this practice. For the reactive attitudes within our epistemic practice reveal the normative significance of purely evidential considerations. The result of the paper is that we should not submit too quickly to treating the epistemic as hostage to the practical. Rather, we should first engage in the project of understanding the distinctive normative significance of purely evidential considerations by appealing to our responsibility for (non-)compliance with epistemic norms. Only if it were to turn out that this project fails-because, say, it turns out that there is no distinctive responsibility attached to the purely epistemic-we would be justified to endorse ANE. However, proponents of ANE have not yet provided arguments that this project fails. Doing so would require them to engage with recent accounts of epistemic blame and responsibility for belief. The paper thus shifts the dialectical burden to proponents of ANE and connects debates within contemporary epistemology.
The Challenge for the Normativity of Evidence
This section argues that normativism about evidence-the view that purely evidential considerations provide us with reasons for belief-faces a dilemma. I first outline two strategies for finding a plausible content of epistemic norms (Sect. 2.1). I argue that both strategies give rise to the same dilemma for normativism (Sects. 2.2). This will then allow us to formulate the central challenge for normativism in Sect. 3, and thus to see the intuitive appeal of ANE.
authority from practical considerations (cf. Cowie, 2014, 4004-5;Steglich-Petersen & Skipper, 2019, 11). I am not here interested in subtle differences between the versions of pragmatism and instrumentalism I consider. I am only interested in their implication of ANE. (However, cf. note 10 below on how Steglich-Petersen/Skipper's version of instrumentalism might collapse into pragmatism.).
Replying to the Clutter-Objection: Background Conditions on Epistemic Norms
Consider the following rough first approximation towards formulating an epistemic norm (also mentioned at the beginning of this paper): (EN) One ought to believe everything that is sufficiently supported by one's evidence.
Gilbert Harman (1986, 12) In reaction to this, we might modify the epistemic standard so that its violation more plausibly gives rise to serious criticism. We might propose background conditions for when we are required to believe what our evidence sufficiently supports. These background conditions should fulfill two criteria: (a) They must make it plausible that the subject is, at least normally or in paradigm cases of an epistemic norm violation, blameworthy or criticizable for not complying with the epistemic norm when the background conditions are fulfilled. (b) They should not render the norm practical rather than epistemic.
Call (a) the criterion of significance, and (b) the criterion of content. (b) makes sense as a criterion on epistemic norms for our purposes because the aim of the normativist is to preserve a purely epistemic kind of normativity. But why (a)?
The guiding idea behind (a) is that the significance of a norm expresses itself in the reactive attitudes that we show towards violations of the norm. For instance, the significance of a moral requirement will make it often-in absence of an excuse or exemption-appropriate to show resentment or indignation. These emotions are expressions of the normative significance we attach to the moral requirement because they are appropriate in face of its violation. Similarly, if there are distinctively epistemic norms that provide us with reasons for compliance, then we should expect there to be distinctively epistemic reactive attitudes that we show towards the violation of those epistemic norms. In this vein, Antti Kauppinen understands genuine norms (as contrasted with mere evaluative standards) as "rules that someone is accountable for conforming to in suitable circumstances" (2018, 3).
Here is an argument for (a). Why is it false that we should clutter our minds with all the implications of our beliefs? If we would accept that epistemic norms require us to clutter our minds, then we would constantly violate an epistemic norm by not drawing all the implications from our beliefs. However, this constant violation would have no further significance: we would not normally be blameworthy or criticizable for failing to believe what we epistemically ought to believe. The problem with this is that the normative force of this "ought" would then be mysterious: why comply with this norm if one cannot hold us legitimately responsible for non-compliance? The norm would at best have the force of the norms of etiquette or the rules of a game: we can intelligibly ask why we have a reason to comply with the norms of etiquette or rules of a game in a given situation. Such norms do not, by themselves, provide us with reasons. Thus, the best explanation of the intuitive appeal of Harman's clutter-objection when it comes to trivial implications of our beliefs is that we assume that epistemic norms with normative significance would fulfill (a). 4 I will return to the connection between epistemic reasons and epistemic blameworthiness in Sect. 3. For now, consider another strategy for finding a plausible norm of belief that is purely epistemic. Instead of proposing background conditions to (EN), we might rather argue that (EN) is not a central epistemic norm at all. In response to Harman's clutter-objection, we might argue that, although we are never blameworthy merely for failing to believe what our evidence sufficiently supports, there are other epistemic requirements that are purely evidential. Specifically, we might defend the following epistemic norm: (EN*) One ought not [to believe what is not sufficiently supported by one's evidence.] (EN*) is not confronted with Harman's clutter objection: rather than requiring us to believe plenty of propositions we intuitively have no reason to believe, (EN*) merely prohibits us to have certain beliefs. Steglich-Petersen (2018) accepts (EN*) but denies (EN): he thinks that evidence alone determines the permissibility of belief (which beliefs I am epistemically allowed to have), but he argues that evidence alone never gives us, as he puts it, "positive reason" to believe a certain proposition. Epistemic norms, on this picture, determine the space of doxastic permissibility, but they never require a specific belief-rather, they merely prohibit certain beliefs (cf. also Whiting, 2010Whiting, , 2013. However, appealing to a norm of permissibility like (EN*) instead of (EN) won't help to defend the normativity of evidence against the challenge I spell out in this paper. First, it seems that (EN*) should not be any more plausible to skeptics about the normativity of evidence than (EN). The norm that we ought to believe everything that is supported by our evidence faces the problem that it requires us to needlessly clutter our minds. The norm that we ought not to believe anything that is not sufficiently supported by our evidence faces the reverse problem: it would require us not to have a lot of beliefs we, it seems, have no reason to give up. For example, why should I give up evidentially unsupported but beneficial beliefs? We often overestimate our own abilities or the virtues of our significant others. Arguably, this can promote our self-esteem (cf. Kelly, 2003) or our relationships (cf. Stroud, 2006). It seems that such beliefs are blameless as well. A general norm not to believe what is insufficiently supported by one's evidence seems too exclusive. And a norm to believe anything that is sufficiently supported by one's evidence seems too inclusive.
Furthermore, cases of trivial belief pose the same problem for (EN*) as they pose for (EN). What if you believe, in absence of sufficient evidence, that the celebrity gossip in this unreliable magazine is true? Why should it make sense for anyone to blame or criticize you for this belief, if we stipulate that your trivial belief will have no bad consequences? Such trivial propositions seem to pose a challenge to (EN*) as they do to (EN)-as I will illustrate in some more detail in Sect. 2.2 below.
One final clarificatory remark: I will call any form of blame that arises from the violation of a purely epistemic norm-i.e., an evidential norm that does not mention any practical considerations-epistemic blame. That is, epistemic blame, if there is such a thing, is a kind of negative reaction that is appropriate towards violations of purely epistemic norms like (EN) or (EN*), given suitable non-pragmatic background conditions. I now turn to the idea of background conditions on epistemic norms in some more detail to spell out a dilemma for normativism about evidence that will give rise to a challenge for normativism.
Proposing Background Conditions: A Dilemma
One way of developing a background condition on (EN) that might allow us to preserve the normativity of evidence is presented by Kiesewetter (2017, 184-5). He responds to Harman's clutter-objection by proposing that the central standard of theoretical rationality is to believe what one's evidence sufficiently supports if one attends to this evidence. According to this proposal, if I attend to the fact that I have sufficient evidence for a specific disjunctive proposition, then I would be criticizable (because irrational) if I do not come to believe it. Thus, Kiesewetter concludes, there is a sense in which I ought to believe it as soon as I attend to my sufficient evidence. Analogously, we could propose a background condition on (EN*) by saying that if we attend to the fact that we lack sufficient evidence for p, we ought not to believe p: we would be criticizable if we were to believe p; but we wouldn't be criticizable for this if we never noticed how our belief lacks evidential support-we wouldn't count as irrational. 5 It seems that Kiesewetter's background condition, while doing a good job in fulfilling criterion (b), does not fulfill (a). There are cases where we attend to sufficient evidence but where it would not make much sense to regard us as blameworthy or criticizable if we, for whatever reason, do not believe what the evidence supports. Take, again, the case in which I come across the newest celebrity gossip in a magazine that I know to be reliable, but I fail to believe the gossip. Assume again that having a belief about the matter is of no importance and that I do not care about whether the gossip is true. Proponents of ANE will argue that there is then no sense in which I am blameworthy, and that it is false that I ought to believe the gossip. 6 It thus seems that if it does not matter whether we believe an evidentially wellsupported proposition, it is false that we ought to believe it. However, if we instead propose a background condition on sufficient evidence that implies that it always matters whether we comply with the epistemic norm, we seem to end up violating criterion (b): if the norm is only in place when it matters whether we comply with it, then, so it seems, the norm is no longer a purely epistemic norm. It thus seems that there is no background condition on purely epistemic norms like (EN) and (EN*) that fulfills both (a) and (b). The normativist is in a dilemma.
Let us provide this dilemma with additional support by considering a background condition that does not fulfill criterion (b). Steglich-Petersen (2011), after discussing a case of a trivial belief that the subject is not required to have although it is wellsupported by the subject's evidence (23), presents the following partial analysis of reasons for belief: Necessarily, if S has all-things-considered reason to form a belief about p, then [if S has epistemic reason to believe that p, S ought to believe that p] (24).
Here "epistemic reason" can be read as "sufficient evidence for p". The conditional then states that if one has an all-things-considered reason to form a belief about p, one ought to believe what one's evidence sufficiently supports. The italicized ifclause is Steglich-Petersen's proposed background condition for the epistemic standard (EN). Steglich-Petersen could analogously propose a background condition on (EN*): if one has an all-things-considered reason to form a belief about p, then if p is not sufficiently supported by one's evidence, one ought not to believe p. 7 Steglich-Petersen's "all-things-considered reason to form a belief about p" can, for instance, be a reason for an action prior to the belief. 8 "Forming a belief about p" might refer to the action of thinking about whether p: I may have more or less reason to think about whether something is true. I have some reason to think about whether there will be nice weather during the next days, but I have no reason at all to think about the newest celebrity gossip (I might even have reason to avoid such thinking). Thus, according to one plausible reading, the truth of "S ought to believe that p" in Steglich-Petersen's analysis is conditional on a practical reason for an action. It says that if we have a reason to bring it about or to maintain that we have a (true) 9 belief about p, and there is sufficient evidence for p, then we ought to believe that p.
Since we only have a reason to bring a belief about when it matters whether we have this belief, Steglich-Petersen's proposal does a good job fulfilling our criterion of significance. Yet his proposed background condition, and thus the proposed epistemic norm, is no longer epistemic, because it includes a practical reason (for an action). His proposal thus fails to fulfill our criterion of content. 10 Thus, while proposing non-pragmatic background conditions on epistemic norms (á la Kiesewetter) apparently does not result in doxastic norms that fulfill the criterion of significance, proposing a pragmatic background condition (á la Steglich-Petersen) results in doxastic norms that do not fulfill the criterion of content. If the normativist about evidence accepts the criterion of significance for epistemic norms, they have to defend the claim that compliance with epistemic norms matters (in a sense) even if we do not equip these norms with a pragmatic background condition. Prima facie, it is hard to see how purely epistemic norms could matter by themselves. Therefore, any normativist will, it seems, end up in either of two horns: (i) Epistemic norms are purely epistemic, but they fail to be significant. (ii) Epistemic norms are significant, but they fail to be purely epistemic.
Footnote 7 (continued) seems that Steglich-Petersen's instrumentalist framework commits him to a background condition not only for (EN), but also to (EN*): without assuming pragmatic background conditions, both norms seem questionable as genuine normative requirements. 8 Note that the reason for forming a belief about p cannot be itself an epistemic reason for belief, because epistemic reasons favor believing a specific proposition-they favor believing that p or not believing that p. Steglich-Petersen's reason to form a (true) belief about p, by contrast, does not favor believing a specific proposition. It merely favors having a true belief about a matter, whatever this belief turns out to be. Only practical reasons can favor forming a belief about a matter without favoring a specific proposition. 9 In later works, Steglich-Petersen accepts that the reason to form a belief about p must in fact be a reason to form a true belief about p (see esp. the formulations of the norms of belief in Steglich-Petersen & Skipper, 2019, 2020). 10 One might wish to interpret Steglich-Petersen's view without committing to the idea that the practical reason is always a reason for an action of managing one's beliefs (causing, maintaining, etc.). However, as pointed out in note 8 above, the "reason to form a belief about whether p" cannot be epistemic. It must thus be practical. If the practical reason does not favor an action, it must favor the state of believing itself. This would, however, commit Steglich-Petersen to pragmatism about reasons for belief. Whether this reason favors actions of managing beliefs or rather beliefs themselves, the condition renders the requirement practical rather than purely epistemic.
We might be tempted conclude from the dilemma that ANE is true: we might think that we should just reject the idea that we are ever epistemically blameworthy, and that there is any such thing as a purely epistemic kind of normativity.
I think this dilemma points to a serious challenge for the normativity of evidence. However, I will ultimately propose that purely evidential considerations have a kind of normative significance: (non-)compliance with purely epistemic norms matters. This requires me to make sense of a notion of epistemic blame. For the significance of a norm expresses itself in our reactive attitudes towards violations of the norm (cf. Sect. 2.1). Thus, giving a satisfying reply to ANE requires us to reconsider the concept of blameworthiness and responsibility for beliefs. For now, however, we should accept that there is a good case to be made for ANE. I now turn to the argument that is the core of this challenge for the normativity of evidence.
An Argument for Anti-normativism About Evidence
This section presents an argument that constitutes the core of the challenge for normativists (i.e., opponents of ANE) (Sect. 3.1), and it defends one of the two premises of this argument (Sect. 3.2). Replying to the challenge will thus require rejecting the other premise of the argument, which states that there is no distinctively epistemic kind of blame. I will turn to the rejection of this premise in Sect. 4.
The Argument from Doxastic Blameworthiness
Given the dilemma spelled out in Sect. 2, it is now easy to see how the denial of epistemic blame can give rise to an argument for ANE. Take "purely epistemic norms" to refer to (EN) or (EN*), and, if you want to, include any background conditions on purely epistemic norms that do not render the norm practical (like Kiesewetter's attending condition): (1) Evidence provides us with epistemic reasons for belief only if we can be blameworthy (or criticizable) 11 for violating purely epistemic norms.
(2) We cannot be blameworthy (or criticizable) for violating purely epistemic norms.
(3) Thus, evidence does not provide us with epistemic reasons for belief.
According to the view expressed in (3), evidence provides us with reasons only if there is some practical value realized in following the evidence. Even if evidence does not by itself provide us with reasons for belief, it appears as if it provides us with such reason, because we normally have reason to follow the evidence-but this reason is only instrumental because it derives from our reason for the aim of gaining 11 Cf. note 4 on my use of "blameworthy".
practically valuable true beliefs (cf. Rinard, 2015, 219). ANE just is this practicalinstrumental approach to purely epistemic normativity. 12 Premise (1) has a high prima facie plausibility. For it states a very minimal conceptual connection between reasons for belief and blameworthiness. The consequens of (1) states that it must be possible to be blameworthy for non-compliance with purely epistemic norms (under adequate non-pragmatic background conditions).
(1) states that if this is not possible, evidence does not, by itself, provide us with reasons for belief. That is, (1) states that epistemic blame, as defined at the end of Sect. 2.1, must be conceptually possible if purely evidential considerations are to provide us with reasons for belief.
Remember that, as I have argued in Sect. 2.1, Harman's clutter-objection gets its grip on us only because we implicitly assume a connection between reasons and blameworthiness. Epistemologists propose background conditions on epistemic norms, like Kiesewetter's attending-condition or Steglich-Petersen's reason for forming belief about whether p, precisely because they want to make sense of the significance of these norms: they want to explain why it matters to us whether we comply with the norms-why we can be blamed or criticized if we fail to comply with them. The point of spelling out a notion of epistemic blame is to understand the normative force of evidence: why it matters to comply with epistemic norms. 13 Yet most importantly, even if we were to reject that we need to be always blameworthy or criticizable for failing to comply with purely epistemic norms if evidence is to provide us with epistemic reasons for belief, this would not refute (1). For according to (1), it must merely be possible to be blameworthy for such non-compliance: there must be some possible cases in which we are blameworthy in virtue of the fact that we violate purely evidential norms in order for evidence to provide us with epistemic reasons for belief.
If (1) is indeed such a weak claim, then we should expect (2) to be more controversial to allow for the controversial conclusion ANE. Yet we saw that there is a strong prima facie case for (2) to be made by appealing to cases of trivial belief. It is not straightforward in what sense a person who violates a purely epistemic norm is blameworthy when nothing of practical value hinges on whether the person complies with the norm. That we can be blameworthy for violating a purely epistemic norm-i.e., non-(2)-seems to imply that we sometimes are blameworthy in cases of trivial belief. For cases of trivial belief are the cases in which we have isolated any non-epistemic factors-like the factor that there is a practical reason to consider our evidence carefully, or the factor that that it would be morally good to believe what one's evidence supports, or that having a certain belief would be disrespectful 12 Cf. note 2 for proponents. 13 A recent account of epistemic blame which is clearly motivated in this way is Kauppinen (2018). On the side of the proponents of ANE, McCormick (2020) argues that all blame for belief is ultimately prudential or moral. She therefore rejects that there is a normative domain of the purely epistemic. Thus, she explicitly reaches ANE by accepting (1) and (2) (cf. McCormick, 2020, 30). The problem with McCormick's argument is that she does not consider the epistemic forms of blame that have been spelled out by Boult (2020Boult ( , 2021, Brown (2020), and Kauppinen (2018), and to which I will appeal in Sect. 4.2. She rather thinks of blame mainly in moral terms. to a person. If there is never any blameworthiness left after we have isolated these non-epistemic factors-as it seems to be the case in cases of trivial belief-then it seems that there is no such thing as a distinctively epistemic kind of blameworthiness, and thus, given (1), no purely epistemic normativity. (I return to how normativists about evidence can deal with cases of trivial belief in Sect. 4.3.) I will first defend (1) against objections. I thereby show that a challenge for normativism about evidence consists in arguing against (2)-i.e., in finding a good account of the normative significance of evidence by appealing to the concept of epistemic blameworthiness.
Some Worries About Blameworthiness as a Precondition on Reasons
The first objection to premise (1) points out that children or some non-human animals can act for reasons but cannot be blameworthy if they fail to do what is decisively supported by their reasons, because they are not responsible agents. Analogously, some children and animals might be considered has having reasons for belief even though they cannot be blameworthy for violating purely epistemic norms. Thus, (1) does not seem to hold.
The objection can easily be met by pointing out that (1) does not imply that everyone can be blameworthy for violating purely epistemic norms. As I have explained in the last subsection, (1) merely states that it must be possible to be blameworthy in a distinctively epistemic sense if evidence is to provide us with epistemic reasons for belief. If there are some beings who are not fully responsible agents or have not yet developed to fully responsible agents, they might also be exempted from epistemic blame. But that does not count against the idea that those beings who are fully responsible for their actions and beliefs must sometimes be subject to epistemic blame if evidence is to provide us with epistemic reasons.
Secondly, one might wish to deny (1) if one is an objectivist about the meaning of "ought" and "reasons". Objectivists deny a close connection between failing to do what one ought to and being blameworthy (a connection usually utilized or argued for by subjectivists). 14 Objectivism about practical reasons states that "S ought to φ" means that φing is the best option, no matter whether S is in a position to know or has some kind of cognitive access to the fact that φing is the best option. For example, if my house is burning even though I do not have any clue that it is burning, the objectivist would claim that I ought to leave the house. The subjectivist would deny this and say that I only ought to leave the house if I-in some way or another-have cognitive access to the fact that the house is burning. If I have access to that fact but do not leave the house, then I am blameworthy. According to the objectivist, it could be the case that I am not blameworthy, and yet it is true that I ought to leave the house (namely, if I am not in a position to know that it is burning). It thus seems that, if we are objectivists, we do not think that there is any close connection between what we ought to do or what we have reason to do, on the one hand, and blameworthiness, on the other. This suggests that, prima facie, adopting an objectivist theory about reasons for belief would pose a problem to (1).
However, (1) is uncontroversial for objectivists. This is so again because (1) states a very loose connection between reasons and blameworthiness. Even if we grant the objectivist that we can be completely ignorant of our reasons, there will at least be some possible cases in which we are blameworthy for failing to give the response that is best. When we focus on actions rather than beliefs, such cases will be cases where we either act against our better knowledge of what is best or where we culpably fail to know what is best and do the wrong thing as a result of our ignorance. Analogously, if we are objectivists about reasons for belief-for instance, if we think that we ought believe only what is true or correct to believe rather than what is supported by our evidence -, then we can still argue that we are at least sometimes blameworthy because we have a false or incorrect belief. We would be blameworthy in some of the cases where the evidence was accessible to us, and yet did not form the correct doxastic attitude in accord with our evidence. So even if we spell out purely epistemic norms in objectivist terms (e.g., "one ought to believe only what is true"), this does not yet give us an argument against (1). For the accessibility of the evidence does not render the epistemic norm practical, and thus does not compromise the idea that evidence is normative only if we are sometimes blameworthy for violating purely epistemic norms.
Finally, one might want to object to (1) by adopting a permissivist epistemology. Permissivism states, roughly, that our total set of evidence permits more than one set of doxastic attitudes to take towards each (or at least some) proposition(s). 15 According to a permissivist, it could be true that if we have sufficient evidence for a proposition, it is both epistemically permissible to believe it as well as epistemically permissible not to believe it. Such an account might seem to be exactly the conclusion to draw from Harman's clutter-objection (cf. Sect. 2.1): we are not rationally obligated to believe anything that our evidence sufficiently supports, and thus we are not blameworthy for not drawing all implications from our beliefs. But it is always permissible for us to believe propositions that are sufficiently supported by our evidence.
However, it is not straightforward how permissivism could pose a problem for (1). The premise states that we can be blameworthy merely for violating a purely epistemic norm if evidence is to provide us with epistemic reasons. To deny this, the permissivist would have to argue that the possibility of epistemic blame is not a necessary condition on the normativity of evidence. They would have to claim that norms of epistemic permissibility provide us with epistemic reasons even if we cannot be blameworthy for violating them.
But this seems false. If something is permitted only under a certain condition, then it is not permitted-and thus prohibited-if this condition is not fulfilled. That is, that I am permitted to believe that p only if p is sufficiently supported by my evidence implies that I ought not to believe that p whenever p is not sufficiently supported by my evidence. This is what (EN*) states. Thus, even if we understand the normative force of evidence in terms of permissibility, this will still require us to make sense of the idea that we sometimes ought to have certain doxastic attitudes under certain conditions. For instance, when p is insufficiently supported by evidence, we would be required either to suspend judgment about p or to disbelieve p. Purely epistemic norms would then be those norms that require us to either suspend belief about propositions or to disbelieve those propositions that are not sufficiently supported by our evidence (given suitable non-pragmatic background conditions). The normative significance of these norms would still be puzzling if we could not be blameworthy for violating them. Thus, if one reformulates (EN) as a claim about permission rather than obligation, one thereby commits to the equally puzzling epistemic norm (EN*). This won't make the normative force of reasons for belief any more intelligible if one does not show how one can be blameworthy for violating such purely epistemic norms.
This confirms that (1) is uncontroversial, mainly because it rests on a very loose connection between epistemic reasons and epistemic blameworthiness. The premise can be accepted both by proponents and opponents of the normativity of evidence, by objectivists, and by permissivists alike, and is thus a hinge around which the debate can progress.
It is important to see, however, that (1) would be false if we assume that the relevant sense of "blameworthy" must be a paradigm form of moral blame. A person's epistemic failure does not, by itself, give rise to emotions like resentment, indignation, or guilt. If someone believes that candidate X will win the next elections because the flight of the birds gave them a sign, then our reactive attitudes are not, or not necessarily, of that moral kind. But this does not yet rule out that there could sometimes be a distinct kind of epistemic blame appropriate in such cases even when the moral reactions aren't appropriate. This is also why (2) is not trivial: it claims that there is no such distinctively epistemic kind of blame.
I will now turn to the form of epistemic blame that can legitimately arise due to our epistemic answerability, and to my proposal of how this concept of epistemic blame might help us to understand the normativity of evidence.
Making the Normativity of Evidence Intelligible: A Proposal
If premise (1) is right-if evidence provides us with epistemic reasons for belief only if we can be blameworthy for violating purely epistemic norms-then a challenge for the normativist about evidence consists in spelling out the nature of the kind of blame that can be appropriate in response to purely epistemic failings, thereby allowing us to see why (2) is false.
There are, of course, other arguments against the normativity of evidence. In the concluding Sect. 5, for instance, I will mention the challenge of making sense of conflicts between purely epistemic norms and practical norms. A full defense of the normativity of evidence would require responding to such challenges as well. Furthermore, a full account of epistemic normativity would have to provide a justification of our epistemic practices-of why we are justified in having a practice of holding each other answerable to purely epistemic norms, responding with reactive attitudes to their violation, and so on. Here I will not provide such a full account. My more modest aim in this paper is rather to make room for the plausibility of a purely epistemic kind of normativity by showing how it reveals itself in our practice of holding each other answerable to epistemic norms. I will return to these issues briefly in the concluding Sect. 5 to clarify what this paper achieves, and what it doesn't.
To get epistemic blame into focus, I will distinguish between culpable and nonculpable violations of epistemic norms, and I will discuss briefly how different accounts about responsibility for belief evaluate both cases (Sect. 4.1). The kind of blame that is still appropriate in the non-culpable cases will then give us an idea about how a normativist about evidence could understand epistemic blameworthiness (Sect. 4.2). This will help us to evaluate cases of trivial belief in which a purely epistemic norm was violated (Sect. 4.3). The relevant concept of blame will allow us to make sense of the idea that evidence still provides us with reasons to believe when no practical value hinges on what we believe. The proposed view about the normativity of evidence allows us to see that epistemic norms have normative significance even without being hostage to practical value.
Blameworthiness for Non-culpable Violations of Epistemic Norms
Consider the following distinction between culpable and non-culpable violations of epistemic norms. There are violations of epistemic norms that we could have reasonably avoided (culpable), and violations which we could not have reasonably avoided (non-culpable). It seems that many deniers of human-induced climate change have plenty of evidence available that should rationally convince them that they are wrong if they would consider their evidence more carefully. Their epistemic norm violation is thus culpable. Like someone who commits a moral wrong for egoistic motives, these people fail to make an effort of will they owe to others by failing to consider their evidence. The epistemic norm violation has severe consequences for other people, and the culpable deniers could have reasonably avoided the violation. Due to this, it can be appropriate to react to them with moral blame, like resentment or indignation: they do not merely violate an epistemic norm, but also a moral norm of belief-management.
Compare the culpable denier of human-induced climate change with the nonculpable denier. The latter person might be someone who grew up in a community where human-induced climate change is denied by everyone even in the face of sufficient evidence. That is, even if members of this group are presented with clear evidence, they remain unconvinced. Consider one of these non-culpable deniers who was trained from an early age on to believe against the evidence when it comes to the topic of climate change. Careful consideration of the evidence is not anything that comes up as a reasonable course of action to this denier, nor can we reasonably expect this of them. Knowing the social background of the denier, we can say that they lost some authority over their beliefs when it comes to human-induced climate change. 16 This is why resenting them or being indignant does not seem to be appropriate.
Some recent accounts of responsibility for belief would argue that the non-culpable deniers are not blameworthy for their beliefs in any sense. They argue that our responsibility for belief is always derivative to our responsibility for actions and omissions prior to that belief by means of which we could have had some reasonable kind of influence or control over the belief (cf. Meylan, 2013Meylan, , 2017Peels, 2017)say, actions of inquiry or investigation, or of actively considering one's evidence. Consequently, if there was no reasonable course of action for our denier that would have led them to adopt a different doxastic attitude-as we stipulated -, then these accounts imply that our denier is blameless.
Interestingly, given premise (1) of the argument from doxastic blameworthiness, these accounts are committed to denying the normativity of evidence-i.e., they are committed to ANE. For their account implies that a person who holds a blameworthy belief had reasons for actions or omissions by means of which they could have avoided their belief. If so, then a violation of purely epistemic norms does never, by itself, make the person blameworthy. Rather, according to these accounts, blameworthiness presupposes that there were reasons for actions and omissions by means of which the person could have managed their belief. Given (1), ANE follows from this claim. 17 Other accounts of responsibility for belief would disagree, however. They would argue instead that even the non-culpable deniers might still be answerable for their beliefs (cf. Hieronymi, 2006Hieronymi, , 2008Hieronymi, , 2014Smith, 2005Smith, , 2015. That is, they argue that it might still be intelligible to request of them to justify their beliefs by asking them for the evidence they take to bear on whether there is human-induced climate change. In contrast to brute headaches, the deniers' beliefs still reveal an aspect of their overall epistemic character due to being rationally evaluable. That is, as long as we assume that the non-culpable denier's beliefs are not wholly unresponsive to reasons, there seems to be a sense in which we could still be justified to react with negative attitudes towards them if they are incapable of providing a satisfying reply to our request for evidence. According to Hieronymi (2009), although the non-culpable denier's beliefs are not under their indirect voluntary control, they might still be conceived of as being under their evaluative control: their beliefs might still be active responses to their reason-giving environment (even though they are non-voluntary responses that are irrational), and can thus legitimately give rise to serious forms of criticism or blame. This is not the place to decide which account of responsibility for beliefs-indirect control accounts or answerability-accounts-are right. Rather than deciding the dispute about what grounds our responsibility for belief, I will instead turn to my proposal about the nature of the blaming-responses that might still be appropriate towards the non-culpable deniers according to the answerability accounts. However, note that this will also pose a problem for indirect control accounts of doxastic responsibility. For if there is a kind of distinctively epistemic blame appropriate in the case of the non-culpable deniers, then they are epistemically blameworthy for their beliefs even though they could not have reasonably managed them by exercising indirect control. Most importantly for the present purposes, however, considering the nature of a purely epistemic kind of blame will give us a clue about how to understand the normativity of evidence. Hieronymi's (2004Hieronymi's ( , 2019 and Smith's (2013) approaches to the nature of blame are in line with Scanlon's (1998Scanlon's ( , 2008 account. According to this family of accounts of the nature of blame, blaming someone need not mean that one feels emotions like resentment or indignation towards the person. Rather, we might blame someone merely by modifying our relationship towards them in a certain way. We might blame a person without feeling any hostility towards them, e.g., by just ceasing to be friends, or by no longer providing special support to the blamee, or by not taking pleasure in their successes, or by not valuing their opinions in the way we did before, or by developing a general sense of distrust towards them. Recently, especially Boult (2020Boult ( , 2021 has applied these accounts to the epistemic domain. The following sketch of an account of epistemic blame draws on his ideas. 18 Importantly, not all relationship modifications count as instances of blame. First, one might modify a relationship in a positive way, say, when one becomes so fond of someone that one wants to be closer friends with them; or when a parent finds out that their child committed a crime and in response to this cares even more about them (Smith, 2013, 137). Secondly, relationship modifications can happen without negative judgment about another person-as when people who live in different places just drift apart. Scanlonian approaches to blame thus owe us an account of what makes a negative relationship modification an instance of blame. 19 18 Cf. his cited works for a detailed defense. Other accounts of epistemic blame have been worked out by Kauppinen (2018), who also presents an account of epistemic criticism as a form of distrust, and by Brown (2020), who also shares the spirit of Boult and Kauppinen in that she regards epistemic blame as being neither a mere negative evaluation nor a kind of strong reactive emotion (like resentment). However, Brown builds on Sher's (2006Sher's ( , 2009 account of blame in order to spell out an epistemic kind of blame. Neither Kauppinen nor Brown put relationship modifications at center stage. Cf. Boult (2021) for a detailed discussion and critique of Brown's account. 19 In response to Smith's case mentioned in the paragraph above, Boult (cf. 2021, 17) argues that genuine blaming reactions are those that are based on the judgment that the person is blameworthy. However, a problem with this proposal is that it does not tell us what our judgments about blameworthiness are based on. My proposal (that I explain in the next paragraph) avoids this problem: our judgments of blameworthiness are responses to the blamee's vice. Furthermore, it seems that the parent in Smith's case regards their child as blameworthy without blaming them. I think Smith's case can be met simply by restricting blaming responses to negative relationship modifications. Maybe Smith's (2013) proposal that blaming responses are expressions of one's protest is compatible with my proposal that they are based on Negative relationship modifications count as instances of blame only if they are responses to the person's vice. I do not count as blaming my friend by judging and treating them as unreliable, and by modifying my expectations accordingly, if I am aware that their unreliability is due to factors that do not stem from their faulty character. Such factors might include their newborn child that makes them spontaneously cancel on me, or their depression that is the cause for their unreliability. Such factors do not give me a reason not to trust them, but merely a reason not to rely on them. By contrast, it might be legitimate to blame a friend if their unreliability indicates that they do not care about the friendship as much as one can reasonably expect of them as a friend. In this case, they are not fully honest about their attitude towards the friendship. Reducing one's trust in them, and thus modifying one's relationship with them negatively in response to their vice of dishonesty, can be legitimate. 20 Negative relationship modifications in response to vices can plausibly count as blaming responses because they are only legitimate towards responsible beings. This is because we can only have the specific kind of relationship that is presupposed by these reactions with fully responsible beings. Neither computer nor children or animals can display vices that give rise to the negative reactions described above. Their misbehavior can only give rise to impoverished analogues of these reactions. For instance, I might "not trust" a dog in the sense that I suspect that they will bite me. The dog's behavior might be unreliable, but it won't give me a reason to blame the dog, since the dog's behavior does not manifest a vice (on the assumption that dogs cannot have full-blown vices like fully responsible beings). This indicates that negative relationship modifications in response to vices presuppose a subject's responsibility for their character and attitudes. At the same time, the appropriateness of these reactions does not presuppose that the subject could have managed their character or attitudes: these reactions merely presuppose an underlying vice, independently of its origin in voluntary conduct. Since these reactions presuppose responsibility, their potential "coolness" does not, pace Wallace (2011), count against them as genuine blaming-reactions (cf. Boult, 2020). 21 epistemic vice-maybe epistemic blame expresses protest against epistemic vices. However, cf. Boult (2021) for some skepticism about the applicability of Smith's account to the epistemic domain.
Epistemic Blame, Relationships, Vices, and Trust
Footnote 19 (continued) 20 Cf. Smith's (2005, 242) case from George Eliot's Scenes of Clerical Life (1858), where Captain Wybrow fails to notice that Miss Assher never takes jelly, which, according to Smith, "suggests to Miss Assher that she does not yet occupy a distinctive place in his overall emotional and evaluative outlook" (2005,243). Assher might legitimately modify her expectations towards Wybrow, and thus modify the relationship negatively, in response to Wybrow's vice of not caring about the relationship as much as he should. According to the proposed account, this would count as an instance of blame even if it does not involve emotions of resentment or indignation. 21 An anonymous referee objected that negative relationship modifications might merely count as ways of holding responsible, but not of ways of blaming. This raises the question of how full-blown moral blaming responses like resentment and indignation relate to the "softer" Scanlonian negative reactive attitudes. For my purposes here, it is sufficient to note that if we hold a person responsible in the Scanlonian sense, this can provide the basis for a positive or a negative relationship modification in response to virtue or vice. For instance, we might want to be closer friends because of the person's virtues, or we might reduce our involvement with the person due to their vices. I take it to be of secondary interest whether we call these reactions "praise" and "blame". At the very least, they seem to be positive and negative ways of holding responsible. This is sufficient for these reactions to reveal the normative sig-As David Owens puts it, after discussing the epistemic vice of gullibility: when I display a vice indicating a flaw in my character, then "I cannot be trusted to think and feel as I ought" (2000,124). The normativity of these "oughts" is revealed, according to view I propose, by the fact that violating them impairs our relationship to others in specific ways so that it becomes appropriate to negatively modify one's relationship-e.g., by reducing one's presumption of epistemic trust. This impairment exists even if the person had no opportunity to manage their vice: as long as the epistemic vices are still genuine vices (rather than pathologies), non-culpable violations of epistemic norms that reveal a person's epistemic vice can impair our epistemic relationships, and thus give rise to suspension of epistemic trust.
If we allow for a broad concept of blame in terms of impaired relationships, then we might be able to make room for something like purely epistemic blameworthiness. In an initial attempt, we might state that if we are blameworthy morally as soon as our relationship to our moral community is impaired, then we are blameworthy epistemically as soon as our relationship to our epistemic community is impaired. This impairment might matter in specific ways for how we should relate to one another: whether we believe the other person, whether we provide them with information, and whether we engage with them in rational discourse.
One problem with this initial formulation is that one's moral or epistemic community can be epistemically or morally flawed, and thus one might end up impairing one's relationship with them by being morally or epistemically virtuous. 22 Boult's (2020) formulation of the position avoids this problem: one is blameworthy epistemically only if one falls short of the normative ideal of an epistemic relationship-or, in my preferred terminology, only if one displays an epistemic vice. The epistemically virtuous person does not fall short of this ideal even within an epistemically flawed community. Thus, members of the community won't have a reason to reduce their epistemic trust in the virtuous person. By appealing to the normative ideal of an epistemic relationship, we can explain why being dogmatic or gullible, engaging in wishful thinking, or being biased can make one epistemically blameworthy even in epistemic communities that socially reward such vices. For all these vices are, as Boult puts it, problematic ways of exercising one's epistemic agency that make one fall short of the normative ideal and thus warrant suspension of one's presumption of epistemic trust. 23 Footnote 21 (continued) nificance of a norm that we mark as violated by reacting in these ways. For defenses of such reactions as genuine blaming responses, cf. the recent works that argue that these reactions count as blame because they go hand in hand with, or consist in, a kind of motivation-a desire that the blamee had not "believed badly" (Brown, 2020), a protest against the blamee's action or attitude (Smith, 2013) or just generally the motivation to change one's relationship with them by modifying one's expectations and intentions (Boult 2021). 22 I am grateful to an anonymous referee for making me aware of this problem. 23 I take it that Boult does not use "epistemic agency" as referring to indirect voluntary control over beliefs. Plausibly, one can be dogmatic, gullible, a wishful thinker or biased even if this was not under one's indirect voluntary control. Rather, beliefs-including irrational ones-are often involuntary responses to one's environment (cf. Strawson, 2003). Boult's notion of epistemic agency is more plausibly understood in terms of Hieronymi's (2009) notion of evaluative control.
Blameworthiness for Non-culpable and for Trivial Violations of Epistemic Norms
Let us apply this sketch of an account of epistemic blame to our two relevant cases: non-culpable violations and trivial violations of epistemic norms. In both cases, it seems as if passionate forms of moral blame, like resentment or indignation, are no longer appropriate. Importantly, however, reducing our presumption of epistemic trust for failing to live up to the normative ideal of an epistemic relationship might still be appropriate. This will allow us to see that we already take epistemic norms to be normatively significant: we are already committedly involved in epistemic sociality. 24 Our actual practice of holding each other answerable to purely epistemic norms presupposes their normative significance insofar as we express this significance in our reactive attitudes towards norm violators. The non-culpable deniers of climate change might still be manifesting an epistemic vice, a defect in character, which we might label "epistemic irrationality". 25 Note first that their epistemic irrationality is attributable to them in the sense that it is part of their overall outlook on the world, rather than just an occasional lapse which we could excuse. It is thus a genuine vice. Secondly, our non-culpable norm violators are still answerable for their beliefs insofar as it is intelligible to request their evidence for their beliefs. For we conceived of the case in such a way that their disbelief is still rationally evaluable rather than pathological: we assumed that their belief is irrational in the sense that they are aware, on some level, of the evidence against their belief, but they still fail to respond correctly to their overall evidence due to epistemic vices like dogmatism, gullibility, or a tendency for wishful thinking. Our epistemic blame directed at the non-culpable deniers is based on our judgment that they cannot give a satisfying answer to our request for evidence, even though the evidence is readily available to them. As a result, we have a reason to suspend our presupposition of epistemic trust towards them. 26 What is the verdict, according to this account of epistemic blame, about our blameworthiness for trivial belief that is insufficiently supported by one's evidence? The normativist about evidence has two strategies available. Both strategies can be combined.
First, normativists could argue that even violations of epistemic norms in trivial matters might indicate a general flaw in the epistemic character of a person. As Boult puts it when evaluating trivial cases, "[s]o long as I modify my intentions and expectations towards them, in a way made fitting by the judgment (however implicit) that they've impaired the general epistemic relationship, then I count as epistemically blaming them" (Boult, 2020, 9). That is, if your friend tends to believe celebrity gossip that they read in a magazine they know to be unreliable, this might give you a (pro tanto or prima facie) reason to suspend epistemic trust in them. Presumably, this could mean that you should suspend your trust in some situations when it comes to matters of importance, because you now have some evidence that their epistemic character is flawed.
Secondly, the normativist can just grant that violations of epistemic norms do not always make it appropriate to suspend trust. For they need not argue that such violations always make one epistemically blameworthy. In order to disprove premise (2), it is enough to show that we are sometimes blameworthy in virtue of the fact that we violated a purely epistemic norm. More generally, violating a reason-providing norm need not amount to displaying a criticizable vice, and thus need not amount to blameworthiness. Compare the idea that someone's morally wrong action is not necessarily blameworthy. We all act wrong from time to time, and we all violate epistemic norms from time to time. We can usually excuse each other for occasional lapses and do not regard these lapses as having any significant consequences for our interpersonal relationships. Yet moral wrongs and violations of epistemic norms are lapses nevertheless-i.e., they are violations of norms that provide us with reasons for compliance.
Seeing that reducing epistemic trust is an appropriate negative response to an epistemic vice and that it marks the impairment of an epistemic relationship provides us with a plausible starting point for understanding the significance of epistemic normativity. It allows us to meet the challenge for the normativity of evidence presented in this paper by rejecting premise (2). This challenge claims that the absence of a distinctively epistemic kind of blame rules out the normativity of evidence. I have proposed that we can meet this challenge by appealing to recent accounts of doxastic responsibility as answerability and to recent accounts of epistemic blame. The former accounts show us that non-culpable beliefs might still be blameworthy. The latter accounts provide us with an idea about what this blameworthiness could consist in, and how it could sometimes extend also to cases of trivial belief. By building on Boult's account, I have suggested that epistemic blame consists in marking impaired epistemic relationships by reducing epistemic trust in response to a person's epistemic vice.
Conclusion and Outlook
The dispute about the normativity of evidence is a currently lively discussion within epistemology. 27 There is no need right now to settle the dispute once and for all. This paper has contributed two ideas towards bringing the debate forward: 27 Cf. also the recent discussion about the normativity of epistemic reasons. Cf. Kiesewetter (forthcoming) for an overview over this debate and defense of the normativity of epistemic reasons. According to Kiesewetter, some instrumentalists or pragmatists are best read as making room for a notion of a nonnormative epistemic reason, rather than as denying the existence of epistemic reasons altogether. My terminology here does not allow us to distinguish between these two positions, because I used 'epistemic reason' exclusively in a normative sense.
(a) That a central challenge in defending the normativity of evidence consists in spelling out a notion of a distinctively epistemic kind of blame. (b) That appealing to epistemic blame as marking an impaired epistemic relationship by suspending epistemic trust in response to epistemic vices is a promising way for defending the distinctive normativity of evidence in the sense required by this challenge.
Together, both claims shift the dialectical burden towards ANE. Proponents of ANE argue that purely epistemic norms do not provide us with reasons to believe. But if epistemic blame marks the violation of purely epistemic norms with reason-providing force, then proponents of ANE must say that there is no such thing as a distinctively epistemic kind of blame. However, recent approaches on doxastic responsibility as answerability (Hieronymi, Smith), as well as recent works that spell out the nature of a distinctively epistemic kind blame or criticism (Boult, Brown, Kauppinen), call this into doubt. As a result, proponents of ANE need to engage with these theories: they have to show why the appropriateness of the blaming-reactions that these theories spell out does not imply that a norm with reason-providing force was violated; or else argue that these reactions are not appropriate in response to violations of purely epistemic norms. However, I have suggested in Sect. 4 that violations of epistemic norms in non-culpable and trivial cases can well deserve suspension of epistemic trust if they are manifestations of epistemic vice. The presented analysis of these cases thus calls into doubt ANE by revealing a purely epistemic kind of blame that might be appropriate in these cases-a blame that reflects the normative significance we attach to purely epistemic norms. However, this does not yet provide us with a full account of epistemic normativity. I will now briefly explain what I think such an account requires, at a minimum. This will reveal the restrictions of the present inquiry. At the same time, it illustrates how the approach presented in this paper might be fruitfully developed to a fuller account of epistemic reasons.
The first requirement for a full account of epistemic normativity is that it must allow us to meet other challenges for the normativity of evidence. For instance, how do normativists about evidence deal with cases in which complying with an epistemic norm causes practical disvalue-for instance, cases in which others will suffer harm unless I make myself violate an epistemic norm? The proposed view about epistemic blame might help us to make sense of the traditional verdict that I ought epistemically to comply with the epistemic norm even though I ought practically to bring myself not to comply with it. Proponents of ANE will argue that the first "ought" cannot by normatively authoritative in any interesting sense. The proposed view, by contrast, allows us to say that the first epistemic "ought" has still a kind of normative authority insofar as the normative significance of this "ought" is expressed in the fact that members of one's epistemic community might be justified in modifying their trusting attitude towards me if I do not comply with it. That is, even if I bring myself to violate an epistemic norm for good practical reasons, I might end up not being trustworthy epistemically due to the resulting ill-based belief. This will hold at least in cases where my resulting ill-based belief reflects an epistemic vice. However, the discussion about such cases is currently very alive, and this paper has no ambitions meeting this and further possible challenges. 28 Secondly, this paper did not provide an account of the source of epistemic normativity. My appeal to our actual practice reveals that we treat each other as answerable to epistemic norms, and thus that we attach normative significance to these norms. But this does not justify our commitment to the overall epistemic practice. Indeed, the view proposed here is even compatible with a pragmatic foundation of purely epistemic norms: maybe we are justified to engage in our epistemic practice because it is practically valuable to be subject to epistemic norms (cf. Owens, 2017). Combined with such a pragmatic justification of our overall practice, normativists about evidence could maintain that within this practice, all reasons for belief are provided by our evidence, and that pragmatic considerations are only relevant if we wish to externally justify our adherence to this purely evidential kind of normativity. 29 This might be an important element in a complete error-theory about pragmatist-instrumentalist intuitions concerning reasons for belief. | 15,356.6 | 2021-06-14T00:00:00.000 | [
"Philosophy"
] |
Tumor microenvironment-responsive fenton nanocatalysts for intensified anticancer treatment
Chemodynamic therapy (CDT) based on Fenton or Fenton-like reactions is an emerging cancer treatment that can both effectively fight cancer and reduce side effects on normal cells and tissues, and it has made important progress in cancer treatment. The catalytic efficiency of Fenton nanocatalysts(F-NCs) directly determines the anticancer effect of CDT. To learn more about this new type of therapy, this review summarizes the recent development of F-NCs that are responsive to tumor microenvironment (TME), and detailedly introduces their material design and action mechanism. Based on the deficiencies of them, some effective strategies to significantly improve the anticancer efficacy of F-NCs are highlighted, which mainly includes increasing the temperature and hydrogen peroxide concentration, reducing the pH, glutathione (GSH) content, and the dependence of F-NCs on acidic environment in the TME. It also discusses the differences between the effect of multi-mode therapy with external energy (light and ultrasound) and the single-mode therapy of CDT. Finally, the challenges encountered in the treatment process, the future development direction of F-NCs, and some suggestions are analyzed to promote CDT to enter the clinical stage in the near future. Graphical Abstract Supplementary Information The online version contains supplementary material available at 10.1186/s12951-022-01278-z.
Introduction
Malignant tumor is one of the main causes of death in the world. It has become a major disease that seriously endangers human life and health and restricts social and economic development [1,2]. Traditional methods of cancer treatment mainly include surgical resection, radiotherapy, and chemotherapy [3,4]. However, conventional treatments have many limitations (such as low selectivity, easy recurrence, large side effects, and so on) [5]. Fortunately, nanotechnology shows great potentials to improve the anticancer effect and reduce the side effects, and various nanomedicines are widely applied to different new therapeutic methods, including hyperthermia therapy, sonodynamic therapy (SDT), immunotherapy, and chemodyanic therapy (CDT) [6]. Among them, CDT has attracted much attention in recent years due to its strong oxidative lethality to cells and specific suborganelles [7].
CDT is an emerging and minimally invasive cancer treatment, it is defined as the transformation of endogenous H 2 O 2 through Fenton or Fenton-like reactions into highly harmful hydroxyl radical (•OH), which is known as the most oxidizing reactive oxygen species (ROS), and can induce massive apoptosis of tumor cells by damaging DNA and inactivating proteins [8]. Compared with normal cells, cancer cells have a unique way of proliferation, metabolic activity, and mitochondrial dysfunction so that the tumor tissue has a unique structure and physical properties. Especially, the content of hydrogen peroxide (H 2 O 2 ) in tumor tissues is far higher than that of normal tissues [9]. CDT relies on the higher expression of H 2 O 2 in tumors, so this method is highly selective and
Graphical Abstract
can reduce the damage to normal tissues [10,11]. However, the low efficiency of CDT limits its potential clinical applications.
Fenton and Fenton-like reactions are the basis of CDT, which determine the efficiency of this treatment, the equation of Fenton reaction is shown in Fig. 1a [8]. The discovery of Fenton reaction comes from the British scientist H. J. H. Fenton. In 1983, he first proved that H 2 O 2 in acidic environment has the ability to oxidize various organic substances under the catalysis of iron ions, and this technology has widely applied to the field of wastewater treatment [12]. Inspired by this technology, various metals with Fenton-like effect have been developed and applied to cancer treatment, such as Au [13], Ag [14], Cu [15], Mn [16], and so on. However, the tumor is not the best place for Fenton reaction, which greatly reduces the efficiency of CDT. To improve the therapeutic effect of chemical kinetics, three conditions must be met to produce sufficient hydroxyl radicals (•OH). First, sufficient hydrogen peroxide concentration. The concentration of H 2 O 2 in the tumor microenvironment (TME) is not enough to continuously produce •OH [17]. Therefore, increasing the level of H 2 O 2 in the TME is the main method to solve this problem. Second, the generation rate of •OH must be fast enough to produce strong oxidation to the tumor in a short time, so as to avoid the resurrection of cancer cells. The generation rate of •OH can be adjusted by changing the reaction conditions (such as temperature and pH) and optimizing the structure and composition of F-NCs [18,19]. Third, •OH produced by Fenton or Fenton-like reactions should attack cancer cells directly as much as possible, rather than being captured by reducing substances in the TME, such as (GSH) [20].
In addition to the above strategies, another direct way to improve the therapeutic effect of CDT is multi-mode therapy. For example, CDT combined with photothermal therapy (PTT), photodynamic therapy (PDT), or SDT. The combination of CDT and PTT can be realized by using F-NCs with photothermal conversion ability. In the combined treatment of CDT/PTT, the temperature of TME can be increased to accelerate the catalytic effect of Fenton reagents and finally enhance the therapeutic effect of CDT. The combination of CDT/PDT is mainly realized by loading photosensitizer on Fenton reagent, or the transition metal ions with Fenton or Fenton-like effect are coordinated and self-assembled with photosensitizers which can increase the concentration of ROS in TME under the excitation of light [21,22]. PDT and PTT both use light as external energy to enhance the therapeutic effect. However, the fatal disadvantage of light in the treatment process is the low maximum penetration depth in the body (about 10 mm), which greatly restricts the application of PDT and PTT [23]. In order to overcome the defect of insufficient penetration ability of light in the body, researchers use ultrasound (US) to replace light and the maximum penetration depth of ultrasound is about 10 cm (Fig. 1b) [20]. It is possible to combine SDT and CDT to treat deep tumors in vivo, which solves the defect of CDT that cannot produce ROS continuously.
In recent years, the new applications of F-NCs in cancer treatment make the Fenton reaction, an ancient The light penetrates to a depth of 10 mm, which just only be used for the treatment of shallow tumors, while ultrasound can be used for the treatment of deep tumors with a tissue penetration depth of 10 cm, which can reach to major organs in the body. Although the penetration depth of radiation is deeper than the light and US, it can cause damage to the normal tissue reaction, flourish again. However, CDT is still in the preliminary stage with some deficiencies to overcome. This paper elaborates the preparation process and mechanism of F-NCs in detail and summarizes the recent development of F-NCs applied to cancer treatment. According to the shortcomings of F-NCs, some strategies that can improve the anticancer effect of them have been proposed. Especially, the applications of F-NCs in other therapeutic methods are summarized and the development directions of them in the future are prospected.
This review aims to improve researchers' understanding of F-NCs (such as reaction conditions, properties, and mechanisms). More importantly, it provides some important strategies for improving their therapeutic efficiency.
Classification and featured chemistry of F-NCs
CDT, based on the weak acid of TME as reaction condition, uses H 2 O 2 as raw material and transition metal nanomaterials as the catalyst to initiate Fenton or Fenton-like reactions in cancer cells so as to catalyze H 2 [24][25][26]. In addition, Mn 2+ , Ti 3+ , and Cu + can also catalyze the decomposition of H 2 O 2 to produce ROS, which is called Fenton-like reaction [27]. Catalysts play a crucial role in Fenton or Fenton-like reactions, so the design of catalysts is very important. The preparation of different kinds of F-NCs will be described in detail in the following subsections.
Fe-based F-NCs
Iron element is widely present in various tissues and organs of the human body, which plays a significant role in oxygen transport, glucose metabolism, and ATP generation, and shows superior biocompatibility. Therefore, iron-based materials have been widely used in the biological field and show high biosafety [28]. Moreover, iron-containing F-NCs have special magnetic properties and are effective contrast agents for magnetic resonance imaging (MRI), which can enhance the detection of tumor lesions in vivo [29]. Based on these advantages, Fe-based F-NCs have been extensively studied in CDT.
Iron oxide nanomaterials are an important part of Febased F-NCs, which are widely used in CDT [30]. More importantly, they also play a positive role in regulating TME and tumor metabolism and promoting tumor therapy. A recent Fe-based Fenton nanocatalyst involving Fe 3 O 4 nanoparticles (FeGd-HN@Pt@LF/RGD 2 NPs) showed significant anti-tumor effects [31]. In this system, the cis-platinum (CDDP) was loaded on Fe 3 O 4 /Gd 2 O 3 hybrid NPs, and modified the hybrid NPs with lactoferrin (LF) and RGD dimer (RGD 2 ), as shown in Fig. 2a. The LF on the surface of these NPs could help FeGd-HN@ Pt@LF/RGD 2 nanoplatform cross the blood-brain barrier and then this nanoplatform could be specifically internalized by cancer cells upon integrin αvβ3 binding. The released Fe 2+ and Fe 3+ directly participated in the Fenton reaction, while CDDP indirectly produced H 2 O 2 in cancer cells, strengthening the Fenton response in cancer treatment. The specific therapeutic mechanism of the FeGd-HN@Pt@LF/RGD 2 nanoplatform is shown in Fig. 2a. According to the in vivo experiment, Fig. 2b showed that FeGd-HN@Pt 2 @LF/RGD 2 NPs can significantly extend the survival of tumor-bearing mice. In addition, ultrafine Fe 3 O 4 NPs are also known as superparamagnetic iron oxide NPs (IONPs), which are good MRI T2 contrast agents for intravenous administration. It has unique advantages for cell labeling in vivo tracer experiments [32]. For example, an "all-in-one" Fe 3 O 4 /Ag/Bi 2 MoO 6 (FAB) nano platform can be used as an MRI contrast agent, which is helpful to observe the pharmacokinetic characteristics of FAB NPs and determine the optimal treatment time [33]. In brief, FAB NPs were synthesized by three steps, including hydrothermal synthesis of Bi 2 MoO 6 NPs, photoreduction of Ag NPs, and solvent doping of Fe 3 O 4 together with a surface covering of hydrophilic polyvinylpyrrolidone (PVP), as shown in Fig. 2c. In this work, the incorporation of Fe 3 O 4 and Ag could enhance the photocatalytic activity, ferromagnetic and photothermal effect of UV-adsorbing Bi 2 MoO 6 NPs. Moreover, Fe 3 O 4 endowed FAB NPs with the Fenton effect and the ability of MRI. Finally, FAB NPs could highly inhibit tumor growth, which was attributed to the synergy between CDT/PTT/PDT, as well as the sustainable and self-complementary anti-tumor strategy caused by the coupling effect between cascaded nano catalytic reaction and multi-enzyme activity, as shown in Fig. 2c.
In addition to iron oxide nanomaterials, some ironcontaining metal-organic frameworks (MOFs) nanocatalysts also have a good Fenton effect and have been applied in cancer treatment. Compared with iron oxides, iron-containing MOF has better flexibility, responsiveness, and dispersion. Moreover, MOF has a better ability to penetrate cell membranes, which can enhance the treatment effect or imaging capability on the basis of enhancing permeability and retention effect (EPR) [34]. Recently, an iron-containing MOF(Fe) nanosystem (NH 2 -MIL-88B(Fe)) with catalase activity was fabricated to inhibit autophagy and enhance ROS-induced oxidative damage [35]. The structure and catalytic mechanism of NH 2 -MIL-88B (Fe) are shown in Fig. 3a. These NCs could promote the generation of highly oxidized •OH in cancer cells under an acid environment, among which chloroquine is a classical autophagy inhibitor. As can be seen in Fig. 3b, the results of the combined effect of chloroquine and NCs on cancer cells and normal human cells verified that chloroquine and NCs could synergistically enhance the anticancer effect compared with chloroquine and NCs alone. Because the synergetic therapy could effectively block autophagy so that cancer cells cannot extract their own components to detoxify and enhance their own metabolism, and eventually die from the strong oxidation of ROS under the catalysis of NCs. In human umbilical vein endothelial cells (HUVECs), the negligible effect of single MOF(Fe) therapy or synergistic therapy indicated that MOF(Fe) had high therapeutic specificity due to the absence of H 2 O 2 in normal cells. MOF-Fe composites have different morphology and composition, which consequently results in higher catalytic activity [36]. However, MOF-Fe nanomaterials also have some disadvantages. For example, the activation of their catalytic activity has high requirements on the existing environmental conditions. The pH in the TME is 6.5-7, while the catalytic activity of MOF-Fe is extremely low in this physiological environment, which will limit the scope of its biological applications [37]. Some studies have shown that MOF-Fe catalysis of Fenton reaction can only be carried out in acidic media (pH is 2.0-5.0) [38]. To solve this problem, researchers designed pH-responsive MOFs that can regulate the TME. For example, an iron-containing MOF (Fe 2+ ) nanosystem that contained dichloroacetic acid (DCA) can break the limitation of pH [38] (Fig. 3c). DCA is an analog of acetic acid, which can not only reduce the mitochondrial membrane potential but also participate in the oxidation of glucose and increase the concentration of H 2 O 2 in the tumor. Moreover, DCA is a strong organic acid with a pKa value of 1.35. The addition of DCA could regulate the pH in the TME, activate the maximum catalytic activity of MOF-Fe 2+ NPs on the Fenton reaction in the tumor, and decompose H 2 O 2 in the tumor to produce more toxic ROS. Liposomes were coated on the surface of MOF-Fe 2+ NPs, which can increase their solubility. Figure 3d indicated that MOF-Fe 2+ -DCA@Liposomes NCs (MD@Lip NCs) have low biological toxicity. More importantly, the combination of DCA and MOF-Fe 2+ could highly improve anticancer efficacy.
The introduction of organic acids to regulate TME is an innovative idea, but the precise control of the number of organic acids is a major problem in the research. Therefore, in addition to adding acidic substances that can regulate the TME to the NCs, the catalytic activity of F-NCs in the TME can also be increased by improving their properties. Recent studies have shown that zero-valent iron (Fe(0)) is a more active F-NC and has been used for wastewater decontamination [39,40]. However, due to the unstable chemical properties of nanoscale Fe(0), which is easy to be oxidized, it is necessary to construct a stable nanoplatform that can effectively transport Fe(0). Liang et al. [41] In addition to the iron-based nanomaterials described above, other iron-containing nanomaterials have also been used for cancer treatment, such as natural biomineral ferrihydrite [42], ferric hydrogels [43], iron sulfides [44], and organometallic compounds ferrocene [45]. Here, the representative F-NCs in recent years are summarized, as shown in (Additional file 1: Table S1).
Mn-based F-NCs
Compared with iron oxides, manganese oxides have a stronger oxidation capacity, so manganese oxide NCs have more advantages in consuming GSH in tumor cells. Similar to Fe 2+ , Mn 2+ is also an effective contrast agent for T1-weighted magnetic resonance imaging (T1-MRI) for tumor detection, allowing real-time detection of the distribution of nano-catalysts in vivo [46,47]. Mn is an essential trace element for the human body, and Mn 2+ is a water-soluble ion that can be rapidly excreted through the kidneys. Based on these advantages, Mn-based nanomaterials are also used as NCs with a Fenton-like effect in cancer treatment.
MnO 2 is an important component of Mn-based NCs. MnO 2 can undergo a redox reaction with GSH in the body to reduce the level of GSH in cancer cells and produce Mn 2+ . Mn 2+ can catalyze the decomposition of H 2 O 2 to produce ROS and induce apoptosis of cancer cells. For example, Liu et al. [48] used liquid metal (Lm: 75%Ga and 25%In) NPs as templates to design a yolk-shell structure of Lm@MnO 2 (LMN). LMNs were then loaded with cinnamaldehyde (CA) to form CLMN and further coated with hyaluronic acid (HA) to construct CA&LM@MnO 2 -HA nanoflowers (CLMNF) for cancer targeted therapy. CLMNF particles rapidly consumed GSH and produced Mn 2+ , which further promoted the conversion of H 2 O 2 to ·OH to intensify the death of cancer cells. Besides, LM endured the NPs with good near-infrared photothermal conversion ability. The composition and therapeutic mechanism of CLMNF NPs in vivo are shown in Fig. 4a. Figure 4b proved that the combination of CLMNF and NIR could make cancer cells apoptosis efficiently, and the tumor in mice could be basically eliminated, due to the combined action of PTT/ CDT. Yang et al. [49] also verified that the combination of MnO 2 and other metals has the function of multi-mode therapy. MnO 2 and ultra-small gold NPs were deposited on mesoporous silica nanorods, and subsequently, a MnO 2 -Au@SiO 2 nano-reaction platform with multimodal imaging synergism to improve O 2 content and heat sensitivity in tumors was prepared. MnO 2 could catalyze the decomposition of H 2 O 2 to produce ROS, and Au could stably and efficiently oxidize glucose in TME, thus making tumor cells sensitive to thermal ablation, as shown in Fig. 4c. Comparing the liver and kidney function indicators of mice injected or not injected with MnO 2 -Au@SiO 2 , it is indicated that this nanoplatform had a good hepatic and kidney safety profile. More importantly, this nanoplatform could effectively promote cancer cell apoptosis, as can be seen in Fig. 4d. It is suggested that the combination of MnO 2 nanomaterials and other metals to construct a multifunctional nano platform to induce oxidative/heat stress damage in cancer cells is expected to be an effective anti-cancer treatment strategy.
In addition to MnO 2 NCs, bimetallic manganese oxides with anoxic structures have excellent therapeutic effects. The hypoxic structure can be used as an electronic trap to prevent electron-hole recombination, improve the quantum yield of ROS, and release Mn 2+ that can catalyze the decomposition of H 2 O 2 in solid tumors to improve the therapeutic effect. Constructing anoxic structures to improve the production of ROS is a method that has been less studied at present, and it is highly innovative. An ultra-small bimetallic oxide MnWO x nano platform prepared by Gong's group displayed a strong ability of ROS generation due to the hypoxic structures in MnWO x , which provided electron capture sites to prevent electron-hole recombination (Fig. 4e) [50]. Moreover, MnWO x could consume GSH in tumors, release Mn 2+ in an acidic environment and further increase the level of ROS, finally realizing the combination of CDT and SDT. According to the in vivo study, the synergy of CDT and SDT can highly improve the antitumor ability (Fig. 4f ). In this nanoplatform, the Mn and W elements enable MnWO x NPs to display considerable contrast in magnetic resonance and computed tomography imaging, which could be used to track the accumulation of NPs in animals. Moreover, the size of MnWO x NPs is very small with an average diameter of 5.74 ± 1.66 nm, which could be rapidly metabolized in mice. The level of W in vivo was measured by inductively coupled plasma emission spectrometry. After 30 days, the retention rate of W is less than 1.7% ID g −1 . The results in Fig. 4g indicate that MnWO x -PEG is a safe sonosensitizer, which has Fenton catalytic ability and no retention in the mice body.
In addition to manganese oxide and bimetallic manganese oxide NCs, there are some other manganese-related NCs with the Fenton effect. Here, we summarize the recent advances in manganese nano catalytic materials for the treatment of cancer, as shown in (Additional file 1: Table S2).
Other metal-based F-NCs
In addition to Fe-and Mn-based Fenton reagents, other metals have also been used to catalyze Fenton-like reactions, such as Ti [51], Cu [52], Ag [53], V [54], Pt [55], Co [56], Ru [57] and Au [58], etc. For Cu-based NCs, the MOF derivatives of Cu [59], sulfides of Cu (such as CuS [60] and Cu 2-x S [61]), copper oxides (such as CuO [62,63] and Cu 2 O [64]), and copper bimetallic compounds (such as CuSe) [65], are used as catalysts of Fenton-like reactions. Compared with the traditional Fe-based F-NCs, due to the inherent microenvironment response behavior and high biocompatibility of Febased F-NCs, the degradation ability of Fe-based F-NCs in vivo is stronger than that of Cu-based F-NCs, and the retention time in vivo is shorter and easier to be discharged from the body [66]. Although some Cu-based F-NCs have been preliminarily proved to be biocompatible, the high accumulation of Cu may cause potential toxicity problems. Therefore, generally speaking, the biological toxicity of Fe-based F-NCs is lower than that of Cu-based F-NCs, so it was considered that the use of Cu-based F-NCs in biomedicine was relatively limited in early times. However, with the improvement of scientific research and technology, researchers found that transition metal Cu plays an irreplaceable role in the biomedical field, such as Cu can enhance angiogenesis and affect liposome/glucose metabolism [67]. The physical and chemical properties of Cu-based F-NCs can meet the needs of various biomedical applications. For example, Cu-based chalcogenides have strong absorption in the near-infrared window and have a photothermal/photodynamic effect. The photothermal effect can induce tissue expansion, which is conducive to the application of Cu-based F-NCs in photoacoustic imaging (PA) and PTT. In addition, Cu-based F-NCs have (See figure on next page.) Fig. 4 a Diagram of the composition and therapeutic mechanism of CLMNF nanoparticles [48]. b The relative tumor volume, tumor weight, and photographs of tumor tissues of CT26 tumor-bearing mice with various treatments (n = 6, mean ± SD ***p < 0.001). Reproduced with permission. [48] Copyright 2020, Wiley-VCH. c The therapeutic mechanism of MnO 2 -Au@SiO 2 nanoplatforms in solid tumors [49]. d In vivo toxicology assessment of MnO 2 -Au@SiO 2 NPs; the relative tumor volume and photographs of tumor-bearing mice and tumor tissues from tumor-bearing mice after different treatment. Reproduced with permission. [49] Copyright 2020, Tsinghua University Press and Springer-Verlag GmbH Germany, part of Springer Nature. e The mechanism of MnWO x leads to increase ROS production [50]. f Schematic of the in vivo SDT procedure on mice and fluorescence images of DCFH-DA-stained tumor slices collected from mice 24 h post-treatment and tumor growth curves and average weights of tumors after various treatments [50]. g Distribution of W levels in mice at different times based on inductively coupled plasma measurement. Reproduced with permission. [68][69][70]. Based on these advantages of Cu, more and more Cu-based F-NCs have been used in cancer treatment in recent years. However, whether Cu-based F-NCs can enter clinical applications ultimately still depends on their toxicity. Fortunately, many Cu-based F-NCs prepared in recent years have been proved to be low toxic or even non-toxic, with high biocompatibility and biosafety. The key to reducing the biological toxicity of Cu-based F-NCs is to avoid the release of copper ions in Cu-based nanosystems before the materials exert their properties. Amphiphilic liposomes are widely used in material modification and drug loading due to their good biocompatibility and low toxicity, Amphiphilic liposome encapsulation of Cu-based F-NCs can hinder the premature release [61]. d The tumor volume and tumor weight growth of nude mice on 14th day, the survival rates of 4T1 tumor-bearing nude mice within 60 days feeding duration, and the digital images of tumors of each group after receiving varied treatments, including control group, Cu 2-x S-PEG NDs group, NIR-II laser group, and Cu 2-x S-PEG NDs + NIR-II laser group. Reproduced with permission. [61] Copyright 2019, Elsevier Ltd of Cu. For example, the preparation of AIBA@CuS-FA NPs was obtained by encapsulating hydrophilic azo initiator (AIBA) and CuS with amphiphilic liposomes [60]. In this nanosystem, CuS is a nanomaterial with photothermal conversion ability and triggers the thermal decomposition of AIBA into cytotoxic free alkyl groups under laser irradiation. Subsequently, free alkyl could promote the degradation of AIBA@CuS-FA NPs and produce Cu 2+ , which could catalytically decompose H 2 O 2 and produce ROS, as shown in Fig. 5a. These NPs could realize the accurate release of Cu and effectively reduce biological toxicity. Moreover, the photothermal conversion ability of CuS and the catalytic effect of Cu 2+ greatly improved the tumor inhibition ability of AIBA@ CuS-FA NPs, as depicted in Fig. 5b. Similarly, Cu 2-x S NPs (particle size less than 5 nm) also have photothermal conversion ability and the Fenton effect [61]. However, there are some big differences between Cu 2-x S and CuS. Cu 2-x S NPs have unpaired electrons, a large number of free carriers, and an excess of holes, which makes Cu 2-x S NPs have the potential to be a contrast agent and the ability to produce more ROS. Moreover, Cu 2-x S NPs have better photothermal conversion ability than CuS so that the Fenton-like reaction of Cu 2-x S NPs in solid tumors could be better enhanced with the increasing tumor temperature. The Fenton-like reaction of Cu 2-x S NPs in solid tumors is shown in Fig. 5c. Figure 5d indicated that the combined nano catalytic therapy (NCT)/ PTT could significantly inhibit tumor growth, and the tumor in mice was completely removed after 14 days Fig. 6 a Schematic diagram of ultrafine TiO 1+x NRs used as a novel sonosensitizer for SDT/CDT of cancer [72]. b CDT effects of four nanoparticles were detected by TMB and OPDA probes, respectively [72]. c The in-vivo fluorescence imaging and biodistribution of TiO 1+x NRs of 4T1 tumor-bearing mice after different treatment at various time points and the relative tumor volume of mice after different treatments. Reproduced with permission. [72] Copyright 2020, American Chemical Society of treatment. Therefore, the life span of mice could be highly extended. TiO 2 is an inorganic sonosensitizer with high chemical stability and low phototoxicity, which is widely used in SDT. However, when pure TiO 2 is used as a sonosensitizer, the rapid recombination of electrons and holes will reduce the quantum yield of ROS, so blocking the recombination of electrons and holes is an effective strategy to improve the production of ROS by TiO 2 nanomaterials [71]. As mentioned above, oxygen defects can hinder the recombination of electrons and holes, so constructing TiO 2 with oxygen defects is beneficial to improve the generation rate of ROS. More importantly, due to the existence of anoxic structures, titanium oxide compounds have a variety of valence states of titanium ions, and Ti 3+ ions make Ti-based nanomaterials have the ability to catalyze Fenton-like reactions. For instance, the TiO 1+ x nanorods prepared by a typical organic phase synthesis strategy showed a high generation rate of ROS and satisfactory catalytic capacity [72]. The low bandgap of TiO 1+x could enhance electron-hole separation efficiency, and then the ROS generation could be improved under the action of ultrasound. In addition, there were Ti 2+ , Ti 3+ , and a small amount of Ti 4+ in TiO 1+x nanorods. By comparing TiO 1+x nanorods with other Ti-based nanomaterials, TiO 1+x nanorods had the strongest catalytic performance, indicating that Ti 3+ has a Fenton-like effect, as depicted in Fig. 6b. Moreover, the in vivo fluorescence imaging and biodistribution of PEG-TiO 1+x NRs in mice proved that this nanorod had good permeability and retention effect (Fig. 6c), and the tumor growth curves of different groups of mice after various treatments indicated that the therapeutic effect of TiO 1+x NRs was much higher than TiO 2 NPs. Similarly, Liang et al. [23] prepared an octahedral MOF(Ti) with H 2 as the reducing agent, the MOF(Ti) also contains the anoxic structure of TiO x , and the ability of Ti 3+ to catalyze Fenton-like reaction is also verified.
In addition, accumulated evidence has indicated that Ag, Co 2+ , V 5+ , Ru 2+ , g-C 3 N 4 , and so on have the ability to catalyze the decomposition of H 2 O 2 . The specific mechanism of these nanoplatforms is summarized here, as shown in (Additional file 1: Table S3).
Effective strategies of enhancing the anticancer efficacy of F-NCs
According to the essence of Fenton or Fenton-like reactions, the influencing factors related to Fenton or Fenton-like reactions are mainly related to the reaction environment and the catalytic properties of nanomaterials. Regulating TME is an effective strategy to improve the efficiency of Fenton or Fenton-like reactions. The major factors that can influence TME include temperature, pH, the concentration of H 2 O 2 and GSH. More importantly, reducing F-NCs' dependence on acidic environment is another way to improve the therapeutic effect of cancer treatment.
Raising the temperature of solid tumors
Cancer cells can proliferate indefinitely without apoptosis under mild and appropriate conditions. They are easy to disperse and metastasize in the human body, so cancer cells have always been indestructible. However, cancer cells have a fatal weakness; that is, the heat resistance of cancer cells is poor. The temperature they can tolerate is not more than 42 °C, while normal human cells and tissues can withstand the high temperature of 46 °C [73]. Therefore, aiming at this weakness of cancer cells, it is an effective strategy to kill them by increasing the temperature of the tumor. In addition, the increasing temperature can enhance the catalytic activity of F-NCs, accelerate the decomposition rate of H 2 O 2 and realize the synergistic enhancement of CDT. Raising tumor temperature can be achieved with microwave thermal therapy, infrared thermal therapy, ultrasonic thermal therapy, and magnetic hyperthermia therapy.
Microwave thermal therapy
Microwave thermal therapy (MTT) is mainly achieved by thermal effect and biological effect. Due to the existence of magnetoresistance between polar molecules, the damping effect of the oscillations consumes microwave energy and generates heat [74]. Microwave has strong penetration ability and can be used to treat deep tumors. However, due to the limited area of tumor ablation, the recurrence rate of traditional MTT is very high. Therefore, the introduction of microwave sensitizers in MTT can effectively improve the diffusion and accumulation of heat in the tumor. Moreover, if the microwave sensitizers contain some ions with Fenton or Fenton-like effect, the therapeutic efficiency of microwave sensitizers will be highly improved. Based on this theory, a new-style flexible Mn-doped zirconium metal-organic framework nanocubes (Mn-ZrMOF NCs) synthesized by Fu's group were applied to MTT [75]. Mn-ZrMOF NCs have good microwave thermal conversion capability, and the thermal conversion efficiency is up to 28.7%. After 5 min of microwave irradiation, the temperature of tumor tissue could be raised to 62.3 °C. In addition, the catalytic efficiency of Mn 2+ can be rapidly improved due to high temperature, which can greatly improve the anticancer effect, as shown in Fig. 7a.
Photothermal therapy
Infrared thermal therapy, also known as photothermal therapy, is considered to be one of the most promising treatment methods due to its low invasive and high selectivity. PTT uses photothermal conversion materials to convert light into heat to raise the temperature of the focal area and kill cancer cells. PTT combined with CDT is an effective way to improve the killing efficiency of cancer cells. Wang and co-workers [76] demonstrated that mono-dispersed CoS 2 nanoclusters with photothermal conversion ability could significantly improve CDT. The photothermal conversion ability of CoS 2 significantly increased the internal temperature of the tumor and the Fenton-like catalytic reaction rate. Sun et al. [77] utilized the photothermal conversion capacity and catalytic effect of Cu 2-x Se and Au for effective antitumor therapy. The amorphous form of Cu 2-x Se and the catalysis of Au could promote the generation of •OH. In Cu 2-x Se-Au Janus nanoplatform, the plasmonic electrons of Au could intensify the conversion from Cu 2+ and Cu + . More importantly, both Cu 2-x Se and Au contributed to increasing the temperature (up to 67.1 °C, 30 μg/ml Cu ions) of TME under 808 nm laser, which highly improved the therapeutic effect, as depicted in Fig. 7b. In addition to Au and CoS 2 , CuS [78], Cu 9 S 5 [79], MoS 2 [80], and so on have also been proved to have photothermal conversion ability and can be used to increase the temperature inside the tumor and enhance the catalytic efficiency of Fenton reagent subsequently.
Ultrasonic thermal therapy
Ultrasound can be used for various biomedical applications; and the earliest medical application was the heating treatment of tissue. Ultrasound is divided into high-intensity focused ultrasound (HIFU) and low-intensity ultrasound. HIFU can significantly raise the temperature inside the tumor. At present, HIFU is an optional treatment method that focuses energy on deep tumor tissues in vivo but does not produce or only causes minor damage to normal tissues. Compared with PTT, HIFU can treat not only superficial tissues but also deep tissues in vivo [81], which can solve the disadvantage of insufficient light penetration in PTT. The main therapeutic mechanisms of HIFU are the thermal effect and cavitation effect [82]. The reason why HIFU has a thermal effect is that the energy of ultrasound in tissue propagation is absorbed by the tissue and converted into heat energy, which makes the tissue temperature rise. Low frequency and high energy focused ultrasound can make the temperature at the focal point rise abruptly, resulting in instantaneous high temperature (the temperature can rise 65-100 °C in 0.5-1.0 s), thus causing irreversible coagulation necrosis of the tissue [82]. Thermal ablation of tumors by HIFU has entered the clinical stage [83]. The enhancement of tumor temperature and Fenton reagent catalytic rate by combining HIFU and F-NCs should be a novel strategy [84]. In addition, high frequency and low energy focused ultrasound has also been proved to own a thermal effect and can be used to improve the catalytic efficiency of F-NCs. In recent work, the Fe(VI)@ HMON-PpIX-LA-PEG NCs (FHPLP NCs) can improve the temperature (up to 50 °C) of TME after 5 min ultrasonic irradiation (1.0 MHz, 1.4 W/cm 2 ) [85]. The ultrasonic thermal effect could accelerate the catalysis of Fe 2+ and enhance the antitumor ability of this nanoplatform (Fig. 7c).
Magnetic hyperthermia therapy
Magnetic hyperthermia therapy (MHT) has attracted more and more attention in recent years because of its non-invasive, less damage to normal tissue, low cost, and good tissue penetration. MHT is a technology that uses magnetic nanoparticles to produce a large amount of heat to ablate tumors under a strong alternating magnetic field (AMF). These magnetic nanoparticles that can be used in MHT always are F-NCs with magnetic response-ability, such as Fe 3 O 4 , γ-Fe 2 O 3 , and so on [86]. The high temperature produced by magnetic nanoparticles can improve their catalytic capacity, realize the combined treatment MHT/CDT. For example, Ir@MnFe 2 O 4 NPs with mitochondrial targeting properties have an obvious thermal effect under strong AMF [87]. Figure 7d indicates that the thermal effect can increase the conversion rate of Fe (III) to Fe (II) and H 2 O 2 to •OH, and as a consequence significantly enhance the therapeutic effect of CDT.
Briefly, these four methods can be used to increase the temperature of TME and synergistically enhance the anticancer effect of F-NCs. PTT and HIFU have the most obvious effect on the increase of TME temperature, while MT, low-energy ultrasound therapy, and MHT are relatively weak. However, due to the inherent defects of PTT (such as insufficient light penetration depth), the temperature of PTT for deep tumors will be seriously limited, and the instantaneous heating effect of HIFU will greatly improve its operation difficulty. Therefore, using low-energy ultrasound and AMF with high penetration depth to enhance the temperature of deep TME is a good choice. However, it is worth noting that in order to achieve the ideal treatment temperature, the concentration of materials used in MHT is generally higher than that of the other three therapies, which may increase the potential toxicity of this therapy. Therefore, materials with higher magnetocaloric conversion ability need to be developed urgently.
Reducing the pH of the TME and the acid dependence of F-NCs
The pH in TME is 6.5-7, while the optimal pH for the Fenton reaction is 2-4 [88]. Therefore, reducing the pH of TME is also an effective choice to improve the The mechanism of FcPWNPs mediated efficient CDT without acid dependence. Reproduced with permission. [94] Copyright Clearance Center, Inc. c Synthesis of aptamer prodrug conjugate ApDC nanoplatform and its mechanism in tumor. Reproduced with permission [95]. Copyright 2019, American Chemical Society efficiency of the Fenton reaction [89]. Generally, increasing the acidity of the TME can be achieved by introducing exogenous acids or other substances that can regulate the pH of the TME. As mentioned above, DCA is a strong organic acid with a pKa value of 1.35, which can regulate the pH of TME. It has been widely used in the clinical treatment of cancer [90][91][92]. The addition of DCA can not only reduce the pH of TME but also can reduce the mitochondrial membrane potential and greatly increase the reaction rate of the Fenton reaction. In addition to introducing DCA, introducing tamoxifen (TAM) has also been proved to be able to regulate the pH of the TME. However, different from DCA, TAM can indirectly regulate the pH of TME. For example, Shi et al. [93] synthesized a pH-responsive nanoplatform (FePt@FeO x @TAM-PEG). TAM is an anti-estrogen drug that can inhibit mitochondrial complex I, resulting in an increase in the ratio of adenosine monophosphate (AMP) to adenosine triphosphate (ATP), which can trigger the AMP-activated protein kinase (AMPK) signaling pathway. AMPK is a major factor that could regulate energy homeostasis in cells, which can promote glucose decomposition and lactic acid accumulation subsequently and increase the acidity in cancer cells finally, as shown in Fig. 8a. The increase of intracellular acidity can accelerate the release of FePt@FeO x NPs, thereby releasing Fe 2+ and Fe 3+ ions, accelerating the decomposition rate of H 2 O 2 , and enhancing the anti-tumor ability of the nanoplatforms.
Introducing exogenous acids or substances that can reduce the pH of tumors is a common and effective means to regulate the pH of TME. But it is a difficult issue to control the dosage of exogenous acid or other chemicals with pH-adjustable properties. Therefore, to solve this problem, the development of Fenton reagents without acid dependence is also an effective strategy to increase the Fenton reaction rate. The low efficiency of Fenton reaction-mediated CDT is due to the rapid precipitation of iron ions into inert Fe(OH) x in tumor tissues (pH 6.5-7) and the slow conversion rate between Fe 3+ and Fe 2+ . The reduced concentration of Fe 2+ seriously affects the reaction rate of the Fenton reaction. The excessive dependence of Fenton reagent on the acidic environment can be solved by blocking the transformation of iron ions to inert Fe(OH) x . For example, the cysteine-iron phosphotungstate chelate NPs (FcPWNPs) could avoid the transformation of iron ions to Fe(OH) x to break the limitation of pH [94]. The electron shuttle property of phosphotungstate can accelerate the transfer of Fe 3+ to Fe 2+ , and the chaining Fe 2+ will not transform into inert Fe(OH) x under neutral conditions, so that FcPWNPs can produce •OH on the neutral surface and in the acidic interior of the tumor (Fig. 8b). Moreover, because of the excess mitochondrial metabolism, the concentration of H 2 O 2 in tumor cells is several hundred mM, which is much higher than that in normal cells. Using prodrugs to reduce the acid dependence of Fenton reagents is also a way to increase the activity of Fenton reagents. For instance, a novel apder-prodrug conjugate (ApDC) could be used for non-H 2 O 2 and pH-dependent CDT [95]. ApDC micelle is mainly composed of three parts. The first one is the aptamer that identifies cancer cells; the second one is the prodrug base of the Fe 2+ activated tetraoxane (T); the third one is the heme that could respond to TME and provide Fe 2+ for in situ activations of T. Unlike conventional micelles, the prodrug in these micelles contains hydrophobic prodrug bases that not only promote aptamer assembly but form many free radicals through bioorthogonal reactions. More importantly, the strong hydrophobic prodrug bases could achieve the loading of heme in the ApDC micelles and improve the targeting ability of the aptamer-prodrug conjugate (ApPdC) micelle to the nucleus. As the number of "T" bases in a single ApPdc chain increased to three, the non-specific binding of ApPdC micelles to HepG2 cells became very apparent. In this nanoplatform, the free radical production process is independent of strong acidity or endogenous H 2 O 2 and simultaneously weakens the antioxidant capacity of cancer cells by consuming GSH. Although the cytotoxicity of this nanoplatform does not come from hydroxyl radicals. It depends on the C-centered toxic free radicals, and the production of the C-centered poisonous free radicals relies on the concentration of Fe 2+ ions, as shown in Fig. 8c. Therefore, designing the prodrug can fundamentally solve the issue of the conversion of Fe 2+ into Fe(OH) x in a neutral environment.
According to the above analyses, increasing the reactivity of Fenton reagents can start from reducing the pH of the TME by introducing exogenous acids or chemicals that can regulate the pH value of the TME. However, more importantly, the preparation of Fenton reagents that can be independent of the acidic environment has a wider application prospect and will be a new research trend of Fenton reagents in the future.
Increasing the concentration of H 2 O 2 in TME
H 2 O 2 is one of the reaction substrates of Fenton or Fenton-like reactions. The concentration of H 2 O 2 in the tumor is 100 μM, five times higher than normal cells [96]. However, this concentration still fails to achieve the ideal effect for cancer therapy. Therefore, increasing the concentration of H 2 O 2 can enhance the efficiency of the Fenton reaction and the anti-cancer therapeutic effect of Fenton reagents. Here, three methods to increase the concentration of H 2 O 2 in TME are summarized, including adding exogenous H 2 O 2 , some chemical agents Fig. 9 a The structure and action mechanism of H 2 O 2 /Fe 3 O 4 -PLGA NPs [88]. b Tumor growth curves with different treatments (n = 3) after intravenous injection (**p < 0.01). Reproduced with permission. [97] Copyright 2016, American Chemical Society. c Illustration of the synthesis and mechanism of Vk3@MOF-199 NPs [96]. d The tumor volume, tumor weight, tumor photos, and bodyweight of mice after different treatments. Reproduced with permission. [96] Copyright 2020, Elsevier Inc. e The synthetic procedure for GOD@CaCO 3 -Fe 3 O 4 particles and the degradation and action mechanism of Fe 3 O 4 @GOD@CaCO 3 NPs in the tumor [103]. f In vivo anticancer effect of GOD@CaCO 3 -Fe 3 [97]. In this system, liquid H 2 O 2 and disodium triphosphate were encapsulated in a hydrophilic core in the first emulsification, and Fe 3 O 4 NPs were embedded into a PLGA polymer hydrophobic shell in the second emulsification process. The loading amount of H 2 O 2 could be realized by adjusting the concentration of H 2 O 2 in the first emulsion polymerization and did not affect the morphology and size of NPs. Iron oxide mainly existed in the PLGA polymer shell. The encapsulation of H 2 O 2 played a key role in the treatment process. It could not only produce O 2 for echo reflection to achieve ultrasound imaging but also provide reaction substrate H 2 O 2 for the Fenton reaction (Fig. 9a). The interaction between H 2 O 2 and iron ions greatly increased the level of ROS in the TME, and the tumor in mice was significantly inhibited (Fig. 9b). Similarly, Song et al. [98] also solved the hypoxia in a tumor by introducing exogenous H 2 O 2 . They encapsulated catalase (CAT) and H 2 O 2 in liposomes to obtain CAT@Liposome and H 2 O 2 @Liposome NPs, respectively. They found that the combination of CAT@ Liposome and H 2 O 2 @Liposome could significantly improve the effect of cancer treatment. CAT can promote the decomposition of H 2 O 2 to produce ROS, which highly improves the concentration of ROS in cancer cells. Fig. 10 a Schematic diagram of the anticancer mechanism of DOX-CaO 2 -Fe/MS nanoplatform [110]. b Tumor photographs of mice treated by different groups. Reproduced with permission. [110] Copyright 2020, Acta Materialia Inc. c CP nanoparticles enhance the anticancer effect by increasing the level of H 2 O 2 in the tumor [111]. d Biodistribution of Cu in major organs and tumor of U87MG tumor-bearing mice at 24 h post i.v. injection with CPs [111]. e Relative tumor growth curves of U87MG tumor-bearing mice after treatment with saline (control group) or different doses of CPs [111]. f Time-dependent body-weight curves of mice in different groups. Reproduced with permission. [111] Copyright 2019, American Chemical Society
Introduction of chemical agents
Increasing the concentration of H 2 O 2 in TME by introducing exogenous chemical agents is the most widely used research method at present. GOD, doxorubicin (DOX), cinnamaldehyde (CA), vitamin k3(Vk3), β-lapachone (Lap), and some other exogenous chemicals have been found to increase the concentration of H 2 O 2 in tumors [99,100]. Tian and co-workers [96] designed a Cu-based MOF-199 nanoplatform integrated with Vk3. The nanoplatform could dissociate into MOF-199 fragments by reacting with GSH in the tumor and release Vk3 that could be catalyzed by NAD(P)H quinone oxidoreductase-1(NQO1) to produce enough H 2 O 2 to activate the Fenton-like reaction, as shown in Fig. 9c. The lightest and smallest tumors of the Vk3@MOF-199NPs group indicated that Vk3 could synergistically enhance CDT in vivo under the action of the NQO1 enzyme, as depicted in Fig. 9d. In addition, the use of GOD to increase the concentration of H 2 O 2 in TME is also an effective method [100][101][102][103]. GOD can oxidize glucose in tumor cells to H 2 O 2 , which can continuously provide an oxygen source for tumor treatment. Glucose in cells is oxidized and consumed, making cancer cells lack nutrients and starve, so this treatment process is also known Fig. 11 a Schematic illustrations of the construction and ferroptosis-inducing mechanism of FaPEG-MMSNs@DHA nano missiles [115]. b Intracellular biodegradation behavior of FaPEG-MMSNs@DHA [115]. c GPx4 activity of HepG2 cells after different treatments [115]. d The membrane morphological changes of HepG2 cells stained with DIO after co-incubation with different groups [115]. e PL-PUFA-OOH detection assay of HepG2 cells stained with C11-BODIPY 581/591 after co-incubation with different groups. Reproduced with permission [115] Copyright Clearance Center, Inc as "Starvation therapy" [104]. Chen et al. [103] synthesized Fe 3 O 4 @GOD@CaCO 3 NPs with the Fenton effect. Under the effect of the template of soluble starch, the nanocrystalline generated by the reaction of Ca 2+ and CO 3 2− ions immediately self-assembled into CaCO 3 nanocrystals. GOD was added before the completion of self-assembly to ensure the loading of GOD into the interior of CaCO 3 nanocrystals to obtain GOD@CaCO 3 NPs, and then the Fe 3 O 4 NPs prepared by the thermal solvent method were adsorbed on GOD@CaCO 3 NPs by physical adsorption. Finally, the Fe 3 O 4 @GOD@CaCO 3 NPs with the Fenton effect was obtained, as shown in Fig. 9e. The advantage of this nanoplatform is that CaCO 3 and Fe 3 O 4 can degrade in TME to produce Ca 2+ and Fe 2+ . They are essential trace elements in the body so that low dose Fe 3 O 4 @GOD@CaCO 3 NPs have low bio-toxic to mice. Due to the degradation of this nanoplatform, GOD could be successfully released into TME and oxidize glucose in the tumor to produce H 2 O 2 , resulting in a rich oxygen environment for tumor therapy. Under the effect of ultrasound, Fe 2+ could catalyze the decomposition of H 2 O 2 to produce ROS and couple with the overload of Ca 2+ , greatly increasing the apoptosis rate of cancer cells, as shown in Fig. 9f.
Introduction of metal peroxides
Metal peroxides can produce H 2 O 2 through a disproportionation reaction with water and can generate a strong oxidation effect through decomposition products (such as H 2 O 2 ) under acidic conditions [105,106]. Meanwhile, they can slowly release O 2 in water or under heating conditions. Therefore, using metal peroxides is also a new method to increase the concentration of H 2 O 2 in tumors [107].
At present, the metal peroxide mainly used in cancer treatment is CaO 2 . Moreover, ZnO 2 , MgO 2 , BaO 2 , CuO 2 , etc., have also been found to be able to increase the concentration of H 2 O 2 in tumors [107][108][109]. In order to achieve self-sufficiency of O 2 /H 2 O 2 in the tumor, He et al. [110] synthesized a DOX-CaO 2 -Fe nanoplatform containing chemotherapy drug DOX and biocompatible Fenton catalyst ferric oleate complex. Because of the easy decomposition of CaO 2 in water and acidic environment, solid lipid monostearate was used to coat CaO 2 to avoid the premature decomposition of CaO 2 . In the body, the overexpression of lipase can degrade the lipid layer of NPs. CaO 2 can be exposed to the acidic microenvironment of the tumor and react with the acidic water environment to produce H 2 O 2 . Finally, the chemotherapy drug DOX and ferric oleate will be released. Fe 3+ in ferric oleate could react with H 2 O 2 to produce O 2 and Fe 2+ , and Fe 2+ could catalyze H 2 O 2 to generate ROS. The anticancer mechanism of the DOX-CaO 2 -Fe/MS nanoplatform is shown in Fig. 10a. In vivo experiments showed that the addition of CaO 2 endowed the nano platform with the ability to solve the problem of hypoxia in TME. The synergistic effect between CaO 2 and Fe could obviously increase the tumor inhibitory effect of DOX-CaO 2 -Fe/ MS NPs (Fig. 10b). Different from CaO 2 , CuO 2 can not only enhance H 2 O 2 levels in tumors but also act as a Fenton catalyst for hydrogen peroxide decomposition, such as copper peroxide nano points (CP) [111]. The CP nanoplatform was synthesized by the coordination of H 2 O 2 and Cu 2+ with the help of hydroxide ions. After the CPs enter tumor cells, the acidic environment of lysosomes would accelerate the degradation of CPs and produce H 2 O 2 and Cu 2+ at the same time, and then Cu 2+ catalyzed the decomposition of H 2 O 2 , as shown in Fig. 10c. Due to the small hydrodynamic diameter (16.3 nm) of CPs, they could take advantage of the EPR effects to efficiently accumulate in tumors. By evaluating the biological distribution of CPs in U87MG tumorbearing mice, the uptake rate of CPs by tumor reached 5.96 ± 0.79%ID/g after 24 h of intravenous injection (Fig. 10d). The high accumulation of CPs in vivo made it suitable for in vivo CDT without obvious side effects. More importantly, the ability of CPs to generate H 2 O 2 in vivo could significantly improve the tumor inhibition effect of CDT, as depicted in Fig. 10e, f.
Reducing the level of GSH in tumor cells
GSH is a tripeptide composed of glutamate, cysteine, and glycine that can be found in almost every cell in the human body [112,113]. GSH has antioxidant properties and integrates detoxification to remove free radicals in the human body. GSH is easily oxidized by free radicals with oxidative properties in the body and the free radicals can be reduced to acidic substances, so as to accelerate the excretion of free radicals and reduce the toxic and side effects of free radicals on normal cells. In addition, the strong reducibility of GSH can protect the sulfhydryl groups in important enzyme proteins in normal cells from oxidation and inactivation, so as to ensure the metabolism of normal cells [114]. However, overexpressed-GSH in tumors will decrease the level of ROS in cancer cells. Therefore, the therapeutic effect can be improved by reducing the level of GSH for cancer cells.
Enhancing the anticancer effects of Fenton reagents by lowering the concentration of GSH has been proved to be a viable strategy. For example, a mesoporous silica nanosystem (FaPEG-MMSNs@DHA) constructed by Fei's group was used to deplete GSH and enhance ROS production, which was modified by folate-polyethylene glycol, loaded with dihydroartemisinin (DHA), and doped with Mn [115]. When the NPs were phagocytosed by tumor cells, the Mn-O bonds in the NPs would undergo a redox reaction with GSH, and DHA and Mn 2+ with Fenton catalytic effect could be released (Fig. 11a). On the one hand, the degradation of NPs resulted in the decrease of the level of GSH in TME, which inhibited the activity of GP X 4, so that the ability of ROS to oxidize PL-PUFA-OH will be enhanced, leading to the accumulation of lipid peroxides (PL-PUFA-OOH) in the tumor, as shown in Fig. 11b, c, and e. In addition, the released Mn 2+ will catalyze the reaction of peroxide bridge structure in DHA and produce •OH. The membrane morphological changes of HepG2 cells shown in Fig. 11d indicated that the cooperative effects could suppress tumor metastasis by destroying the structure of polyunsaturated fatty acids in the cell membranes and showed a potent antitumor effect. Similarly, some researchers [116][117][118] have synthesized organic-inorganic hybrid hollow mesoporous silica (HMONs) by the chemical homology method. HMONs have a unique nanostructure and composition. 4,4,13,13-tetraethoxy-3,14-dioxa-8,9-dichiath-4,13-disilahxadecane (BTDS), as a structural crosslinking agent, was covalently hybridized into the HMONs framework. The disulfide bond (S-S) enabled HMONs to consume reduced-GSH and be biodegradable. Therefore, HMONs have a broad application prospect in anticancer drug delivery.
Applications of F-NCs in anticancer therapy
CDT is a classical therapy mediated by Fenton or Fentonlike reactions, which is considered a green and efficient treatment method. However, the application of CDT has been severely hampered by the shortcomings of insufficient H 2 O 2 content in tumors to produce continuous ROS and the fact that TME is not the optimal reaction condition for F-NCs. Nowadays, most of the F-NCs are commonly combined with other treatment methods to overcome these shortcomings. More importantly, the combination of CDT with other treatments can Fig. 13 a Schematic diagram of the anticancer mechanism of multifunctional BP@Cu@PEG-RGD hybrid nanomaterials in vivo [133]. b Relative tumor volume after different treatments on day 14 [133]. c Inhibitory rates of B16F10 tumors at day 14 post-treatment [133]. d MIP PET images of B16F10 tumor-bearing mice after 2 weeks of treatment with saline or BP@Cu 0.4 @PEG-RGD, respectively. PET images were taken at 30 and 40 h after intravenous injection of saline or BP@ 64 Cu@PEG-RGD. The white circles denote the tumor sites. Reproduced with permission. [133] Copyright 2020, The Author(s) significantly improve the efficacy of anticancer therapy. At present, the treatment methods that can be combined with CDT mainly include PTT, PDT, SDT, ST, Gas therapy, and so on. As two common external excitation energies, light and ultrasound have the unique advantages of controllable wavelength and intensity and adjustable action area. In addition, the relatively low cost and noninvasive therapy make F-NCs widely used in light-excited or ultrasound-excited cancer treatment (such as PTT, PDT, and SDT), as shown in Fig. 12 [119][120][121]. The applications of F-NCs in PTT, PDT, and SDT will be introduced in detail in the following subsections.
Applications of F-NCs in PTT
As mentioned above, PTT has made huge progress in anticancer treatment due to its unique advantages. [122][123][124]. For example, Liu et al.have designed the NIR-light responsive and injectable DNA-mediated upconversion and gold NPs hybrid hydrogels (DNA-UCNP-Au) [125] for the treatment of the targeted treatment of malignant tumors. Xu et al.prepared the NIR-II photothermally activatable semiconducting polymeric nanoantagonist (ASPA) [126]. And Zhou et al. fabricated an activatable NIR-II plasmonic theranostics system based on silicaencapsulated self-assembled gold nano chains (AuNCs@ Fig. 14 a The synthesis of PEG/LDNPs@CMSNs nanoplatform and its action mechanism in vivo [135]. b The UC and DC mechanism of LDNPs [135]. c Corresponding CLSM images dyed with AM and PI of HeLa cells in four groups [135]. d Relative tumor volume in the control group and PEG/ LDNPs@CMSNs + NIR group. Reproduced with permission [135]. Copyright 2020, American Chemical Society SiO 2 ) [127] for efficient photoacoustic imaging and photothermal cancer therapy. Generally, the single-mode therapy of PTT is unable to eradicate tumor cells [128]. Interestingly, some studies have shown that PTAs with Fenton or Fenton-like effects can highly improve the anticancer therapeutic effect of them.
For example, two-dimensional (2D) nanosheets (FePS 3 NSs) with good biocompatibility and satisfactory Fenton effect could effectively eradicate tumors in mice [129]. The photothermal conversion efficiency of these NSs was 43.3%. Under the combined effect of PTT and CDT, the tumor inhibition rate was 95% after treatment with a drug concentration of 24 μg/ml. The tumor could be effectively eradicated after intravenous administration without any signs of recurrence. Similarly, another 2D nanomaterial (CuFe 2 S 3 ) also displayed a highly therapeutic effect due to its excellent photothermal conversion ability and catalytic capacity [130]. The near-infrared photothermal conversion efficiency of CuFe 2 S 3 -PEG was 55.86%, resulting in a great improvement of temperature in TME. It could accelerate the reaction rate of CuFe 2 S 3 -PEG and GSH Fig. 15 a The synthesis of (MSNs@CaO 2 -ICG)@LA and its action mechanism in cancer cells [136]. b Fluorescence images show ROS and hypoxia level in MCF-7 cells with different treatment under normoxia condition [136]. c Representative photos with different treatments of the mice and corresponding tumor tissues collected from different groups at 14 days. Reproduced with permission [136]. Copyright 2020, The Author(s) and further enhance the catalytic decomposition of H 2 O 2 by Fe 2+ and Cu + . PTT combined with CDT can eventually induce apoptosis of 87.97% hepatoma cells and complete tumor resection in vivo.
There is another advantage about PTAs with Fenton or Fenton-like effects. Sometimes, there will be a conflict between the high photothermal conversion efficiency and the degradability of photothermal agents (PTAs) [131]. PTAs with high photothermal conversion ability are difficult to degrade in vivo. This conflict will seriously limit the application of PTAs in cancer treatment. PTAs with Fenton or Fenton-like effects can solve the conflict between photothermal conversion efficiency and biodegradability. Because PTAs with catalytic ability generally can respond to the TME, which makes them own slow-degradability and little loss photothermal conversion capability. Based on this theory, Hu and co-workers [132] exploited the electrostatic attraction and coordination effect of twodimension(2D) material black phosphorus nanosheets (BPNS) to capture Cu 2+ and synthesized a photosensitizer (BP@Cu) with high photothermal conversion efficiency and Fenton effect that can be degradable in vivo (Fig. 13a). The coordination between Cu 2+ and BP could enhance the degradation of BP, the thickness of BPNS@Cu is significantly lower than that of pure BPNS. In addition, the best therapeutic effect of the BP@Cu 0.4 @PEG-RGD group, as shown in Fig. 13b-d, indicated that the photothermal effect of Cu 2+ and BPNS could synergistically enhance the CDT efficiency of Cu ions.
Applications of F-NCs in PDT
In addition to PTT, PDT is another light-mediated cancer treatment. PDT is a type of photoactivated chemotherapy. The photosensitizer absorbs the energy of photons to the excited state and generates some oxidation active molecules. After the photosensitizer (oxidation active molecules) is injected into the body for a period of time, it will specifically gather in the tumor site and combine with tumor cells, and then the photochemical reaction will be generated after the laser irradiation with a specific wavelength [133]. Compared with PTT, PDT has irreplaceable advantages. The local high fever of tumors caused by PTT may damage normal tissues. However, PDT can convert molecular oxygen into cytotoxic ROS, which causes irreversible damage to tumors. More importantly, PDT can accurately and mildly inhibit tumor growth for a long time [128]. But the single-mode of PDT is still cannot completely kill cancer cells, so it is necessary to develop multi-mode therapy. The combination of PDT and CDT can highly improve the efficiency of PDT.
High levels of GSH and low concentrations of H 2 O 2 in cancer cells are two major obstacles in PDT and CDT. In order to combine PDT and CDT with good therapeutic effects, there is an urgent need to develop Fenton effect photosensitizers that can reduce intracellular GSH levels or increase intracellular H 2 O 2 levels. Xu et al. [134] synthesized biodegradable lanthanide-doped NPs (LDNPs) encapsulated in copper/manganese silicate nanospheres (CMSN). The doping of Yb 3+ /Er 3+ /Tm 3+ in LDNPs endowed them the function of near-infrared laser upconversion (UC) and downconversion (DC), as shown in Fig. 14a, b. LDNPs with high atomic coefficients and unpaired electrons could be used in MRI and CT imaging. The CMSN shell could be excited by the emitted short-wavelength photons to realize PDT. It was also able to react with GSH in the tumor, resulting in the degradation of the CMSN shell and releasing Cu + and Mn 2+ Fenton-like ions, which could increase the level of •OH. There is another way to increase ROS levels in tumors about these NCs. When the up-conversion photon is activated by the NIR laser, O 2 could react with samples to produce 1 O 2 . Therefore, this nanoplatform solved the problems of low concentration of H 2 O 2 and high concentration of GSH in TME to improve PDT, as shown in Fig. 14a. Figure 14c, d showed that PEG/LDNPs@CMS-BNs + NIR group was more effective than other groups. The tumor was almost completely removed from the mice after the treatment of CDT/PDT, indicating Fenton NCs can dramatically enhance PDT.
Liu and co-workers [135] also constructed a nanoplatform((MSNs@CaO 2 -ICG) @LA) that could solve the poor therapeutic effect caused by high GSH content and low concentration of H 2 O 2 in the TME. As shown in Fig. 15a, (MSNs@CaO 2 -ICG) @LA was prepared by loading CaO 2 and indocyanine green (ICG) on manganese silicate (MSNs) and coating with the phase change material lauric acid (LA). This nanocatalyst can respond to the TME. MSNs was able to react with GSH and release Mn 2+ Fenton-like ions. CaO 2 was able to react with water under an acidic environment and generate much H 2 O 2 and O 2 . Finally, there would be a large amount of ROS in the TME under the effect of Mn 2+ . More interestingly, these results were achieved by the introduction of the phase change material LA which would crack under the irradiation of 808 nm laser. In addition, photosensitizer ICG could synergistically enhance the concentration of ROS in cancer cells. O 2 could react with it to produce 1 O 2 under laser irradiation. The in vivo and in vitro studies showed that (MSNs@CaO 2 -ICG)@LA could significantly improve the therapeutic effect, indicating that the combination of PDT and CDT has an excellent anticancer effect, as shown in Fig. 15b, c.
Applications of F-NCs in SDT
Light is the external energy of PTT and PDT, which can stimulate material to interact with TME to kill cancer cells. But light as external energy has a fatal disadvantage. The maximum penetration depth of light below the skin tissue is 10 mm, which seriously limits the clinical applications of PDT and PTT. However, the penetration depth of ultrasound below the skin tissue is 10 cm, which can solve the problem of tumor treatment deep in the body. Compared with PTT and PDT, the principle of SDT is more complex. At present, there are many studies on the mechanism of SDT, but there is still no definite conclusion. Most researchers support the synergy of multiple mechanisms leading to cell death. Among them, ultrasonic cavitation, ROS, and ultrasonic induced apoptosis are the recognized reasons for cell death caused by SDT [136].
Similar to PDT, SDT is also a relatively mild treatment for cancer. However, the large size, low sensitivity, and insufficient osmotic capacity of the sonosensitizer at present result in the inadequate short-term treatment effect of SDT [137,138]. In order to avoid the relatively long treatment cycle of SDT, it is necessary to improve the sonosensitizer. Some studies have proved that under the action of ultrasonic cavitation, the collapse of cavitation bubbles could cause the local liquid to occur violent turbulence, which could enhance the mass transfer rate of homogeneous or heterogeneous Fenton reagent system and consequently promote the therapeutic effect of CDT [139]. Therefore, the combination of CDT and SDT provides a new model to improve the effectiveness of cancer treatment.
Sonosensitizers are generally divided into organic and inorganic sonosensitizers. Organic sonosensitizers generally include porphyrin and its derivatives, DOX, curcumin, etc. [136]. Organic sonosensitizers generally come from photosensitizers, and organic sonosensitizers have a short cycle in the body and are specifically recognized and discharged out of the body by the immune system [140]. Therefore, organic sonosensitizers are generally loaded in carriers with good stability, so as to avoid premature exposure of organic sonosensitizers and to be transported to the tumor site with minimum loss. For example, Huang et al. [141] carried organic sonosensitizer protoporphyrin (PpIX) onto HMONs and constructed a sonosensitizer MnPpIX@HMONs with Fenton effect via the coordination between Mn 2+ and protoporphyrin. The therapeutic effect of MnPpIX@HMONs under the action of ultrasound was obviously better than that of single-use MnPpIX@HMONs, which demonstrates that the F-NCs can improve the effect of SDT. Fu et al. [85] also used HMONs to load protoporphyrin and at the same time adsorb FeO 4 2− in the mesopore of HMONs by electrostatic adsorption. They used the phase change material lauric acid to coat Fe(VI)@HMONs-PpIX. A slight thermal effect induced by ultrasound could trigger the phase change of lauric acid, resulting in the release of FeO 4 2− . Subsequently, a series of oxidation reactions occurred in TME. FeO 4 2− could reduce the concentration of GSH, and the Fenton reaction between Fe 2+ and H 2 O 2 could increase the ROS level in TME, as shown in Fig. 16a.
Inorganic sonosensitizers are more stable than organic sonosensitizers, and the most representative inorganic sonosensitizer is TiO 2 . In addition, inorganic sonosensitizers have less toxic and side effects on the human body, and it is easy to control the size and morphology of inorganic sonosensitizers so that inorganic sonosensitizers can accumulate in tumor cells better [142]. At present, the trend of designing inorganic sonosensitizers is to make inorganic sonosensitizers multifunctional, so as to realize multi-mode therapy. For example, sonosensitizer TiO 1+x and MnWO x [50,72] with anoxic structure could greatly improve the therapeutic effect of SDT since the Fenton-like Mn 2+ and Ti 3+ could catalyze the decomposition of H 2 O 2 . Moreover, the anoxic structure acts as a charge trap to limit the recombination of electron-hole pairs, thus improving the quantum yield of ROS. Recently, it has been demonstrated that ultrasmall nanoscale Au NPs can also be used as an effective sonosensitizer in SDT. Lin et al. [143] prepared Janus Au-MnO NPs (JNPs) with an asymmetric particle size of 10 nm by the heteroepitaxial growth of MnO on one side of Au NPs. Then the hydrophobic ROS sensitive polymer poly-(1,4-phenyleneacetone dimethylene thioketal) (PPADT-SH) and hydrophilic PEG-SH were grafted onto the surface of Au by covalent bond Au-S. Eventually, the amphiphilic JNP@PEG/PPADT vesicles (JNP Ve) were prepared by oil in water emulsification (Fig. 16b). In cancer cells, the ROS-sensitive polymer PPADT cleaves under the action of ultrasound. MnO is exposed to TME and reacts with GSH to produce Mn 2+ so that a large number of Au NPs exist alone in TME. The nano-size (5 nm) of Au NPs increases the possibility of ultrasonic cavitation to improve the level of ROS in TME and finally achieve the combined treatment of CDT and SDT, as shown in Fig. 16b. The in vivo experiments showed that the therapeutic effect of JNP Ve was greatly reduced without ultrasound (Fig. 16c), because PPADT could not be decomposed, resulting in a poor penetration ability of JNP Ve.
Conclusions and outlook
This review has summarized the development of F-NCs in recent years by introducing their preparation process, action mechanism, and applications in cancer treatment. With regards to the deficiency of F-NCs, some effective strategies to improve their therapeutic effect are proposed. In addition, the development prospect of F-NCs in this emerging field has prospected, as shown in Fig. 17. The F-NCs are usually responsive to the TME which can be regulated to enhance the lethality of the nanoplatforms to cancer cells, showing huge potentials for anticancer treatments and significantly accelerating the pace of clinical anticancer of nanomaterials. Although F-NCs have made important advances in cancer therapy, some crucial issues that can promote F-NCs to enter the clinic must be considered.
First, reducing the potential toxicity of F-NCs. Metalbased F-NCs may have systemic toxicity problems (such as nervous system abnormalities, loss of organ metabolic function, etc.). The low biocompatibility of metal-based F-NCs and the low uptake of F-NCs by cancer cells are the key reasons for their systemic toxicity. Generally, there are two ways to improve the biocompatibility of F-NCs. One is to select natural and non-toxic biomaterials with good water solubility in the synthesis process of F-NCs; the other one is to improve its biocompatibility through surface engineering. The surface engineering of Fenton nanocatalyst mainly includes: (a) introducing polymers (such as polyethylene and polyhydroxy ethyl methacrylate) on the material surface to prevent the adsorption of specific proteins; (b) introducing bioactive substances (such as specific growth factors) on the surface to biomimetic the cell membrane to achieve the purpose of biocompatibility so as to realize the "invisibility" of F-NCs to normal cells and proteins. At present, the accumulation of F-NCs in tumors is mainly achieved by the EPR effect. However, the uptake rate of F-NCs by tumor cells is less than 10% (intravenous injection), which will increase the possibility of F-NCs entering human functional organs through blood circulation. Strengthening the uptake of tumor cells can be achieved by adjusting the size and shape of nanoparticles. Another effective method is to utilize tumor-targeting technology to improve the uptake of F-NCs and reduce the distribution of F-NCs in the body.
Second, realizing controllable, repeatable, and largescale preparation of F-NCs. Due to the complex preparation process of F-NCs, it is difficult to synthesize the same nanomaterials quickly, accurately, and repeatedly. Therefore, some novel and simple preparation technics should be developed in future research, such as the microfluidic method, which can synthesize nanoparticles with uniform size, adjustable physical and chemical properties, and good repeatability through high-speed selfassembly. In addition, the synthesis cost of most current F-NCs is too high for large-scale production, so future research should focus on developing low-cost F-NCs.
Third, exploring the in-depth mechanism of F-NCs inducing cancer cell apoptosis in vivo. Most researchers believe that the apoptosis of cancer cells is caused by the oxidation of ROS, and this theory has been confirmed by in vitro experiments [144]. However, the TME is complex; this theory may not be suitable for the study of the interaction between F-NCs and cancer cells (inducing apoptosis) in vivo, which should be got more attention in future research. Exploring the specific mechanism of F-NCs in vivo is conducive to the design and development of multifunctional F-NCs.
Fourth, developing new Fenton reagents for multimodal treatment with diagnostic ability. Although many strategies have been proposed to improve CDT performance while the therapeutic effect is not very satisfactory. To completely eliminate malignancies, designing multifunctional F-NCs that can be used in other therapies is necessary. A large number of studies have proved that CDT combined with other treatments (such as PTT, PDT, SDT, immunotherapy, GT, etc.) can achieve the effect of "1 + 1 > 2" [145]. Particularly, F-NCs with the ability of diagnosis and multimodal therapy are more promising to enter the clinical stage. Because these nanomedicines can accurately diagnose the disease in real-time and treat it simultaneously. More importantly, we can monitor the curative effect and adjust the administration plan at any time in the whole treatment process, which is conducive to achieving the best treatment effect. Fortunately, some multifunctional F-NCs with imaging modes (such as magnetic resonance [146], ultrasonic imaging [147], photothermal imaging [148], and surfaceenhanced Raman [149]) have been developed, which lays a solid foundation to realize the precise theranostics of cancer.
Fifth, a complete and systematic material library and a standard evaluation system should be established. The way of preparation, collection, storage, and the structure and morphology of the samples have a direct impact on the catalytic and therapeutic effect of the F-NCs, and there is no unified standard to evaluate the catalytic capacity and therapeutic efficacy of different F-NCs. The establishment of material library and evaluation system can direct the design of F-NCs with desirable properties.
In summary, F-NCs have broad application prospects in the field of anticancer therapy. We hope that through our continuous efforts, we can design NCs with high catalytic efficiency, excellent safety, and perfect performance to realize their clinical applications as soon as possible and bring the gospel to cancer patients in the near future. | 17,117.8 | 2022-02-05T00:00:00.000 | [
"Chemistry"
] |
Analysis of the Relationship between Road Accidents and Psychophysical State of Drivers through Wearable Devices
A driver’s behavior and their psychophysical state are the most common causes of road accidents. The research presented in the paper proposes a method that allows the identification of highly dangerous road stretches/intersections in advance, based on the localization of stressful/relaxing situations measured on drivers. These were measured through the collection of physiological parameters using wearable devices. A correlation between stressful/relaxing situations and locations with high accident rates, based on a historical statistical database (black spots), was investigated. A series of driving tests was conducted in the city of Milan. The first set was mostly oriented to the research and validation of the parameters related to the driver’s psychophysical state. Subsequent tests allowed the definition of a correlation between black spots and relaxing/stressful areas. The results showed that the most stressful areas for drivers fell mainly within those with high accident rates. Furthermore, 80% of the most dangerous zones of the route were identified using this method, thus confirming the validity of the approach as a support tool for a priori preventive analysis for road safety. The wearable devices allowed the study and the integration of specific elements relating to human behavior in the field of road safety, which typically involves a technical-engineering approach.
Additionally, they are the main cause of death for young people aged between 15 and 29.The United Nations (UN) General Assembly, in 2010, established the Decade of Action for Road Safety (2011-2020), with the goal of halving the number of deaths on roads by 2020, compared to the 2011 records.From the data analysis on accidents, it is possible to appreciate how, currently, the trend of reduction in the number of victims of accidents, even if relevant, is not sufficient to achieve the mentioned goal [1][2][3].
From the engineering perspective, two kinds of analysis are usually performed to understand, and therefore, limit the phenomenon of accidents: preventive analysis according to road safety review (RSR) techniques, i.e., the identification of problems concerning the safety of a road infrastructure before the occurrence of an accidental event, and the analysis of historical data on accidents, based on the collection and subsequent processing of accident-related data detected by the different collectors [3].The two kinds of analysis mentioned, and particularly the analysis of historical data on accidents, are often affected by the following limitations:
•
Unavailability or lack of accuracy of information about the location of accidents.Both the localization and the repetitiveness of accidents in a site are essential elements for the execution of accurate safety analysis; • Unavailability of data related to car accidents that did not require the intervention of law enforcement agencies or collectors; • Limited consideration of the human factor in the analyses.
This last element is particularly significant, since, although the dynamics of road accidents are the result of a complex interaction between the vehicle, the driver, and the external environment, the responsibility for the accident is, in most cases, attributable to the driver's behavior.Considering the Italian national context, the data collected by the Italian National Institute for Statistics (ISTAT), updated in 2016, show that the circumstances underlying road accidents with injuries to people are mainly due to distracted driving (19.6% of total accidents on extra-urban roads), followed by failure to comply with safety rules (17.4% of the total considering only urban roads), and by right of way and high speed (15.3% of accidents on extra-urban roads) [2].Thus, the recorded increase in the safety of vehicles and infrastructures must necessarily be associated with interventions and measures able to determine positive impacts on the driver's behavior.
To effectively direct the interventions in this context, it is useful to increase the knowledge and understanding of the driver during the driving activity, investigating also their emotional states.Studies and researches about this subject were conducted in various fields and disciplines.The complexity related to these studies lies in the component of subjectivity associated with emotional states.For example, considering stress, it can be observed that, typically, the reaction of the human body to a stressful situation can be identified with an increase in heartbeat, muscle tension, blood pressure, and sweating [4][5][6].However, the factors and elements that can determine the onset of a state of stress, and its related "degree" of stress, can vary widely depending on each individual subject and, for the same subject, depending on many internal variables (such as stress collected during the day, emotional factors, or moods).
Trying to assess the psychophysical state of a person as objectively as possible, methods evolved from simple questionnaires to a direct evaluation of parameters, allowed by new and smarter technological possibilities.In the analyses performed within this study, the physiological signals taken into consideration, according to the literature review, were heartbeat (in particular, heart rate variability (HRV) and some of its components), skin conductivity (galvanic skin response (GSR)), and respiratory rate (RR) [7][8][9][10][11][12][13][14][15][16][17][18][19][20][21].These parameters and their functionality are described together with the method.
The research described in this paper is oriented to the study of the psychophysical state of the user driving a car, investigating conditions of particular stress, and contrarily, of considerable relaxation as possible causes of distraction, to increase the knowledge of these conditions during driving activities, and to provide elements of possible support for preventive accidental analysis.
The main objectives can be summarized with the following three points:
•
Definition of a method for the identification of stressful/relaxing points for the driver; • Validation of the method through the development and testing of an experimental protocol; • Identification of possible correlations between stressful/relaxing points and black spots, identified through accidental analysis.
It should be underlined that investigation of the driver's psychophysical state was performed in several previous studies [22][23][24][25][26][27][28][29][30][31].The added value of this paper is an investigation into how this aspect influences driving activity, in particular, the probability that high levels of stress or relaxation could impact on-road safety issues, supporting a preventive approach for road safety analysis.Among all the remarkable elements, it must be taken into account that dynamic tests with wearable and comfortable tools were carried out in the real world, while, in other methodologies, the tests were mainly performed in protected environments or with driving simulators.
Materials and Methods
From the methodological point of view, the approach adopted in this study can be summarized by the diagram reported in Figure 1.It should be underlined that investigation of the driver's psychophysical state was performed in several previous studies [22][23][24][25][26][27][28][29][30][31].The added value of this paper is an investigation into how this aspect influences driving activity, in particular, the probability that high levels of stress or relaxation could impact on-road safety issues, supporting a preventive approach for road safety analysis.Among all the remarkable elements, it must be taken into account that dynamic tests with wearable and comfortable tools were carried out in the real world, while, in other methodologies, the tests were mainly performed in protected environments or with driving simulators.
Materials and Methods
From the methodological point of view, the approach adopted in this study can be summarized by the diagram reported in Figure 1.As reported, three main inputs were required, and they are presented and described in the upcoming sections.These inputs are as follows:
•
Parameters related to the psychophysical state of the driver; • Location and scenario information; • Road safety analysis.
Parameters Related to the Psychophysical State of the Driver
Within the first set of experiments, to gather information about the psychophysical state, and particularly, to investigate the stressful situations of a user driving their vehicle, the physiological parameters of heart rate variability (HRV), respiratory rate (RR), and galvanic skin response (GSR) were selected.
Heart rate variability (HRV) is the natural variability of the heartbeat, thus representing the change in heart rate as a consequence of emotional factors, including stress.It can be divided into three frequency bands: very low frequency (VLF; between 0.01 and 0.04 Hz), low frequency (LF; between 0.04 and 0.15 Hz), and high frequency (HF; between 0.15 and 0.4 Hz).For the purposes of the first test phase, the component considered as most significant was LF, since several studies indicated it as a parameter closely related to the stress state of a person [12,13].As reported, three main inputs were required, and they are presented and described in the upcoming sections.These inputs are as follows:
•
Parameters related to the psychophysical state of the driver; • Location and scenario information; • Road safety analysis.
Parameters Related to the Psychophysical State of the Driver
Within the first set of experiments, to gather information about the psychophysical state, and particularly, to investigate the stressful situations of a user driving their vehicle, the physiological parameters of heart rate variability (HRV), respiratory rate (RR), and galvanic skin response (GSR) were selected.
Heart rate variability (HRV) is the natural variability of the heartbeat, thus representing the change in heart rate as a consequence of emotional factors, including stress.It can be divided into three frequency bands: very low frequency (VLF; between 0.01 and 0.04 Hz), low frequency (LF; between 0.04 and 0.15 Hz), and high frequency (HF; between 0.15 and 0.4 Hz).For the purposes of the first test phase, the component considered as most significant was LF, since several studies indicated it as a parameter closely related to the stress state of a person [12,13].
Respiratory rate (RR) represents the number of breaths performed by a subject in one minute.In the case of abnormal conditions, particular moods, or physical states, an increase in respiratory rate may be recorded [20].Typically, while a subject is in rest condition, the value of this parameter is around 12-20 breaths per minute [21].
The data collection and the analysis of HRV and RR were developed through the use of a wearable instrument consisting of a T-shirt (or a top for the female version) equipped with two sensors placed at the lower limit of the chest, where the tool equipped with a battery was fixed.This device allowed the measurement of an electrocardiogram (ECG) and the transmission of data collected via Bluetooth to a smartphone application, or their collection in a dedicated internal storage.
The devices, shown in Figure 2, were developed by a working group coordinated by the Sensibilab Laboratory of the Design Department-Politecnico di Milano.These tools were created for research purposes, and therefore, they are not directly comparable with commercial devices, as the precision and reliability of the outputs allow overcoming some limits of commercial tools, well described in the literature [32].Respiratory rate (RR) represents the number of breaths performed by a subject in one minute.In the case of abnormal conditions, particular moods, or physical states, an increase in respiratory rate may be recorded [20].Typically, while a subject is in rest condition, the value of this parameter is around 12-20 breaths per minute [21].
The data collection and the analysis of HRV and RR were developed through the use of a wearable instrument consisting of a T-shirt (or a top for the female version) equipped with two sensors placed at the lower limit of the chest, where the tool equipped with a battery was fixed.This device allowed the measurement of an electrocardiogram (ECG) and the transmission of data collected via Bluetooth to a smartphone application, or their collection in a dedicated internal storage.
The devices, shown in Figure 2, were developed by a working group coordinated by the Sensibilab Laboratory of the Design Department-Politecnico di Milano.These tools were created for research purposes, and therefore, they are not directly comparable with commercial devices, as the precision and reliability of the outputs allow overcoming some limits of commercial tools, well described in the literature [32].Another parameter considered significant is the galvanic skin response (GSR), which represents the conduction ability of the skin; in the case of emotional agitation or stress, the electrical resistance of the skin decreases progressively, while, on the contrary, the conductance increases [33,34].This parameter, together with HRV low frequency and the LF/HF ratio, appears to be one of the most valid indicators for the acquisition of information regarding the autonomic nervous system and stress levels [24].The measures of GSR are usually performed with sensors placed on the fingers of the hand and/or on the feet; however, to avoid interference with driving maneuvers, a bracelet with electrodes for the measurement of skin conductance was adopted (Figure 3) [33].The values recorded by the instrument during the test can be displayed on a smartphone application called MAXREFDES#73, developed by Maxim Integrated (San Jose, CA, USA), and they were collected in a text file.
For the second set of experiments, the HRV parameter was confirmed as a fundamental parameter for the assessment of the psychophysical state of the driver.In particular, in this second stage, the LF/HF ratio was considered, being able to provide information on the balance between the sympathetic and parasympathetic activity of the autonomic nervous system.High values of this ratio are linked to stressful situations involving greater activity of the sympathetic system, while low values are related to relaxed conditions, with a predominance of parasympathetic activity [15,[17][18][19].The threshold values for this parameter were 0.5 and 2; thus, if the LF/HF ratio was included within this interval, the system was balanced and the subject was in a "normal" condition [35].The tool for recording data used in this case was very similar to the one described above.It is called Another parameter considered significant is the galvanic skin response (GSR), which represents the conduction ability of the skin; in the case of emotional agitation or stress, the electrical resistance of the skin decreases progressively, while, on the contrary, the conductance increases [33,34].This parameter, together with HRV low frequency and the LF/HF ratio, appears to be one of the most valid indicators for the acquisition of information regarding the autonomic nervous system and stress levels [24].The measures of GSR are usually performed with sensors placed on the fingers of the hand and/or on the feet; however, to avoid interference with driving maneuvers, a bracelet with electrodes for the measurement of skin conductance was adopted (Figure 3) [33].The values recorded by the instrument during the test can be displayed on a smartphone application called MAXREFDES#73, developed by Maxim Integrated (San Jose, CA, USA), and they were collected in a text file.
For the second set of experiments, the HRV parameter was confirmed as a fundamental parameter for the assessment of the psychophysical state of the driver.In particular, in this second stage, the LF/HF ratio was considered, being able to provide information on the balance between the sympathetic and parasympathetic activity of the autonomic nervous system.High values of this ratio are linked to stressful situations involving greater activity of the sympathetic system, while low values are related to relaxed conditions, with a predominance of parasympathetic activity [15,[17][18][19].The threshold values for this parameter were 0.5 and 2; thus, if the LF/HF ratio was included within this interval, the system was balanced and the subject was in a "normal" condition [35].The tool for recording data used in this case was very similar to the one described above.It is called PegasoWes437, and it was also developed by the Sensibilab Laboratory (Lecco, LC, Italy).
Location and Scenario Information
To support the evaluation of the physiological indicators listed, the proposed method also considered the collection of further information.In particular, it was necessary to record the position, as well as a range of contextual information useful for the characterization of the road environment, and of the situations and scenarios that may occur within it.This information was collected using a Global Positioning System (GPS) device and a video camera.
The GPS was fundamental for the continuous spatial location of the data collected, and for the correlation between these and the black spots identified through the analysis of accidents.Several smartphone apps can fulfill this requirement and ensure instant car location data, including MotionXGPS (developed by Fullpower Technologies, Inc., Santa Cruz, CA, USA) and GeoTracker-GPS tracker (developed by Ilya Bogdanovich, Moscow, Russia).These applications allow saving files in .gpxformat, manageable with Google Earth.For each point, longitude, latitude, altitude, speed, and time can be displayed.
The use of a video camera was needed to effectively record the contextual features of the environment during the experimental driving tests, to identify events and situations that may indicate the potential causes of stress for the driver.During the field tests, different tools were used.In the first phase, a GoPro camera was used, positioned on the head of the driver (to record what he was actually seeing) or on the dashboard of the car.In the second phase, Camera Sunglasses (produced by Risest Technology Co., Futian District, Shenzhen, China) were used.
Further information could be collected through a recall test, carried out by the testers in both phases of the test (at the end of each driving test).The purpose of the questionnaire was to evaluate how stress was perceived by the user during the path, based on the perceptions declared by the testers.The recall test also allowed the collection of general information concerning the driving experience in the analyzed context.
Similar to the approach adopted in the study by Healey J.A. and Picard R.W. [24], two types of evaluation were requested in the recall test, shown below.
1.The individual user was asked to remember the events considered most stressful during the test and was asked to give each one a score from 1 (no stress) to 5 (very high stress).2. Participants were asked to list the causes of perceived stress from most stressful to least stressful.
The results of the questionnaires were then compared with the data collected during the different tests.
Location and Scenario Information
To support the evaluation of the physiological indicators listed, the proposed method also considered the collection of further information.In particular, it was necessary to record the position, as well as a range of contextual information useful for the characterization of the road environment, and of the situations and scenarios that may occur within it.This information was collected using a Global Positioning System (GPS) device and a video camera.
The GPS was fundamental for the continuous spatial location of the data collected, and for the correlation between these and the black spots identified through the analysis of accidents.Several smartphone apps can fulfill this requirement and ensure instant car location data, including MotionXGPS (developed by Fullpower Technologies, Inc., Santa Cruz, CA, USA) and GeoTracker-GPS tracker (developed by Ilya Bogdanovich, Moscow, Russia).These applications allow saving files in .gpxformat, manageable with Google Earth.For each point, longitude, latitude, altitude, speed, and time can be displayed.
The use of a video camera was needed to effectively record the contextual features of the environment during the experimental driving tests, to identify events and situations that may indicate the potential causes of stress for the driver.During the field tests, different tools were used.In the first phase, a GoPro camera was used, positioned on the head of the driver (to record what he was actually seeing) or on the dashboard of the car.In the second phase, Camera Sunglasses (produced by Risest Technology Co., Futian District, Shenzhen, China) were used.
Further information could be collected through a recall test, carried out by the testers in both phases of the test (at the end of each driving test).The purpose of the questionnaire was to evaluate how stress was perceived by the user during the path, based on the perceptions declared by the testers.The recall test also allowed the collection of general information concerning the driving experience in the analyzed context.
Similar to the approach adopted in the study by Healey J.A. and Picard R.W. [24], two types of evaluation were requested in the recall test, shown below.
1.
The individual user was asked to remember the events considered most stressful during the test and was asked to give each one a score from 1 (no stress) to 5 (very high stress).2.
Participants were asked to list the causes of perceived stress from most stressful to least stressful.
The results of the questionnaires were then compared with the data collected during the different tests.
Road Safety Analysis
To evaluate the possible correlations between the elements emerging from the study of the described parameters and the accidental events, it was necessary to develop a road safety analysis.
Currently, the analysis of accidents on a road network involves a first phase of historical data collection, over an extended time horizon (three or five years).These data are typically managed by institutes and bodies that deal with statistics at the national level.Considering the Italian context, accidental data are collected, processed, and published by ISTAT in collaboration with Automobile Club d'Italia (ACI).It must be highlighted that these data concern only serious accidents (i.e., the ones that require the intervention of the police authority), and that they do not always provide all the necessary information.Despite some limits, such as the ones mentioned, the statistical analysis of accidents allows a first understanding of these phenomena and supports the identification of the most critical areas (the black spots) located on a network.
The traditional approach is based on an initial aggregated analysis, with the aim of assessing the extent of the phenomenon, the types of events, the factors of accidents, and the location of critical points.A more in-depth investigation involves subsequent disaggregated analysis.It analyzes, for a particular location, the factors that caused accidents, so as to identify the possible countermeasures necessary to face critical issues.Figure 4 shows an example of a result of an accident analysis.
Road Safety Analysis
To evaluate the possible correlations between the elements emerging from the study of the described parameters and the accidental events, it was necessary to develop a road safety analysis.
Currently, the analysis of accidents on a road network involves a first phase of historical data collection, over an extended time horizon (three or five years).These data are typically managed by institutes and bodies that deal with statistics at the national level.Considering the Italian context, accidental data are collected, processed, and published by ISTAT in collaboration with Automobile Club d'Italia (ACI).It must be highlighted that these data concern only serious accidents (i.e., the ones that require the intervention of the police authority), and that they do not always provide all the necessary information.Despite some limits, such as the ones mentioned, the statistical analysis of accidents allows a first understanding of these phenomena and supports the identification of the most critical areas (the black spots) located on a network.
The traditional approach is based on an initial aggregated analysis, with the aim of assessing the extent of the phenomenon, the types of events, the factors of accidents, and the location of critical points.A more in-depth investigation involves subsequent disaggregated analysis.It analyzes, for a particular location, the factors that caused accidents, so as to identify the possible countermeasures necessary to face critical issues.Figure 4 shows an example of a result of an accident analysis.
Tests
The methodological approach described was applied to a series of experimental driving tests, so as to evaluate its applicability to a real case, and to develop an initial calibration.
The driving tests were carried out on the road network in the city of Milan.All participants were properly informed, and they signed a declaration of informed consent to take part in the study.
In the first set of experiments, two tests were carried out, both with drivers between the ages of 25 and 35, who were used to driving in large urban centers and using their own vehicles, so as to avoid the arising of further stress during the test.The experiments were carried out on "standard" days, avoiding anomalous situations (holidays or strikes, and, as much as possible, rush hours).Data collection took place over a time interval of about 1 h and 40 min for each test, for about 26 km of overall travelled distance.The path is reported in Figure 5.
Tests
The methodological approach described was applied to a series of experimental driving tests, so as to evaluate its applicability to a real case, and to develop an initial calibration.
The driving tests were carried out on the road network in the city of Milan.All participants were properly informed, and they signed a declaration of informed consent to take part in the study.
In the first set of experiments, two tests were carried out, both with drivers between the ages of 25 and 35, who were used to driving in large urban centers and using their own vehicles, so as to avoid the arising of further stress during the test.The experiments were carried out on "standard" days, avoiding anomalous situations (holidays or strikes, and, as much as possible, rush hours).Data collection took place over a time interval of about 1 h and 40 min for each test, for about 26 km of overall travelled distance.The path is reported in Figure 5.Each driver was equipped and monitored by means of the previously presented wearable devices (T-shirt/top with electrodes, GSR bracelet, and video camera on the head or on the dashboard), and was instructed about the path to follow.The tests were carried out with other people on board to activate the instruments and to use the connected applications.
In the second set of experiments, seven participants aged between 20 and 30 were involved, carrying out nine tests.Each driver drove his own car; however, unlike the first experimental set, some testers were not used to driving within an urban environment.As described before, the testers were instructed on the path to follow, and were monitored with the same wearable devices used in the first test.To record the environmental conditions, glasses with an integrated video camera were used instead of the video camera mounted on the head/dashboard.Before the actual driving test, the drivers were subjected to a test in rest conditions, lasting about 5 min, for the calibration of LF/HF ratio ranges for each driver.This baseline was fundamental to remove, as much as possible, the subjective components of the each driver's stress.In fact, knowing the range of values for each tester at rest allows obtaining objective results regarding values that exceed those recorded in rest conditions.
The tests were carried out during the daytime hours, along an 11-km path, reported in Figure 6, for a duration of about 45 min.
Both phases of experimentation allowed the identification of solutions to the operational problems that emerged.In particular, it was necessary to define an appropriate protocol for the synchronization of the different tools, since some complications in their simultaneous start-up arose.
The developed test in rest conditions or the tests of the second experimental phase allowed, instead, referring all values recorded for the parameters to the specific feature of each driver.
It was not possible, at this first level of research, to carry out long-term experiments, both because of the temporary availability of the used devices, and the complications that arose during the tests.In fact, the simultaneous activation of wearable tools, the GPS, and the video camera, as well as the checking of data collection, required the presence of at least two operators in the vehicle, making the independent management of tools by the drivers themselves difficult on various days.Each driver was equipped and monitored by means of the previously presented wearable devices (T-shirt/top with electrodes, GSR bracelet, and video camera on the head or on the dashboard), and was instructed about the path to follow.The tests were carried out with other people on board to activate the instruments and to use the connected applications.
In the second set of experiments, seven participants aged between 20 and 30 were involved, carrying out nine tests.Each driver drove his own car; however, unlike the first experimental set, some testers were not used to driving within an urban environment.As described before, the testers were instructed on the path to follow, and were monitored with the same wearable devices used in the first test.To record the environmental conditions, glasses with an integrated video camera were used instead of the video camera mounted on the head/dashboard.Before the actual driving test, the drivers were subjected to a test in rest conditions, lasting about 5 min, for the calibration of LF/HF ratio ranges for each driver.This baseline was fundamental to remove, as much as possible, the subjective components of the each driver's stress.In fact, knowing the range of values for each tester at rest allows obtaining objective results regarding values that exceed those recorded in rest conditions.
The tests were carried out during the daytime hours, along an 11-km path, reported in Figure 6, for a duration of about 45 min.
Both phases of experimentation allowed the identification of solutions to the operational problems that emerged.In particular, it was necessary to define an appropriate protocol for the synchronization of the different tools, since some complications in their simultaneous start-up arose.
The developed test in rest conditions or the tests of the second experimental phase allowed, instead, referring all values recorded for the parameters to the specific feature of each driver.
It was not possible, at this first level of research, to carry out long-term experiments, both because of the temporary availability of the used devices, and the complications that arose during the tests.In fact, the simultaneous activation of wearable tools, the GPS, and the video camera, as well as the checking of data collection, required the presence of at least two operators in the vehicle, making the independent management of tools by the drivers themselves difficult on various days.
Elaboration of the Psychophysical Parameters
The data processing phase was developed with different approaches for the two test phases considered.In the first set of experiments, the data collected by the heart-rate measurement sensor were sent in real time to the smartphone application, also developed by the Sensibilab Laboratory.This app made it possible to obtain and manage information on HRV and RR.The data collected by the tool were then used as input to a specific software for the calculation and processing of the HRV parameter-Kubios-developed by the Biosignal Analysis and Medical Imaging Group of the University of Kuopio, Finland [36,37].This software allows the analysis of HRV and its components over discrete time intervals (with a minimum time interval of 30 s).Both the values of the different frequency components, i.e., VLF, LF, HF, and the LF/HF ratio, and the parameters in the time domain are provided.The latter values were not considered in the analysis as they are less related to stress conditions [16,17].An example of the information collected and processed is shown in Figure 7.
Elaboration of the Psychophysical Parameters
The data processing phase was developed with different approaches for the two test phases considered.In the first set of experiments, the data collected by the heart-rate measurement sensor were sent in real time to the smartphone application, also developed by the Sensibilab Laboratory.This app made it possible to obtain and manage information on HRV and RR.The data collected by the tool were then used as input to a specific software for the calculation and processing of the HRV parameter-Kubios-developed by the Biosignal Analysis and Medical Imaging Group of the University of Kuopio, Finland [36,37].This software allows the analysis of HRV and its components over discrete time intervals (with a minimum time interval of 30 s).Both the values of the different frequency components, i.e., VLF, LF, HF, and the LF/HF ratio, and the parameters in the time domain are provided.The latter values were not considered in the analysis as they are less related to stress conditions [16,17].An example of the information collected and processed is shown in Figure 7.
Elaboration of the Psychophysical Parameters
The data processing phase was developed with different approaches for the two test phases considered.In the first set of experiments, the data collected by the heart-rate measurement sensor were sent in real time to the smartphone application, also developed by the Sensibilab Laboratory.This app made it possible to obtain and manage information on HRV and RR.The data collected by the tool were then used as input to a specific software for the calculation and processing of the HRV parameter-Kubios-developed by the Biosignal Analysis and Medical Imaging Group of the University of Kuopio, Finland [36,37].This software allows the analysis of HRV and its components over discrete time intervals (with a minimum time interval of 30 s).Both the values of the different frequency components, i.e., VLF, LF, HF, and the LF/HF ratio, and the parameters in the time domain are provided.The latter values were not considered in the analysis as they are less related to stress conditions [16,17].An example of the information collected and processed is shown in Figure 7. Concerning the GSR parameter, the values recorded by the instrument during the test, after being collected and analyzed by the application MAXREFDES#73, were consulted and processed as text files.Concerning the GSR parameter, the values recorded by the instrument during the test, after being collected and analyzed by the application MAXREFDES#73, were consulted and processed as text files.
The values of the LF, RR, and GSR parameters were reported on three graphs that illustrate their trends over time.By overlapping these graphs, thanks to the output synchronization, it was possible to identify the instances, or more correctly, the time intervals, in which a coincidence of the LF and GSR peaks was recorded.The comparison between several indicators provides further confirmation and allows overcoming the potential errors of the single device.For this reason, the points that were considered as stressful were those in which both parameters presented peak values.This condition allowed the identification of a first set of points in which the values of altered psychophysical status were recorded.However, for the identification of the points chosen for the comparison with black spots, the RR parameter recorded at the identified locations was also considered (its value must be greater than 20 breaths/minute to be considered as anomalous [21]), and a video-recording check of what the driver was seeing and perceiving during the test drive was made.
In the second test phase, the data relating to the HRV parameter were collected and processed on the personal computer (PC) using the Mx Viewer software (developed by CSEM, Nazartel, Switzerland within the Pegaso project) [38], before being analyzed with the Kubios software, as in the first experimental phase.The HRV component considered for the analyses was the LF/HF ratio.Thresholds were defined, different for each driver, and four bands of stress/relaxation states were considered: stress, neutral-stress, neutral-relaxation, and relaxation.Each road section, defined in the road safety analysis phase, featured the following:
•
One of the four bands of accidents (high, medium-high, medium-low, low);
•
The number of times (N) in which the parameter, LF/HF, fell into one of the four bands of stress/relaxation (for each of the bands: stress, neutral-stress, neutral-relaxation, or relaxation) As an initial and quick analysis, a correlation matrix was developed to assess whether high stress levels corresponded to high accident rates and vice versa (Figure 8).
Each cell of the matrix contains the number of cases in which the level of stress reported in each row was recorded within a specific area characterized by a specific accidental level indicated in each column.For example, the a 11 coefficient represents the total number of times in which the high stress condition occurred within the areas featured by a high accident rate.
A scoring method was used, implying a score for each area equal to the sum of the individual scores related to the four levels of psychophysical state (i.e., 3 for stress, 1 for neutral-stress, and 0 for neutral-relaxation and relaxation).By setting a threshold for the score of the zones, the areas that exceeded this threshold could be considered as actually stressful and potentially risky zones.
Appl. Sci. 2018, 8, x FOR PEER REVIEW 9 of 17
The values of the LF, RR, and GSR parameters were reported on three graphs that illustrate their trends over time.By overlapping these graphs, thanks to the output synchronization, it was possible to identify the instances, or more correctly, the time intervals, in which a coincidence of the LF and GSR peaks was recorded.The comparison between several indicators provides further confirmation and allows overcoming the potential errors of the single device.For this reason, the points that were considered as stressful were those in which both parameters presented peak values.This condition allowed the identification of a first set of points in which the values of altered psychophysical status were recorded.However, for the identification of the points chosen for the comparison with black spots, the RR parameter recorded at the identified locations was also considered (its value must be greater than 20 breaths/minute to be considered as anomalous [21]), and a video-recording check of what the driver was seeing and perceiving during the test drive was made.
In the second test phase, the data relating to the HRV parameter were collected and processed on the personal computer (PC) using the Mx Viewer software (developed by CSEM, Nazartel, Switzerland within the Pegaso project) [38], before being analyzed with the Kubios software, as in the first experimental phase.The HRV component considered for the analyses was the LF/HF ratio.Thresholds were defined, different for each driver, and four bands of stress/relaxation states were considered: stress, neutral-stress, neutral-relaxation, and relaxation.Each road section, defined in the road safety analysis phase, featured the following:
•
One of the four bands of accidents (high, medium-high, medium-low, low);
•
The number of times (N) in which the parameter, LF/HF, fell into one of the four bands of stress/relaxation (for each of the bands: stress, neutral-stress, neutral-relaxation, or relaxation) As an initial and quick analysis, a correlation matrix was developed to assess whether high stress levels corresponded to high accident rates and vice versa (Figure 8).
Each cell of the matrix contains the number of cases in which the level of stress reported in each row was recorded within a specific area characterized by a specific accidental level indicated in each column.For example, the a11 coefficient represents the total number of times in which the high stress condition occurred within the areas featured by a high accident rate.
A scoring method was used, implying a score for each area equal to the sum of the individual scores related to the four levels of psychophysical state (i.e., 3 for stress, 1 for neutral-stress, and 0 for neutral-relaxation and relaxation).By setting a threshold for the score of the zones, the areas that exceeded this threshold could be considered as actually stressful and potentially risky zones.
Elaboration of Accidental Data
For both sets of experiments, the accidental data used for the elaboration were provided by the Agenzia Mobilità Ambiente e Territorio-Comune di Milano (AMAT) and concerned accidents with injuries to people occurring in the three-year period of 2011-2013 (experimental phase 1) and in the period of 2011-2017 (experimental phase 2, with partial data for the final year).
Elaboration of Accidental Data
For both sets of experiments, the accidental data used for the elaboration were provided by the Agenzia Mobilità Ambiente e Territorio-Comune di Milano (AMAT) and concerned accidents with injuries to people occurring in the three-year period of 2011-2013 (experimental phase 1) and in the period of 2011-2017 (experimental phase 2, with partial data for the final year).
In the first experimental phase, both aggregate and disaggregated analysis of all the available data were performed, while, in the second phase of the research, the data were previously filtered, based on the type of accident and vehicles involved.All accidents not involving cars were excluded from the elaboration, following the choice of performing tests with cars only.In addition, isolated accidents were excluded, i.e., those that did not show a feature of recursion.
In both cases, accidents were located, reporting their spatial coordinates on a map with the QGIS software (QGIS Development Team (2018).QGIS Geographic Information System.Open Source Geospatial Foundation Project.http://qgis.osgeo.org).
In the first experiment, the individual points of accident were not considered, but rather, an area of influence (buffer) of 60 m in diameter around them.This choice allowed partially overcoming the inaccuracies relating to the location of the data, and, at the same time, appropriately considering also the area surrounding the points in which the events were recorded.The possible causes of an accident could, in fact, also be researched in the neighborhood of the point where it happened.
In the second experimental phase, as a conclusion of the analysis of accidents, the route was divided into zones of about 100-400 m length, as reported in the example in Figure 9.The division was developed starting from the points that presented numerous incidents, and by setting around them an initial and a final section, so as to create a homogeneous subdivision of the route.A homogeneous zone can be defined as a spatial interval that presents a homogeneous infrastructural features (i.e., intersection area or road link in urban areas), in which it is assumed that behavior is similar for all drivers.
This approach allowed transforming the analysis from punctual to areal, partially overcoming possible localization errors.
Appl.Sci.2018, 8, x FOR PEER REVIEW 10 of 17 In the first experimental phase, both aggregate and disaggregated analysis of all the available data were performed, while, in the second phase of the research, the data were previously filtered, based on the type of accident and vehicles involved.All accidents not involving cars were excluded from the elaboration, following the choice of performing tests with cars only.In addition, isolated accidents were excluded, i.e., those that did not show a feature of recursion.
In both cases, accidents were located, reporting their spatial coordinates on a map with the QGIS software (QGIS Development Team (2018).QGIS Geographic Information System.Open Source Geospatial Foundation Project.http://qgis.osgeo.org).
In the first experiment, the individual points of accident were not considered, but rather, an area of influence (buffer) of 60 m in diameter around them.This choice allowed partially overcoming the inaccuracies relating to the location of the data, and, at the same time, appropriately considering also the area surrounding the points in which the events were recorded.The possible causes of an accident could, in fact, also be researched in the neighborhood of the point where it happened.
In the second experimental phase, as a conclusion of the analysis of accidents, the route was divided into zones of about 100-400 m length, as reported in the example in Figure 9.The division was developed starting from the points that presented numerous incidents, and by setting around them an initial and a final section, so as to create a homogeneous subdivision of the route.A homogeneous zone can be defined as a spatial interval that presents a homogeneous infrastructural features (i.e., intersection area or road link in urban areas), in which it is assumed that behavior is similar for all drivers.
This approach allowed transforming the analysis from punctual to areal, partially overcoming possible localization errors.
Results
Different results were obtained from the two experimental phases.
Results of the First Experimental Phase
At the end of the first set of tests, after the selection and location of the peak stress points, maps were provided for each driver involved in the test, as shown in Figure 10.
Results
Different results were obtained from the two experimental phases.
Results of the First Experimental Phase
At the end of the first set of tests, after the selection and location of the peak stress points, maps were provided for each driver involved in the test, as shown in Figure 10.Three main results were achieved, as follows: • Some of the points identified during the tests were stressful for both involved drivers.Even on the basis of two tests only, it was, therefore, possible to highlight road areas for which it would be advisable to investigate the causes of an increase in stress, so as to carry out possible interventions; • A correlation between stress points and accident points was found.By creating a buffer of 60 m in diameter around the points in which the accident occurred, 50% of the recorded stress points were located within this buffer.On the contrary, considering the same buffer around stress points, the 56% of the points in which the accident occurred were within the defined area.Even considering the limited number of tests, the recorded corresponding values appear as an initial interesting element for the validation of the method.Figures 11 and 12 show two examples of results, whereby incidental points are displayed in red and stress peaks in blue.The buffers highlighted in yellow show the areas in which there was a correspondence between stress condition and accidents, while the various dimensions of red and blue points are associated with the different number of accidents or with the different level of stress encountered (low, medium, or high); The data elaboration highlighted the relevant effect related to the presence of construction sites, road works, and detours along the path investigated.In fact, it emerged that many of the points defined as stressful were located in areas with unclear indications of deviations or with bottlenecks due to the presence of road works.Three main results were achieved, as follows: • Some of the points identified during the tests were stressful for both involved drivers.Even on the basis of two tests only, it was, therefore, possible to highlight road areas for which it would be advisable to investigate the causes of an increase in stress, so as to carry out possible interventions; • A correlation between stress points and accident points was found.By creating a buffer of 60 m in diameter around the points in which the accident occurred, 50% of the recorded stress points were located within this buffer.On the contrary, considering the same buffer around stress points, the 56% of the points in which the accident occurred were within the defined area.Even considering the limited number of tests, the recorded corresponding values appear as an initial interesting element for the validation of the method.Figures 11 and 12 show two examples of results, whereby incidental points are displayed in red and stress peaks in blue.The buffers highlighted in yellow show the areas in which there was a correspondence between stress condition and accidents, while the various dimensions of red and blue points are associated with the different number of accidents or with the different level of stress encountered (low, medium, or high);
•
The data elaboration highlighted the relevant effect related to the presence of construction sites, road works, and detours along the path investigated.In fact, it emerged that many of the points defined as stressful were located in areas with unclear indications of deviations or with bottlenecks due to the presence of road works.Three main results were achieved, as follows: • Some of the points identified during the tests were stressful for both involved drivers.Even on the basis of two tests only, it was, therefore, possible to highlight road areas for which it would be advisable to investigate the causes of an increase in stress, so as to carry out possible interventions; • A correlation between stress points and accident points was found.By creating a buffer of 60 m in diameter around the points in which the accident occurred, 50% of the recorded stress points were located within this buffer.On the contrary, considering the same buffer around stress points, the 56% of the points in which the accident occurred were within the defined area.Even considering the limited number of tests, the recorded corresponding values appear as an initial interesting element for the validation of the method.Figures 11 and 12 show two examples of results, whereby incidental points are displayed in red and stress peaks in blue.The buffers highlighted in yellow show the areas in which there was a correspondence between stress condition and accidents, while the various dimensions of red and blue points are associated with the different number of accidents or with the different level of stress encountered (low, medium, or high); The data elaboration highlighted the relevant effect related to the presence of construction sites, road works, and detours along the path investigated.In fact, it emerged that many of the points defined as stressful were located in areas with unclear indications of deviations or with bottlenecks due to the presence of road works.
Results of the Second Experimental Phase
In this phase, after the division of the path into homogeneous zones and the assignment of levels based on the accident rate and on the levels of stress, it was possible to fill the correlation matrix.This matrix, described in Section 2.5.1, takes into account all accidents selected.At this time, two important results become evident, as follows:
•
The first result concerned the testers, and it is the lack of significant differences between habitual users and users who followed the path for the first time;
•
The most meaningful result was that the greater number of accidents was positioned on the diagonal of the matrix (Figure 13).This condition defines, thus, a substantial correspondence of psychophysical state-incidental level; specifically, a stressful psychophysical state corresponds to a high accident rate, and, at the same time, a relaxed state corresponds to a limited accident rate.The outputs highlighted that this second experiment allowed the identification, in a more defined way, of a correlation between stress and accidents.The result obtained made it possible to define a scoring method useful to support the identification of the sections that may require interventions to reduce the risk of accidents.
Relying on the scoring method, it was possible to make the two following observations: • Considering the total number of stressful zones (28 zones were classified as stressful), representing 45% of the total zones of the path, it can be observed that, among these, 14 are
Results of the Second Experimental Phase
In this phase, after the division of the path into homogeneous zones and the assignment of levels based on the accident rate and on the levels of stress, it was possible to fill the correlation matrix.This matrix, described in Section 2.5.1, takes into account all accidents selected.At this time, two important results become evident, as follows:
•
The first result concerned the testers, and it is the lack of significant differences between habitual users and users who followed the path for the first time;
•
The most meaningful result was that the greater number of accidents was positioned on the diagonal of the matrix (Figure 13).This condition defines, thus, a substantial correspondence of psychophysical state-incidental level; specifically, a stressful psychophysical state corresponds to a high accident rate, and, at the same time, a relaxed state corresponds to a limited accident rate.
Results of the Second Experimental Phase
In this phase, after the division of the path into homogeneous zones and the assignment of levels based on the accident rate and on the levels of stress, it was possible to fill the correlation matrix.This matrix, described in Section 2.5.1, takes into account all accidents selected.At this time, two important results become evident, as follows:
•
The first result concerned the testers, and it is the lack of significant differences between habitual users and users who followed the path for the first time;
•
The most meaningful result was that the greater number of accidents was positioned on the diagonal of the matrix (Figure 13).This condition defines, thus, a substantial correspondence of psychophysical state-incidental level; specifically, a stressful psychophysical state corresponds to a high accident rate, and, at the same time, a relaxed state corresponds to a limited accident rate.The outputs highlighted that this second experiment allowed the identification, in a more defined way, of a correlation between stress and accidents.The result obtained made it possible to define a scoring method useful to support the identification of the sections that may require interventions to reduce the risk of accidents.
Relying on the scoring method, it was possible to make the two following observations: • Considering the total number of stressful zones (28 zones were classified as stressful), representing 45% of the total zones of the path, it can be observed that, among these, 14 are The outputs highlighted that this second experiment allowed the identification, in a more defined way, of a correlation between stress and accidents.The result obtained made it possible to define a scoring method useful to support the identification of the sections that may require interventions to reduce the risk of accidents.
Relying on the scoring method, it was possible to make the two following observations: • Considering the total number of stressful zones (28 zones were classified as stressful), representing 45% of the total zones of the path, it can be observed that, among these, 14 are located in areas with high accident rates.It follows that half of the zones characterized by stress have a direct correspondence with high-accident areas; • By sorting the 62 zones by their respective stress scores, and by selecting the 15 sections with a higher stress score (more stressful), 12 of these areas (80%) were represented by high-accident areas, as reported in Figure 14.
This represents an appreciable and promising result that shows how this method, referring to the test developed, is able to provide an effective tool to support preventive road safety analysis.
Appl.Sci.2018, 8, x FOR PEER REVIEW 13 of 17 located in areas with high accident rates.It follows that half of the zones characterized by stress have a direct correspondence with high-accident areas; • By sorting the 62 zones by their respective stress scores, and by selecting the 15 sections with a higher stress score (more stressful), 12 of these areas (80%) were represented by high-accident areas, as reported in Figure 14.
This represents an appreciable and promising result that shows how this method, referring to the test developed, is able to provide an effective tool to support preventive road safety analysis.
Figure 14.The 15 areas with the highest stress scores.The areas identified with high accident rates according to road safety analysis are reported in red.The colors yellow and green identify zones with medium-high and medium-low accident rate.
General Observations
Finally, a mention about the outcomes of the recall test, reported in Section 2.2, should be provided.By definition, this questionnaire was submitted to the driver at the end of the test, asking him to list and order the most stressful situations met while driving.
By locating the points in which the events declared by the participants occurred, and by consequently identifying the moment or time interval in which they actually happened, it was possible to compare them with the values of the physiological parameters.A good correspondence was recorded between the situations considered stressful by the user and high values of LF, GSR, or RR that defined the stress points selected in the elaboration.
Considering the high subjectivity intrinsic in the compilation of the questionnaire by the participants, the information that could be deduced was considered only as partial or supporting.These data are, thus, not strictly necessary and not sufficiently objective to be used as an effective reference for a study concerning accidents; however, they should be considered useful complementary materials.
Discussion
This study intended to define a method of collecting unbiased information on the psychophysical state of the driver, with the aim of investigating the possible correlations between road safety and their emotional state.In particular, this study focused on the possibility that either stressful or particularly relaxing conditions could be correlated with road accidents.
The first phase of the research was oriented to the identification of physiological parameters related to stress, thus defining the methods of collection and comparison, which were later useful to define stress peaks.Data collection showed that the most interesting indicators were the LF
General Observations
Finally, a mention about the outcomes of the recall test, reported in Section 2.2, should be provided.By definition, this questionnaire was submitted to the driver at the end of the test, asking him to list and order the most stressful situations met while driving.
By locating the points in which the events declared by the participants occurred, and by consequently identifying the moment or time interval in which they actually happened, it was possible to compare them with the values of the physiological parameters.A good correspondence was recorded between the situations considered stressful by the user and high values of LF, GSR, or RR that defined the stress points selected in the elaboration.
Considering the high subjectivity intrinsic in the compilation of the questionnaire by the participants, the information that could be deduced was considered only as partial or supporting.These data are, thus, not strictly necessary and not sufficiently objective to be used as an effective reference for a study concerning accidents; however, they should be considered useful complementary materials.
Discussion
This study intended to define a method of collecting unbiased information on the psychophysical state of the driver, with the aim of investigating the possible correlations between road safety and their emotional state.In particular, this study focused on the possibility that either stressful or particularly relaxing conditions could be correlated with road accidents.
The first phase of the research was oriented to the identification of physiological parameters related to stress, thus defining the methods of collection and comparison, which were later useful to define stress peaks.Data collection showed that the most interesting indicators were the LF component of heart rate variability, the LF/HF ratio (always linked to HRV), and the skin conductance (GSR).Following this introductory phase, two different experiments were carried out on the streets in the city of Milan.
The first experimental phase represented a useful warm-up and made it possible to evaluate and test the tools, as well as revealing how to operate and manage them during the driving phases.At the same time, the test allowed the identification of stress points along a path and a comparison across data collected for each driver.These points were then spatially correlated with the locations where road accidents occurred, previously identified by techniques of road safety analysis.Taking into consideration the areas of linear influence around the incident point, it was found that 50% of the detected stress points also corresponded to incidental points; vice versa, about 56% of the incidental points were a part of the zones of influence around stress points.Another element of interest that emerged from the first experimental phase concerns the rise in stressful conditions associated with the presence of important road works (due to the construction of the new underground line M4).In fact, even during uncongested traffic hours, the user was stressed due to the continuous deviations.In particular, a considerable number of stressful points (identified as such on the basis of the monitored parameters) were recorded where the deviations and the alternative route were not adequately indicated.
The second experimental phase represented a development and a deepening of the first phase; for this part, a significantly different approach was adopted, especially considering the data elaboration step.On the basis of the monitored parameters, it emerged that 38.7% of the cases reported stressful conditions in high-accident areas.On the other hand, the state of relaxation was registered in zones of low accidents in 40.8% of the overall sections considered.These results give an indication of the actual correlation between the psychophysical state of the drivers and the safety conditions.With the development of a scoring method, it was possible to combine the results of all the drivers undertaking the test, eliminating, as much as possible, the elements of uncertainty, and identifying the most stressful areas.Each area was given a score that conveyed information about the level of stress.It emerged that, among the 15 sections with the highest score, 12 of them were also sections with high accident rates.In terms of preventive road safety analysis, it is also possible to proceed by reversing the correlation.Out of 14 high-accident sections, 12 of them were also subject to high stress.This means that, if we want to apply the method for prevention, intervening on 25% of the route (i.e., limiting the possible interventions to a selection of more critical areas from the stress point of view) would identify 80% of the critical areas for car accidents, even without historical data.
Assuming that the emerged relationship between stressful points and accident points also features the routes where no accident historical data is available, the method can prove to be a useful support to preventive analysis on road safety, which is currently mainly oriented toward problems concerning the infrastructure.
The use of wearable devices allowed the collection of the physiological parameters described in Section 2.1, enabling the effective investigation of the correlation between the psychophysical state of the driver and the results of the accident analysis, and demonstrating how it is possible to integrate, in a more explicit way, the elements related to human behavior within these techniques.
The research gave encouraging results, with many possible future developments.Among the possible investigations, there are those concerning the analyzed parameters and tools used for collection and monitoring.The impossibility of collecting second-by-second the values of LF and LF/HF (not just at time intervals) is a limitation that makes it difficult to identify precisely the stressful path areas.Therefore, the association of these parameters with additional elements, such as the GSR, proved to be an effective solution to the problem.Monitoring and gathering additional parameters could contribute to a refinement of the results.For example, of great importance could be the recording of the variation of pupil diameter over time, measurable through eye-tracking devices; this parameter is able to return information about the psychophysical state of the tester [39,40], and it would allow obtaining interesting information.
A further development could concern the devices used.These could be designed so as to grant the opportunity for management and synchronization by a simple user as the tester, in order to develop an experiment in which data are collected for weeks or months.The tools should become more user friendly while maintaining the quality standards of the recorded data, which was a feature of the non-commercial devices used in the tests presented.A useful indication for this purpose, even considering issues of user acceptance, can be found in the literature [32,41,42].
The purpose of this work was to investigate whether or not there is a correlation between driver stress and road accidents.The results showed the existence of such a correlation.To deeper investigate this topic, an important future development will surely be an increase in the number of tests and a better characterization of the experiments and testers.In fact, one of the main future goals could be the creation of a database of tests that allows a varied and complete clustering (for example, based on variables such as the time of the day, traffic conditions, road environment, vehicle typologies, driver age, gender, and driving experience) and a cross-check between all these variables.
Also, a study with a more complete correlation could be carried out using accident data collected by insurance companies, which also concern accidents without deaths or injuries.Of notable interest could be to have different kinds of users (such as cyclists and motorcyclists) undertaking the tests, even in contexts different from the urban environment, such as suburban roads or motorways.
Figure 1 .
Figure 1.Procedural diagram of the study.
Figure 1 .
Figure 1.Procedural diagram of the study.
Figure 2 .
Figure 2. (a) T-shirts used for the tests, equipped with sensors; (b) female version of the wearable sensor.
Figure 2 .
Figure 2. (a) T-shirts used for the tests, equipped with sensors; (b) female version of the wearable sensor.
Figure 4 .
Figure 4. Example of analysis and location of traffic accidents and subdivision by type (QGIS elaboration of Google Maps).Figure 4. Example of analysis and location of traffic accidents and subdivision by type (QGIS elaboration of Google Maps).
Figure 4 .
Figure 4. Example of analysis and location of traffic accidents and subdivision by type (QGIS elaboration of Google Maps).Figure 4. Example of analysis and location of traffic accidents and subdivision by type (QGIS elaboration of Google Maps).
Figure 5 .
Figure 5. Path selected for the first set of experiments (QGIS elaboration of Google Maps).
Figure 5 .
Figure 5. Path selected for the first set of experiments (QGIS elaboration of Google Maps).
Figure 6 .
Figure 6.Path selected for the second set of experiments (QGIS elaboration of Google Maps).
Figure 7 .
Figure 7.Example of the information obtained with the use of the Kubios software (University of Kuopio, Kuopio, Finland) for heart rate variability (HRV) analysis[36,37].
Figure 6 .
Figure 6.Path selected for the second set of experiments (QGIS elaboration of Google Maps).
17 Figure 6 .
Figure 6.Path selected for the second set of experiments (QGIS elaboration of Google Maps).
Figure 7 .
Figure 7.Example of the information obtained with the use of the Kubios software (University of Kuopio, Kuopio, Finland) for heart rate variability (HRV) analysis[36,37].
Figure 7 .
Figure 7.Example of the information obtained with the use of the Kubios software (University of Kuopio, Kuopio, Finland) for heart rate variability (HRV) analysis[36,37].
Figure 8 .
Figure 8. Example of correlation matrix, where axy is the number of recorded correlations between psychophysical state and accident rate.
Figure 9 .
Figure 9. Subdivision in homogeneous zones of the route for the second experimental phase (QGIS elaboration of Google Maps).
Figure 9 .
Figure 9. Subdivision in homogeneous zones of the route for the second experimental phase (QGIS elaboration of Google Maps).
Figure 10 .
Figure 10.Location of the peak stress points (QGIS elaboration of Google Maps).
Figure 11 .
Figure 11.Example of a route-accidents identified in red, and stress points in blue.Circles indicate the buffer around accidental points (QGIS elaboration of Google Maps).
Figure 10 .
Figure 10.Location of the peak stress points (QGIS elaboration of Google Maps).
17 Figure 10 .
Figure 10.Location of the peak stress points (QGIS elaboration of Google Maps).
Figure 11 .
Figure 11.Example of a route-accidents identified in red, and stress points in blue.Circles indicate the buffer around accidental points (QGIS elaboration of Google Maps).
Figure 11 .
Figure 11.Example of a route-accidents identified in red, and stress points in blue.Circles indicate the buffer around accidental points (QGIS elaboration of Google Maps).
Figure 12 .
Figure 12.Example of a route-accidents identified in red, and stress points in blue.Circles indicate the buffer around stress points (QGIS elaboration of Google Maps).
Figure 13 .
Figure 13.Correlation matrix of psychophysical status and the level of accident.Data are expressed in percentages.
Figure 12 .
Figure 12.Example of a route-accidents identified in red, and stress points in blue.Circles indicate the buffer around stress points (QGIS elaboration of Google Maps).
Figure 12 .
Figure 12.Example of a route-accidents identified in red, and stress points in blue.Circles indicate the buffer around stress points (QGIS elaboration of Google Maps).
Figure 13 .
Figure 13.Correlation matrix of psychophysical status and the level of accident.Data are expressed in percentages.
•
Validation of the method through the development and testing of an experimental protocol; • Identification of possible correlations between stressful/relaxing points and black spots, identified through accidental analysis. | 15,498 | 2018-07-26T00:00:00.000 | [
"Engineering",
"Psychology",
"Computer Science"
] |
MIXED CONVECTION IN TECHNOLOGICAL RESERVOIR OF THERMAL POWER STATION
The problem of mixed convection of a viscous incompressible fluid in an open rectangular reservoir with inlet and outlet of mass with considering nonuniform heat sink at the external borders of the solution domain is solved. The region of the solution was limited by two vertical and by one horizontal walls of finite thickness and one free surface. The flat nonstationary mixed convection within the framework of Navier-Stokes model is examined for liquid and thermal conductivity for solid walls. Distributions of hydrodynamic parameters and temperatures with different intensity of heat sink on the outer contour of the cavity show a change in the intensity of heat sink on the region boundaries of the solution leads to scale changes in the structure of flow and temperature fields of the liquids.
Introduction
The scales of modern power engineering are such, that its interaction with the environment has not only local, but also global in nature [1,2]. When assessing the impact of power engineering on nature, finding measures for the limitation of the negative consequences of this action, and also for creating the optimum thermal systems for environmental protection is necessary the analysis of different hydrodynamic processes. It is essential to the hydrothermal regime of the reservoir-coolers with hot water from the turbine condensers [1,2]. This forecast is important both from the point of view of the thermal pollution of aqueous medium and from the point of view of the temperature distribution of water recirculation. When designing such reservoirs and selection of their technological parameters the need for analysis of thermal conditions of objects, which are the cavity, filled with an incompressible fluid and the sources of inlet and outlet of mass, significant temperaturegradients and heat exchange on the outer contour of cavity. Analysis of the physical picture of flow shows that under such conditions must be realized the regime of mixed convection, complicated by heat sink from the outer boundaries of the analysis region. In many in practice significant cases this heat sink plays important role in the formation of the thermal condition of object and water flows. Up to now the simulation of such flows in the combined setting, which considers the influence of environment on the flow pattern and the temperature field of object was not carried out [1][2][3][4][5]. The purpose of this work is the numerical simulation of the mixed convection of liquid in the open reservoir with the local sources of input and output of mass considering the heat sink to the environment around the outer contour.
Physical model
Is examined the flow of the incompressible viscous fluid and heat exchange into the cavity of that having two vertical, one horizontal walls of finite thickness and one free surface, with two sections of input and output of liquid (Fig. 1).
When the problem is assumed that the temperature of the injected fluid substantially exceeds the initial temperature of the medium in the cavity and is considered known. Mass arrival is also known value. Heterogeneous boundary conditions are assigned on the outer boundaries of region. Heterogeneity is caused by different thermophysical characteristics of media and by conditions of heat exchange on the boundaries of the solution domain. Liquid is considered viscous, heat-conducting, laminar flow regime. Mass outflow from the upper limit due to evaporation is not considered. All boundaries except the sections of inlet and outlet of mass are considered liquid-tight. The thermophysical properties of liquid and solid phase do not depend on temperature.
Laminar flow regime is also most typical for the attainable in the task in question values ofthe Reynolds and Grashofnumbers. The draining of mass from the free surface of reservoir due to the evaporations is, as a rule, achieved in practice, but the intensity of this process is not so great so that it could change the configuration of cavity by the filled water, or its sizes.
Task is examined in the nonstationary setting due to the ability of the material of solid walls to accumulate by heat-and significant temperature differentials between the introduced into the cavity liquid and the initial temperature of solid walls. In the general case different arrangements of openings for input and output of liquid from the cavity are possible. Are examined the most typical versions ( Fig. 1), realization of which, leads to the formation of the structures of flow of liquid most interesting for the analysis. It is also assumed with the formulation of the problem that the contact on the interfaces "liquid -solid wall" is ideal, but heat exchange conditions on the outer boundaries of the solution region do not depend on time. The ideality of the contact of liquid and solid wall in the task in question is much more substantiated, than for example in the analogous models for the contact of two solids body. Liquid fills all roughness elements of concrete (or soil) in the reality. Therefore heat transfer through this contact surface in practice insignificantly is differed from ideal. Also in the real practice the characteristic times of a change of heat exchange conditions on the free surface of technological reservoirs are much more than the characteristic transit time of energy in the liquid both due to the convection and due to the thermal conductivity.Special importance in in this problem are the boundary conditions on the outer boundaries of the solutionregion (Fig. 1). These conditions determine the intensity of heat sink from the outer boundaries and essential influence on the flow conditions of liquid, and, correspondingly, to the intensity of heat transfer. . Based on the analysis of the various embodiments of the scheme in practice can be on the right, left and bottom borders of the region solutions exhibit boundary conditions of various kind. For the correct use of fourth kindconditions necessary to enlarge the dimensions of the solution region by the introduction of additional subregions to the values x and y, with which the front of warming up in any regimes does not reach these outer boundaries. This approach substantially complicates the algorithm of problem solution. The use of heat insulation conditions on the outer boundaries of the solution region (ris.1) is not legitimate, since under the actual conditions with different gradients of temperatures the heat sink into the environment from these boundaries is always accomplished. The boundary conditions of the second kind on the discussed boundaries were selected for these reasons.
It should be noted that on the boundaries of the enclosing walls the use of boundary conditions of the second kind during the entire apparent formalization of real physical process can be substantiated sufficiently reasoned. Thus, for instance, is possible solution of the problem for the relatively small time interval in question, but taking into account heat propagation directly in the ground. Boundary conditions ofsolutioncan define a range of possible changes in the heat flux on the border "concretesoil". This characteristic will change in the time very slowly in connection with the high energy content of real soil. Accordingly, this solution creates objective conditions for using the boundary conditions of the second kind on the outer duct of reservoir.
Mathematical model and method of solution
Transfer process of mass, momentum and energy in such a setting is described by the unsteady Navier-Stokes equations for the liquid phase and the heat equation for the solid phase [6][7][8]. The problem was solved in the dimensionless formulation.
Accordingly, the dimensionless Navier-Stokes equations in the Boussinesq approximation in variables "vorticity -stream function -temperature" for the liquid phase (mixed convection mode) and the heat equation for the solid phase will be: The 2 nd International Youth Forum "Smart Grids" x internal border between the solid and liquid phases, parallel to the axis 0X 0 x section of inlet liquid The system of equations (1) -(4) with the appropriate initial and boundary conditions is solved by finite difference method [6][7][8].
Equations It should be noted that the ranges of the dimensionless quantities and size characteristicswere selected based on the following conditions. First -matching range of parameters inreal industrial waters.Second -the real scales of existence both of the forced and free convection without the degeneration of these mechanisms of heat transfer. Furthermore, were controlled the conditions of the geometric similarity of real systems and used in the mathematical description of process models. In this case also were examined in essence not the most favorable for the realization "conjugate" heat transfer [8] ranges of change both the dimensional values and dimensionless complexes. Thus, for instance an increase in the temperature of the introduced into the cavity in question liquid by 20…30° could substantially change the relationship between the characteristic times of the realization of the process of the forced and free convection, but extremely possible versions were not examined. Fig. 2 shows typical results of the solution of (1-4) with varying intensity heat sink on the borders of the outer contour. Fig. 2a shows the streamlines and temperature field for the case when the left, right and bottom borders of the outer contour insulated. At the top of the cavity seen one an extensive vortex that is formed by natural and forced convection. In this case the heated liquid due to natural convection seeks upwards. Accordingly, the cold liquid, falling toward the left side, running out the main flow to the bottom of the cavity. Due to the high intensity of the vortex, the heated liquid rises up along the right side only to the outlet. In the cavity is a relatively uniform temperature distribution due to the fact that the liquid is cooled only at the upper boundary and the heat sink on the other boundaries is absent. Fig. 2b shows the streamlines and temperature field for the case when the lower boundary of the outer contour of the heat sink is present, and the left and right boundaries are insulated. It also shows
Analysis of numerical simulation results
The 2 nd International Youth Forum "Smart Grids" 01005-p.5 the formation of a vortex extensive, but already at the bottom of the cavity. The main mechanism of its formation are forced convection forces. Hot liquid due to the forces of natural convection rises. In the presence of heat removal from the lower boundary of the external contour, cooled liquid moving along the bottom directs the main stream to the left wall and the upper boundary of the cavity. The temperature distribution in this case is substantially uneven. In the upper part of the cavity is almost 50 degrees temperature higher than the bottom. This happens due to the fact that the coolant in the lower part of the cavity is practically not mixed with the main heated stream. Fig. 2d shows the streamlines and temperature field for the case, when on the right boundary of outer contour there is heat sink, and lower and right boundary are heat-insulated. Seen the formation of two vortices in a cavity under consideration. Upper vortex exists due to the forces of the natural and forced convection. Flow relative to cold liquid descends on the left wall, pressing input flow downward. Lower vortex is formed due to the forced convection, as a result the motion of main flow and free convection during cooling of liquid by heat sink from the right boundary of cavity. Vortex in the lower region is scale than the vortex in the upper region, since the size of upper vortex is limited to the being risen flow of hot liquid. Temperature field is sufficiently even, since the main flow is passed practically along the diagonal of cavity. A drop in the temperature not more than 35 degrees, since 2 vortices are formed, in which sufficiently intensively occurs the heat exchange with the main flow.
The distributions of the hydrodynamic parameters and temperatures with different intensity of heat sink on the outer duct of the cavity in question show that, a change in the intensity of heat sink on the boundaries of solution region leads to scale changes in the structure of flow and temperature fields of liquids.
All presented as illustrative materials are obtained for the regimes sufficient moderate mixed convection. Is in practice possible the achievement, for example, of the large scales of temperatures or intensities of heat sink on the external contour. In such cases chosen regularities are manifested substantially more distinctly.
CONCLUSION
The influence of the varied conditions of heat exchange on the boundaries of rectangular cavity with the sources of inlet and outlet of mass to the regimes of the convection of the viscous incompressible fluid into the conjugate formulation is theoretically investigated. The obtained theoretical consequences give the new information, which characterizes convective flow regime and more for construction and approval of models of mixed convection in the conjugate formulation.
On the basis obtained results it is possible to make the conclusion that by regulating the intensity of heat exchange on the boundaries of rectangular region it is possible to govern the thermal regime of the liquid with implementation mixed convection under the conditions for inlet and outlet of mass into the region of limited sizes.
Work performed under the research state assignment «Science» (Code of Federal Target Scientific and Technical Program 2.1321.2014). | 3,075.8 | 2014-01-01T00:00:00.000 | [
"Physics",
"Engineering"
] |
Training deep learning models for cell image segmentation with sparse annotations
Deep learning is becoming more prominent in cell image analysis. However, collecting the annotated data required to train efficient deep-learning models remains a major obstacle. I demonstrate that functional performance can be achieved even with sparsely annotated data. Furthermore, I show that the selection of sparse cell annotations significantly impacts performance. I modified Cellpose and StarDist to enable training with sparsely annotated data and evaluated them in conjunction with ELE-PHANT, a cell tracking algorithm that internally uses U-Net based cell segmentation. These results illustrate that sparse annotation is a generally effective strategy in deep learning-based cell image segmentation. Finally, I demonstrate that with the help of the Segment Anything Model (SAM), it is feasible to build an effective deep learning model of cell image segmentation from scratch just in a few minutes.
Introduction
Deep learning has become a powerful approach to bioimage analysis. In particular, cell image segmentation is a topic that has attracted the attention of many researchers because it is a fundamental step in many analysis workflows. StarDist (1,2) is a widely used algorithm that was originally developed for 2D cellular images (1) and later extended to 3D images (2). Cellpose (3,4) has recently been developed as a universally applicable cell segmentation algorithm. In these algorithms, adequate performance can be achieved by applying a versatile pre-trained model if the target image is a typical cellular image. However, it requires training a model with additional annotated data with characteristics similar to the target image when the pre-trained model is not applicable. Because the current implementation of the algorithms requires annotation to be performed on the entire region of the input images, the user has to spend considerable time on the annotation process. On the other hand, ELEPHANT (5), an algorithm for cell tracking, is a method that can train deep learning models with sparse annotations (Fig.1). ELEPHANT performs the tracking task in two stages: cell detection and linking, where cell detection is performed internally using U-Net (6, 7) based segmentation. In ELEPHANT, training of the segmentation model is performed using labels generated from sparse ellipse (2D) or ellipsoid (3D) annotations that represents cell instances. Because the deep learning model in ELEPHANT is designed to work with sparse annotation, users do not need to annotate all cells in input images. Instead, they interactively iterate a cycle of annotation, training, prediction and proofreading. I introduced sparse annotation to StarDist and Cellpose by making their loss functions compatible with sparsely annotated labels. In this work, I describe how sparse annotation-based training works with these algorithms. For each algorithm, I investigated the relationship between the number of annotations and performance and how the behavior differs with and without background pixel annotations, in addition to cell annotations. I further showed that the selection of sparse annotations can change performance, even when training is performed with the same number of annotations. As a proof-of-concept for this project, I generate sparse annotations by running the Segment Anything Model (SAM) (8) on QuPath (9) and train the StarDist model from scratch, demonstrating that it is feasible to build an effective deep learning model of cell segmentation in just a few minutes. These sparse annotation-supported algorithms are available as open source.
Results
Training of deep learning models for cell segmentation with sparse annotations. A dataset with sparse cell annotations, containing 447 training data and 50 validation data, was created by the procedure described in Methods (Fig.2). Briefly, there are three annotation approaches: (i) dim nuclei preferentially, (ii) bright nuclei preferentially, and (iii) both mixed. I also included conditions with additional background labels for each of them. The number of annotations was incrementally increased to train and evaluate the deep-learning models (Fig.2). StarDist, Cellpose, and ELEPHANT models were trained using the training data under these conditions, and their performance was evaluated using the validation data. In StarDist, D R A F T cell nuclei were well identified with sparse annotations, but many false positives were observed in conditions that did not include background annotations (Fig.3, 6). When dim nuclei were preferentially annotated, the Recall score increased, but the Precision score decreased. On the other hand, when bright nuclei were selected preferentially, the Recall score was low when the number of annotations was around 4.6%. When the number of annotations reached about 18.5%, the Recall score improved while maintaining the Precision score. A mixture of dim and bright nuclei showed intermediate behavior. In Cellpose, the boundary between nuclei and background regions could not be discriminated in the conditions without background annotation, and both Recall and Precision showed low scores (Fig.4, 6). On the other hand, when background annotations were included, training with sparse annotations performed well. As shown in StarDist, prioritizing dim nuclei increases the Recall score, while prioritizing bright nuclei increases the Precision score, and including dim and bright nuclei exhibited intermediate properties.
In ELEPHANT, effective models could be built with sparse annotations, even without background annotation (Fig.5, 6). This could be due to the fact that in ELEPHANT, the foreground annotation is converted to two-layer labels: a center region and a periphery region (5). The tendency of performance with intensity-based nucleus selection was similar to StarDist, and Cellpose. Including both dim and bright nuclei seemed the best approach, especially when the number of annotations was limited.
Training of a deep learning model from scratch in a few minutes. To demonstrate that training deep learning models based on sparse annotation is practical, I implemented extensions on the widely used image analysis tool QuPath (9). To facilitate the annotation process, I have implemented an extension to perform SAM (8), which enables the generation of a cell nucleus annotation from a bounding box. In addition, I implemented an extension that calls sparse annotationbased training and inference with a StarDist model. The training was performed from scratch with no prior training.
Discussion
This study showed that background annotation is essential for training the StarDist and Cellpose models. Introducing the embedding consistency loss used in (10) may enable training them without background annotation. However, a major concern is that it requires another convolutional neural network in the training phase, which would increase the computational cost.
Conclusion
In this study, I explored sparse annotation-based training of deep learning models for cell image segmentation. Widely used cell segmentation algorithms, StarDist and Cellpose, were made compatible with sparse annotation. I trained the models of the modified versions of StarDist and Cellpose, and ELEPHANT's segmentation module with sparse annotations generated under multiple conditions, including three strategies: (i) dim nuclei preferentially, (ii) bright nuclei preferentially, and (iii) both mixed, and five annotation percentages ranging from 4.6% to 100%. I showed that for training StarDist and Cellpose models, background information is essential. I found that recall and precision scores changed depending on the annotation strategy; prioritizing dim nuclei produced higher recall scores, and prioritizing bright nuclei produced higher precision scores. The results showed models trained with relatively small sparse annotations (4.6% to 18.5%) performed similarly to fully annotated data. Finally, I demonstrated that with the help of SAM, an efficient StarDist model was trained from scratch with a few sparse annotations just in a few minutes.
Methods
Adaptation of StarDist and Cellpose algorithms to sparse annotation. StarDist and Cellpose are widely used algorithms, but require densely annotated data for training with custom data. I adapted these algorithms to sparse annotation with the same idea as implemented in ELEPHANT. The modification is very simple: the loss function is calculated by ignoring unannotated pixels in the training phase. These changes can be found in the following GitHub repositories (https://github.com/ ksugar/stardist-sparse and https://github. com/ksugar/cellpose-sparse).
Dataset preparation. I used a dataset from the StarDist paper (1). The dataset contains 447 training data and 50 validation data, which are a subset of the Data Science Bowl 2018, an annotated collection of 2D nuclear images acquired by fluorescence microscopy. In addition to the original fully annotated data, sparsely annotated data were prepared for the evaluation in this study. In generating the sparsely annotated data, a maximum of 2n nuclei (n = 1, 4, 16, 64, 256) were selected in each image, not exceeding the number of nuclei in the image, under the following three conditions: (i) 2n nuclei with the lowest intensities (min), (ii) 2n nuclei with the highest intensities (max), and (iii) n nuclei with the lowest intensities and n nuclei with the highest intensities (min-max). Cell instances with a minor axis calculated as zero were excluded. Here, the cell annotations were prioritised over the background annotations if they are overlapped, and annotated regions outside the image area were ignored.
Evaluation of performances.
Performance evaluation was carried out on the validation data using the evaluation method in the StarDist library (1). In this method, the detected cell instances are matched with the groud-truth cell instances and if their intersection over union (IoU) exceeds a threshold value, they are counted as true positive (TP), otherwise they are counted as false positive (FP). After the matching, the remaining ground-truth instances were counted as false negative (FN). In this study, the threshold was set at 0.5 and P recision = T P T P +F P , Recall = T P T P +F N , F 1score = 2T P
D R A F T
2T P +F P +F N were adopted as the evaluation metric.
Training of deep learning models. The following data augmentations were stochastically applied to input images during training: rotation, resize, horizontal/vertical flip, intensity modification. The batch size was set to 8, the number of steps per epoch to 56, training was performed for 100 epochs, and the model from the last epoch was adopted. | 2,261 | 2023-06-13T00:00:00.000 | [
"Computer Science",
"Biology"
] |
Bulk and Surface Defects in Nanoporous SiO2 Ceramic
The methods of electron paramagnetic resonance and optically stimulated electron emission have been used to study the conversion of defects in samples of a nanostructured SiO2 ceramic synthesized by the thermal decomposition of polysilazane HxCyNzSi. The ceramic samples additionally underwent a thermal treatment and were exposed to accelerated electrons.
Introduction
Silica is one of the most important materials in optics and semiconductor engineering, but so far the specific features of the formation and conversion of defects in its different low-dimensionality modifications have been poorly understood. One of the possible methods for investigating these materials is the electron paramagnetic resonance (EPR), which provides data not only on the concentration of defects, but also on their nature considering the values of the g-tensor and the superfine interaction constants. The information capacity of EPR can be expanded by the use of additional spectroscopic techniques.
The aim of this work was to study the nature of defects in porous nanostructured SiO 2 and the effect of the low dimensionality on their magnetic and photoemission properties.
Experimental
The objects of study were silica samples synthesized by the thermal decomposition of polysilazane H x C y N z Si in air. They were a nanostructured porous ceramic. The basic characteristics of the samples after different thermal treatment regimes are given in table 1.
The samples 1-3 were exposed to electrons (an energy E = 10 MeV and a fluence Ф = 10 16 cm -2 ) in an M-20 accelerator-microtron. The EPR spectra were measured in a 3-cm spectrometer with a highfrequency modulation of the magnetic field. It allowed making measurements in fields as high as 7.5 kGs, was equipped with devices for adjustment, stabilization, and measurement of the temperature, and was outfitted with a computer system for recording of spectra. 1 The corresponding author. The spectra of nonstationary optically stimulated electron emission (OSEE) in the range of 4.9 to 6.2 eV were measured at room temperature in a vacuum of 10 -4 Pa using a VEU-6 secondary emission multiplier as an electron detector. The samples were excited by the light of a DDC-30 deuterium lamp with a DMR-4 monochromator. The method of processing the measured spectra is described in detail elsewhere [1].
Results
According to the results of the electron microscopic examination, the surface of the samples had characteristic nanostructural pores about 100-500 nm in size, which could appear due to the release of the gaseous phase (figure 1). Some ordering of the spatial distribution of pores in the samples is worthy of note since it adduces evidence that this material later can be the basis for development of ordered nanostructures. The measurements of EPR spectra, which were performed on the unirradiated samples 1-3 at temperatures of 300 and 163 K, did not reveal the presence of paramagnetic defects in concentrations sufficient for the measurements. Oppositely, a narrow intensive signal with the g-factor close to 2, which was stable in air, was observed in the samples 4. Figure 2 depicts a spectrum, which was obtained by simultaneous recording of the above signal and a signal of a DPPH (diphenyl-picrylhydrazyl) test sample. As determined from the measurements at room temperature, the g-factor of the signal of the samples under study was 2.0026. For the DPPH test sample the g-factor was g = 2.0036. The exposure to fast electrons, which was aimed at producing a high concentration of paramagnetic defects, did not lead to visible changes in the spectrum of the samples 4, but had a considerable effect on the spectra of the samples 1-3 (figure 3). The basic parameters of the EPR spectra are given in table 2.
The results of measurements of the OSEE spectra of the samples 1-3 are shown in figure 4. The parameters of the computer-simulated spectral lines are given in table 3.
Discussion
The measurement results demonstrated that the lines of the spectrum of the samples 4 were most intense (see figure 2). According to the X-ray diffraction analysis, these samples contained both carbon and silicon carbide. It is known that a narrow isotropic air-stable signal with a similar g-factor (2.0029) was observed in mechanically broken diamond and silicon carbide. It was related to a broken covalent bond of a 12 C atom [2]. A narrow signal with g = 2.0029 can also be assigned to a defect related to an unpaired electron of a carbon atom. The line with the g-factor = 2.0027, which was repeatedly observed in the EPR spectrum of the silicon surface [3], appears due to the presence of impurities containing carbon compounds. It can be assumed that the EPR signal of the samples 4 has an analogous origin and is related to centers of carbon with a broken covalent bond. These centers were present on the surface of the pores, which appeared during the thermal treatment. The line with g = 2.0026 in the spectrum of the samples 1 ( figure 3 coincide well with the spectrum of the methyl radical • CH 3 , which can be part of polysilazanedecomposition organic compounds on the surface or in the bulk of the samples [4]. The EPR spectrum of the samples 2 ( figure 3) has a complicated structure. Although the signal of 12 C can be present among the central lines of the spectrum of these samples, this region should be referred primarily to E' centers. The obtained values of the g-factor for the observed structure (2.0026, 2.0016, and 2.0007) are close to those of an E γ ΄ center in amorphous silica (2.0029, 2.0017, and 2.0015 [5]) and quartz glasses (g || = 2.0018, g ⊥ = 2.0004 [6]). However, the same region can include signals of an E΄ s center (g || = 2.0018, g ⊥ = 2.0003 [2]), which is a surface analog of an E γ ΄ center. Also, the data on the composition of the samples probably suggest the presence of • C-Si 3 centers with a broken bond of a carbon atom in the silicon environment.
The low-intensity broad signal with the g-factor of ~2.0035, which is observed in the spectrum of the samples 3 ( figure 3), most probably is due to the defects related to a broken covalent bond of silicon. According to the optical spectroscopy data, the samples 3 are characterized by the presence of oxygen-deficient ≡Si-Si≡ and =Si: centers, ≡SiSiSi≡ clusters, and nanoscale inclusions of crystalline silicon. Then it is probable that the exposure to accelerated electrons leads to the formation of paramagnetic ≡Si • centers analogous to P b centers observed in Si-SiO 2 systems [7].
Thus, the EPR data point to a change in the composition of the samples under study during their thermal treatment, leading to a considerable decrease in the concentration of the centers, which are due to carbon-hydrogen compounds and, later, to compounds of silicon and oxygen.
An important feature of the OSEE method is relative thinness of the analyzed layer of substances and a strong dependence of the spectrum on the surface treatment quality. An analysis of the OSEE spectra ( figure 4) and a comparison with the data in [1] suggest that centers of the E' type were present in all the samples studied. The concentrations of the bulk Е΄ γ centers corresponding to an isolated three-coordinated silicon atom and the Е΄ 2 centers related to the presence of a hydroxyl group proton are much lower than the concentrations of their surface analogs. The most intensive in the samples 1 is the OSEE signal of surface E S '(2) centers. The growth of the concentration of surface centers in the samples 2 correlates well with the increase in the porosity of the material. The subsequent decrease in the concentration of the E 2S ' centers in the samples 3 is in agreement with the removal of the hydroxyl group during annealing and a structural rearrangement of the sample. The growth of the concentration of E S '(1) centers in the samples 3 (figure 4) slightly contradicts the EPR data; nevertheless, it can be explained by considerably different sensitivities of the research methods.
Conclusion
The study demonstrated that the thermal treatment of nanostructured silica changes the number and the type of paramagnetic defects, primarily due to a variation in the composition of the material studied. As the thermal treatment temperature rises, the number of organic paramagnetic impurities decreases considerably and oxygen-deficient bulk and surface E' centers are formed.
The fact that the samples under study contain high concentrations of surface E' centers is a specific feature of the nanoporous SiO 2 ceramic. | 2,002 | 2010-11-01T00:00:00.000 | [
"Materials Science"
] |
Making Data Reports Useful: From Descriptive to Predictive
The purpose of analyzing data is to transform it into useful knowledge. Descriptive analytics renders factual information about research and events that can be used to relate an organization’s environment to its activities. However, descriptive analytics alone is not enough to gain understanding and possibly predict the future. Minding only the output of such an analysis can mislead the researcher and decisionmaker. Because many factors influence results, it is essential to advance the prediction of future challenges through statistical analytics and factual patterns that dictate the environment with scientifically tested models. The data patterns, types of analysis, and attributes the prediction will be based on are all important. Data influenced by unforeseen variables make for poor predictions, such as the evening capacity report data in this study.
Introduction
Exploratory research helps scientists develop initial hunches or insights [1]. However, the tradition in medical science research presentations is descriptive analytics. Descriptive analytics and statistics provide images of what happened in experiments based on past data. Yet, for health care organizations, this reactive approach helps to present what happened historically, but it does not help forecast future outcomes. The key to descriptive analytics is to present data effectively with statistical functions to reflect what really happened and with visual tiles for easy understanding.
Predictive analytics, if used appropriately, has been proven to foresee the future with precision [2]. This study continues to examine emergency department (ED) capacity reporting data during the coronavirus disease 2019 (COVID-19) pandemic the author descriptively examined in a previous publication in this journal (August 2020) that described the importance of presenting descriptive data in a meaningful, continuous, and easy-to-understand fashion [3]. From data to insights, the study further advocates for predictive analytics, which provides evidence of the associations between variables and identifies areas in need of improvement. The aim is to help health care organizations to utilize available data analytics tools to produce valuable information applicable to assist health care leaders in decision making and improve services in the future. Application of predictive analytics may not yield completely accurate results, but it does provide a clearer picture of what might happen in the future based on past events.
Materials And Methods
As presented in a previous report [3], the hospital studied here is a state safety net health organization. It is a 440-bed acute care teaching hospital in the Western region of the United States. It has a 45-bed capacity emergency room and is licensed for 48 intensive care beds.
Twice a day, the nursing house supervisor distributes the emergency room capacity alert reports to medical staff via email. These reports include ED census and numbers of ED holds with and without bed assignment. It also includes COVID-19 cases held in the ED and, through calculation, bed availability is determined. Thus, there are five parameters identified in this study: ED census, ED hold with bed assignment, ED hold without bed assignment, COVID-19 patients holding in ED without bed, and bed availability at the hospital.
Predictive analytics involves forecasting, which dictates timely decision making. In this study, forecasting was applied to predict bed availability at the hospital through ED capacity reporting data. It is not possible to predict the future demand for hospital beds with certainty, but an estimate can be realized from past data. The data collected in this study revealed trends from May 2020 to July 2020. Linear regression performed by Excel® (Microsoft, Redmond, WA, USA) was used to determine attributes' associations and forecast bed availability with suitable independent variables. A paired t-test was applied to test the significant similarity between forecasted outputs and what really happened during the month of August 2020 (the true data). Waikato Environment for Knowledge Analysis (WEKA®, University of Waikato, New Zealand) machine learning software was used to visualize the forecasting results and to test the degree of accuracy of the models by classification.
Results
Data in this study consisted of the morning reported data, which represented how resources were allocated at night, and the evening reported data, which represented how efficiently resource allocation occurred during the day.
The analysis began with regression analysis and forecasting. Regression is about quantifying the relationship between two or more variables. As presented in Figure 1, the study began with regression analytics to determine what ED holding situations (dependent variables) would be at differing levels of bed availability (the independent variable). On the horizontal axis is bed availability at the hospital, and on the vertical axis is the bed availability related to ED census, ED holding without bed assignment, ED holding with bed assignment, and COVID-19 related hold in ED. The regression plots then tried to fit a straight line to the data and put a formal equation (y) into each of the dependent variables.
COVID-19: coronavirus disease 2019
The graph's equations connect bed availability at the hospital to each holding parameters and an R-square value (how good the regression line is). In general, an R-square value above 70% can be depicted as a wellmodeled regression able to capture the majority of value points. For example, regression between bed availability at the hospital and ED hold without bed assignment is considered a particularly good fit with an R-square value of 0.9395 (93.95%). Yet, lower values of R-square output, such as that of ED hold with bed (20.79%) and COVID-19-related hold in ED (32.30%), should not be immediately discounted where the Pvalue of the parameter in computing summary may represent some merits in the regression model. In some cases, it is possible that additional predictors can increase the true explanatory power of the model. Even when R-square is low, low P-values still indicate a real association between the significant predictors and the response variable.
Multiple linear regression estimates the relationship between a quantitative dependent variable and two or more independent variables using a straight line. In multiple regression analytics, multiple independent predictors are used in an attempt to forecast bed availability at the hospital (the response variable). The preliminary multiple regression examination revealed that both ED hold with bed (P-value = 0.3231) and COVID-19-related hold in the ED (P-value = 0.2795) were not significantly associated with bed availability at the hospital and were omitted from the analysis. The final model was designed to associate two predictors, ED census and ED hold without bed assignment, to bed availability at the hospital and were deemed to be strongly reliable. The R-square values of the final multiple regression models in the morning and evening were 95% and 83%, respectively. The final regression model output summary is shown in Table 1. It depicted the calculated values presented by multiple regression of the final model in the morning and evening. P values were such that the null hypothesis was rejected with 95% level of confidence in all predictors. All evidence available strongly validated the data model.
Coefficients
Standard Error t Stat P-value Visualization of forecasting exercises was completed with WEKA® machine learning software. The forecasting results are shown in Figure 2 and Figure 3. Figure 2 depicts forecasting results based on the morning dataset, and Figure 3 presents the forecasting output using the evening dataset. The forecast setting was placed to forecast 30 data points to mime 30 days in August 2020 and displayed after the brown arrow in the figures. It is important to verify and test whether the forecasting output is factually accurate or close enough to be significantly similar to what really happened in the month of August 2020. To examine the performance of the forecasting model, paired T-tests of two sample means were used to compare the forecast 30 data points with the factual data collection in August of 2020 (
TABLE 2: T-Test, Paired Two Sample for Means on predicted and August values
There was no statistically significant difference between all pairs, namely the ED census, ED hold without bed assignment, and the availability of bed at the hospital with the morning data set. Yet, the comparison of bed availability and ED hold without bed assignment showed a significant difference between the predicted value and the data collected in August 2020 in the evening data set. The significant difference between forecast and real events during the day can be explained by the unexpected variabilities of factors that can influence bed availability at the hospital. Allocation of resources, human and bed, is much easier to achieve during the day and, in turn, created too many possible variations to predict. The prediction exercise was then further scrutinized using machine learning classification for confirmation.
Machine learning classification is a form of data analysis used to build models describing the accuracy of classes the data represent [4]. Here, the study sought to examine how well the algorism predicts correctly when bed availability is positive or negative. Given the regression analysis output, the new task was to test if the regression analysis was compatible through machine learning classification. Using machine learning models to examine a proposed strategy or decision-making process through historical data is vital [5]. There are many analytics models available in machine learning to help management categorically predict the executability of a decision through accuracy values based on past experiences.
The datasets were uploaded into WEKA® machine learning software to test diagnostic decision-making accuracy from regression and forecasting results. Before classification of test data was performed, supervised learning using Support Vector Machine classification with 70% random split ratio was chosen to test the accuracy of model-classified instances. Accuracy of classified instances refers to the percentage of training data the algorism gets correct. The classification returned a 96.63% accuracy, resulting in confidence in the fitness of the model.
The classification tests of the datasets were established using the forecasted 30 value points and what actually happened in August 2020. Table 3 depicts the results from both morning and evening reports. Accuracy was in the 90th percentile in the morning and evening reports' predicted outputs. Factual (what really happened in August) outputs in the evening dataset were less fitted, with lower accuracy percentage (equal or less than 80%), which concurs with the results of the paired T-test ( Model performance in machine learning is estimated in terms of its accuracy in predicting the given or training data based on unknown or test data. An accuracy metric is used to measure the algorithm's performance and is calculated in the form of a percentage. It is the measure of how accurate the model's prediction is compared to the true data. Accuracy is used along with precision and recall, which are other metrics that use various ratios. These metrics provide insight into how the algorithm classifies data points based on prediction correctness.
Discussion
It is necessary to bear in mind the hospital is constantly trying to allocate resources during high census, which may distort the forecast in predictive models and other tests. In regression analysis, the coefficient of determination represents the mean change in the response for one unit of change in the predictor. Low Rsquare values are problematic when prediction needs to be precise. Here, the ED census alone is not enough to reflect bed availability at the hospital, and the additional support of using ED hold without bed assignment can better predict it.
It is predictively valid to forecast bed availability at the hospital with both ED census and ED hold without bed assignment as predictors. The limitation is obvious in applying evening ED capacity report data to predict bed availability, as these data were influenced by the effectiveness of stakeholders' allocating hospital resources during the day. Resource allocation is often carried out after morning clinical activities are over and can take place too late in the day to make the evening report useful. Thus, it is critical and meaningful for the nursing house supervisor to distribute ED capacity information to the medical staff in the early morning and alert stakeholders to provide beds and other resources effectively as early as possible during the day. ED census alone does not well reflect bed availability. It is the combination of two predictors, ED census and ED hold without bed assignment, that enable stakeholders to reflect the scarcity of resources with confidence.
Conclusions
Valuable administrative data in health care organizations is severely underutilized, and the lack of available research in health care operational data is supporting such claims. Data analytics are proven to be helpful in forecasting and decision making. There is much data collection in health care, and the content is not limited to clinical and evidence-based scientific research and learning. It also includes daily administrative and business data, which is mostly idle in database storage. Keeping health care business intelligence in silos limits the improvement of health delivery and health quality as well as cost reduction. The changing landscape of healthcare creates great demand for health data analytics. Data-driven business intelligence and analytics enhance healthcare performance, revenues, and patient experience. Today, technologies like predictive analytics and machine learning are readily available to transform health care business, strategy, and communications.
Additional Information Disclosures
Human subjects: All authors have confirmed that this study did not involve human participants or tissue. Animal subjects: All authors have confirmed that this study did not involve animal subjects or tissue.
Conflicts of interest:
In compliance with the ICMJE uniform disclosure form, all authors declare the following: Payment/services info: All authors have declared that no financial support was received from any organization for the submitted work. Financial relationships: All authors have declared that they have no financial relationships at present or within the previous three years with any organizations that might have an interest in the submitted work. Other relationships: All authors have declared that there are no other relationships or activities that could appear to have influenced the submitted work. | 3,204.6 | 2020-10-01T00:00:00.000 | [
"Business",
"Computer Science"
] |
Elliptic flow of electrons from heavy-flavour hadron decays at mid-rapidity in Pb-Pb collisions at $\mathbf{\sqrt{s_\mathrm{NN}}}$ = 2.76 TeV
The elliptic flow of electrons from heavy-flavour hadron decays at mid-rapidity ($|y|$ $<$ 0.7) is measured in Pb-Pb collisions at $\sqrt{s_{\rm NN}} = 2.76$ TeV with ALICE at the LHC. The particle azimuthal distribution with respect to the reaction plane can be parametrized with a Fourier expansion, where the second coefficient ($v_{\rm 2}$) represents the elliptic flow. The $v_{\rm 2}$ coefficient of inclusive electrons is measured in three centrality classes (0-10%, 10-20% and 20-40%) with the event plane and the scalar product methods in the transverse momentum ($p_{\rm T}$) intervals 0.5-13 GeV/$c$ and 0.5-8 GeV/$c$, respectively. After subtracting the background, mainly from photon conversions and Dalitz decays of neutral mesons, a positive $v_{\rm 2}$ of electrons from heavy-flavour hadron decays is observed in all centrality classes, with a maximum significance of $5.9\sigma$ in the interval $2<$ $p_{\rm T}$ $<$ 2.5 GeV/$c$ in semi-central collisions (20-40%). The value of $v_{\rm 2}$ decreases towards more central collisions at low and intermediate $p_{\rm T}$ (0.5 $<$ $p_{\rm T}$ $<$ 3 GeV/$c$). The $v_{\rm 2}$ of electrons from heavy-flavour hadron decays at mid-rapidity is found to be similar to the one of muons from heavy-flavour hadron decays at forward rapidity (2.5 $<$ $y$ $<$ 4). The results are described within uncertainties by model calculations including substantial elastic interactions of heavy quarks with an expanding strongly-interacting medium.
Introduction
The main goal of the ALICE [1] experiment is the study of strongly-interacting matter at the high energy density and temperature reached in ultra-relativistic heavy-ion collisions at the Large Hadron Collider (LHC). In these collisions the formation of a deconfined state of quarks and gluons, the Quark-Gluon Plasma (QGP), is predicted by Quantum ChromoDynamic (QCD) calculations on the lattice [2][3][4][5][6]. Because of their large masses, heavy quarks, i.e. charm (c) and beauty (b) quarks, are produced at the initial stage of the collision, almost exclusively in hard partonic scattering processes. Therefore, they interact with the medium in all phases of the system evolution, propagating through the hot and dense medium and losing energy via radiative [7,8] and collisional scattering [9][10][11] processes. Heavy-flavour hadrons and their decay products are thus effective probes to study the properties of the medium created in heavy-ion collisions.
Heavy-quark energy loss in strongly-interacting matter can be studied via the modification of the transverse momentum (p T ) spectra of heavy-flavour hadrons and their decay products in heavy-ion collisions with respect to the proton-proton yield scaled by the number of binary nucleon-nucleon collisions, quantified by the nuclear modification factor (R AA ). [13][14][15]. In addition a similar R AA for D 0 mesons was measured by STAR [12]. Similar values were measured by the ALICE Collaboration in central Pb-Pb collisions at the LHC for prompt D mesons at mid-rapidity and for muons from heavy-flavour hadron decays at forward rapidity [17][18][19]. The p T and centrality distributions of the D meson R AA are compatible, within uncertainties, with those of charged pions [18]. In addition, the modification of the p T spectra is studied separately for beauty and charm via the R AA of D mesons and non-prompt J/ψ from beauty hadron decays measured by the ALICE [18] and CMS Collaborations [21,22], respectively. A hint for a smaller suppression for beauty than for charm hadrons is observed at high p T in central Pb-Pb collisions, which is well reproduced by calculations including a mass dependence of the parton energy loss [23][24][25].
Further insight into the transport properties of the medium is provided by the measurement of the azimuthal anisotropy of heavy-flavour hadrons and heavy-flavour decay leptons with respect to the reaction plane, defined by the beam axis and the impact parameter of the nucleus-nucleus collision. In non-central collisions, the initial geometrical anisotropy in coordinate space of the nucleons participating in the collision is converted, by the interactions among the medium constituents, to a final anisotropy in momentum space of the produced particles. This effect can be characterized by the elliptic flow v 2 , which is the second order harmonic coefficient of the Fourier expansion of the particle azimuthal distribution [26]. At low p T the measured large v 2 of light-flavour hadrons [27][28][29][30] is considered as an evidence for the collective hydrodynamical expansion of the medium [31,32]. On general theoretical ground, the formation time of heavy quarks, shorter than 1/(2 m c,b ) where m is the mass of the quark (≈ 0.08 fm/c for charm), is expected to be smaller than the QGP thermalization time (≈0.6-1 fm/c [33]) with a very small annihilation rate [34]. The heavy-flavour elliptic flow measurements carry information about their degree of thermalization and participation to the collective expansion of the system. It is also relevant for the interpretation of recent results on J/ψ anisotropy [35], because the J/ψ mesons formed from charm quarks in a deconfined partonic phase are expected to inherit the azimuthal anisotropy of their constituent quarks [36,37]. At low and intermediate p T , the v 2 of heavy-flavour hadrons and their decay products is also expected to be sensitive to the heavy-quark hadronisation mechanism. Hadronisation via the recombination of heavy quarks with light quarks from the thermalized medium could further increase the elliptic flow of heavy-flavour hadrons and their decay products [38][39][40]. At high p T the v 2 measurements can constrain the path-length dependence of the in-medium parton energy loss, which is different for The ITS [53] detector consists of six cylindrical silicon layers surrounding the beam vacuum tube. The first two layers are positioned at 3.9 and 7.6 cm radial distance from the beam line. Dealing with the high particle density in this region requires an excellent position resolution, which is achieved with Silicon Pixel Detectors (SPD). The third and fourth layers are radially positioned at 15 and 23.9 cm and consist of Silicon Drift Detectors (SDD), while the two outermost layers are radially positioned at 38 and 43 cm and are made of Silicon Strip Detectors (SSD). The four SDD and SSD layers enable charged-particle identification via the measurement of their energy loss dE/dx with a resolution of about 10-15%.
The TPC [54] detector has a cylindrical shape with an inner radius of about 85 cm, an outer radius of about 250 cm, and a length of 500 cm. The TPC is the main tracking detector of the central barrel and is optimized to provide, together with the other central barrel detectors, charged-particle momentum measurement with excellent two-track separation and particle identification. For a particle traversing the TPC, up to 159 space points are recorded and used to estimate its specific energy loss. The resolution of the dE/dx measured in the TPC is approximately 6% for minimum-ionizing particles passing through the full detector.
At a radial distance of 3.7 m from the beam axis, the TOF detector [55] improves further the particle identification capability of ALICE. It provides a measurement of the time of flight for the particles from the interaction point up to the detector itself with an overall resolution of about 80 ps for pions and kaons at p T = 1 GeV/c in the Pb-Pb collision centrality intervals used in this analysis. The measured time-offlight of electrons is well separated from those of kaons and protons up to p T ≃ 2.5 GeV/c and p T ≃ 4 GeV/c, respectively. The V0 detectors [57] consist of two arrays of 32 scintillator tiles covering the pseudorapidity ranges 2.8 < η < 5.1 (V0A) and −3.7 < η < −1.7 (V0C), respectively. The two arrays are arranged in four rings each around the beam pipe. The V0 detectors are used to select beam-beam interactions online. For Pb-Pb collisions, the total signal amplitude is fitted with a model based on the Glauber approach, which is used to classify events according to their centrality classes [58], which correspond to percentiles of the hadronic cross section. For instance, the 0-10% centrality class corresponds to the 10% most central events. In addition, the azimuthal segmentation of the V0 detectors allows for an estimation of the reaction plane direction.
The ZDCs [59] are located on both sides of the interaction point at z ≈ ±114 m. Parasitic collisions of main bunches with satellite bunches are rejected on the basis of the timing information from the neutron ZDCs.
The results presented in this paper are based on a data sample of Pb-Pb collisions recorded with ALICE in November and December 2011 at √ s NN = 2.76 TeV. The events were collected with a minimum-bias interaction trigger using information of the coincidence of signals between V0A and V0C detectors. Central and semi-central Pb-Pb collisions were selected online by applying thresholds on the V0 signal amplitudes resulting in two separate trigger classes (central and semi-central triggers). In addition to the central and semi-central data samples, events selected by the EMCal trigger are analysed. The EMCal trigger required an EMCal cluster energy summed over a group of 4×4 cells, implemented as a sliding window, larger than an energy threshold. A centrality-dependent energy threshold was used, varying approximately from 7 GeV in the 0-10% centrality class to 2 GeV in the 80-90% centrality class. The EMCal trigger is in coincidence with the minimum-bias trigger. Detailed trigger information for the ALICE apparatus are reported in [52]. Table 1: Number of events and integrated luminosity for the different triggers (see text) and centrality classes considered in this analysis. The centrality classes are expressed as percentiles of the hadronic cross section [58].
Only events with a reconstructed interaction vertex (primary vertex), determined by extrapolating chargedparticle tracks to the beam line, with |z| < 10 cm from the nominal interaction point are used in the analysis in order to minimize edge effects at the limit of the central barrel acceptance. In addition, the z position of the primary vertex reconstructed using tracklets defined by hit pairs in the SPD is required to agree within 0.5 cm with the one of the primary vertex reconstructed with tracks. Since the v 2 measurements could be biased by multiplicity outliers, the centrality estimated with the V0 information is compared to that estimated using the number of reconstructed tracks in the TPC. Events with an absolute difference between the centrality estimated with the V0 detectors and the one estimated with the TPC detector larger than 5%, corresponding to events with pile-up from different bunch crossings, are rejected from the analysis. The event selection removed about 5% of the total number of events depending on the trigger and the centrality of Pb-Pb collisions. The number of events analysed after applying the event selection are listed in Table 1 for the different centrality classes and triggers together with the corresponding integrated luminosity. The EMCal trigger is not used in the 0-10% centrality class because of the high statistics achieved with the central trigger.
Data analysis
The elliptic flow of electrons from heavy-flavour hadron decays v e ± ←−HF 2 is obtained from the measurement of the inclusive electron elliptic flow v e ± 2 by subtracting the elliptic flow of electrons which do not originate from heavy-flavour hadron decays, v Bkg 2 . Exploiting the additive property of the particle azimuthal angle distribution with respect to the reaction plane, v e ± ←−HF 2 can be expressed as: where R SB is the ratio of the heavy-flavour decay electron yield to that of background electrons. In this paper, electrons from heavy-flavour hadron decays include electrons from quarkonium decays, whose contribution is however expected to be small as discussed in Section 3.4. In the following sections, the v e ± 2 and R SB measurements are presented, as well as the two procedures to determine v Bkg 2 .
Track selection and electron identification
Electron candidate tracks are required to fulfill the track selection criteria summarized in Table 2. Tracks are selected by requiring at least 100 associated space points in the TPC with at least 90 used for the dE/dx calculation and a value of the χ 2 /point of the momentum fit in the TPC smaller than 3.5. These selection criteria suppress the contribution from short tracks, which are unlikely to originate from the primary vertex. To further reduce the contamination from particles originating either from weak decays of light hadrons or from the interaction of other particles with the detector material, only tracks with a maximum value of the distance of closest approach (DCA) to the primary vertex in both the xy-plane (DCA xy < 2.4 cm) and the z direction (DCA z < 3.2 cm) are accepted. In addition, in order to minimize the contribution of electrons coming from γ conversions in the detector material at large radii, hits in both SPD layers are required for all selected tracks in the ITS-TPC-TOF analysis (p T < 3 GeV/c). Tracks are required to have at least three out of the four possible hits in the external layers of the ITS (SDD and SSD) in order to have at least three dE/dx measurements to be used for the Particle IDentification (PID). This guarantees a good particle identification based on the dE/dx in the ITS. Since the azimuthal coverage of the EMCal had a significant superposition with parts of the SPD detector that were not active during the data taking, this approach has to be modified for the TPC-EMCal analysis (p T > 3 GeV/c). In this case, at least one hit in any of the two SPD layers is required and the minimum number of associated ITS hits is reduced to 3. This results in a larger contribution of conversion electrons in the inclusive electron sample. The signal-to-background ratio is, as a consequence, smaller in the TPC-EMCal analysis than in the ITS-TOF-TPC analysis at the same p T .
p T range TPC dE/dx cut ITS dE/dx cut TOF compatibility E /p matching (GeV/c) with e hypothesis 0.5-1. Table 3: Summary of the electron identification criteria used in the analyses (see text for more details).
Electron identification is mainly based on the measurement of the specific energy loss in the TPC (dE/dx). The discriminant variable used, n TPC σ , is the deviation of this quantity from the parameterized electron Bethe-Bloch [60] expectation value, expressed in units of the dE/dx resolution [52]. This distribution is shown as a function of the track momentum in semi-central triggered events for the 20-40% centrality class in the upper left panel of Figure 1. In the low momentum region the kaon, proton and deuteron dE/dx bands cross that of electrons. In addition, the particle identification at high momentum is limited by the merging of the dE/dx bands of electrons, pions, muons and other hadrons, therefore the information of other detectors is mandatory to select a pure sample of electrons. Table 3 summarizes the PID cuts.
At low p T (0.5 < p T < 3 GeV/c), the measured time-of-flight in the TOF detector and the dE/dx in the ITS are used in addition to the TPC dE/dx to further reject hadrons. In the top right panel of Figure 1, the n TPC σ distribution is shown after requiring that the measured time-of-flight of the particle is compatible with the electron hypothesis within two sigmas, where sigma is the time-of-flight resolution (|n TOF σ | < 2). The kaon and proton contributions in the low momentum region are reduced but not completely removed due to wrongly associated hits in the TOF detector. This source of contamination is further suppressed using the dE/dx in the ITS. This selection is applied using the n ITS σ variable, defined in the same way as for the TPC. Electron candidates are selected with |n ITS σ | < 1 for 0.5 < p T <1.5 GeV/c and with |n ITS σ | < 2 for 1.5 < p T < 3 GeV/c, where the particles species are less separated in n ITS σ . In the lower panel of Figure 1, the n TPC σ distribution is shown after the additional electron identification criteria in the ITS are applied. A pure electron sample is obtained by selecting tracks with − 1 < n TPC σ < 3 and 0 < n TPC σ < 3 in the intervals 0.5 < p T < 1.5 GeV/c and 1.5 < p T < 3 GeV/c, respectively. In order to keep the contamination below 5%, the stronger requirement in the p T interval 1.5 < p T < 3 GeV/c is applied due to the merging of the pion and electron dE/dx bands in the TPC.
In the p T interval 3-13 GeV/c, the electron identification is based on the measurement of the TPC dE/dx and the E/p ratio, where E is the energy of the EMCal cluster matched to the prolongation of the track with momentum p reconstructed with the TPC and ITS detectors. Unlike for hadrons, the ratio E/p is around 1 for electrons, because they deposit most of their energy in the EMCal. In addition, the EMCal cluster shape is used to improve the purity of the electron sample, because the profile of the shower produced by electrons is more circular than the one produced by hadrons [61]. In the p T interval 8-13 GeV/c, the EMCal PID selection is applied in terms of n EMCal σ , which is defined as the deviation of the measured E/p from the expected E/p for electrons obtained from data and normalized by the width of the electron E/p distribution obtained with a fit Gaussian function. Electron candidates are selected with the identification criteria −1 < n TPC σ < 3 and −2 < n EMCal σ < 3 in the p T interval 8 < p T < 13 GeV/c.
The hadron contamination in the p T interval 0.5-3 GeV/c is estimated by fitting in momentum slices the TPC dE/dx distribution after the TOF-and ITS-PID selections with a convolution of Landau and exponential functions, similarly to what was done in [62]. For p T > 3 GeV/c, the hadron contamination is obtained from the E/p distribution of reconstructed tracks in momentum slices after applying only the TPC-PID selection. The estimated hadron contamination is lower than 5% up to p T = 8 GeV/c with negligible dependence on centrality, event plane and pseudorapidity and therefore it is not subtracted. The possible effect induced by this contamination is considered in the systematic uncertainties, as discussed in Section 3.3. For higher p T (8 < p T < 13 GeV/c), the contamination of hadrons is subtracted statistically from the electron sample in the n EMCal The rapidity ranges used in the ITS-TPC-TOF (p T < 3 GeV/c) and TPC-EMCal (p T > 3 GeV/c) analyses are restricted to |y| < 0.8 and |y| < 0.7, respectively, to avoid the edges of the detectors, where the systematic uncertainties related to particle identification increase. It was checked, by restricting the ITS-TPC-TOF analysis to |y| < 0.7, that the change in the results due to the different y range are not significant. In the following the notation |y| < 0.7 will be used.
Flow methods
The p T -differential azimuthal distribution of produced particles can be described by a Fourier expansion of the Lorentz invariant distribution of outgoing momenta [26]: where E, p and ϕ are respectively the energy, momentum and azimuthal angle of the particle, and Ψ n the angle of the initial state spatial plane of symmetry of the n-th harmonic defined by the geometrical distribution of the nucleons participating in the collision. In order to determine the second harmonic coefficient v 2 , the following #» Q 2 vector is measured from the azimuthal distribution of charged particles (so called ReFerence Particles RFP): where ϕ i are the azimuthal angles and N the multiplicity of the RFP [63]. The weights w i are described later in the text. The azimuthal angle of the #» Q 2 vector is denoted by event plane angle and is an estimate of the second harmonic symmetry plane angle Ψ 2 [26].
The event plane (EP) and scalar product (SP) methods are used to measure the elliptic flow of inclusive electrons. The two methods are described in detail in the second part of this section. Both methods use the #» Q 2 vector, which is determined with the signal amplitudes in the V0 detectors at forward and backward rapidity for the EP method and with the reconstructed tracks in the TPC at mid-rapidity for the SP method. In the first case, the sum in Eq. 3 is running over the eight azimuthal sectors of each V0 detector and ϕ i is defined by the central azimuth of the i-th sector. The weights w i are equal to the signal amplitude in the i-th sector for the selected event, which is proportional to the number of charged particles crossing the sector. Non-uniformities in the V0 acceptance and efficiency are corrected for using the procedure described in [64]. Despite these corrections, a residual modulation of up to 4% is observed in the distribution dN evt /dψ 2 in central collisions. The effect is corrected for using additional event weights in order to make the ψ 2 distribution flat. The weights are obtained dividing the average expected number of events per each interval of the event plane distribution by the observed number of events in a given event plane interval. In the TPC case the weights w i described in [48] are used to correct for non-uniformities in the acceptance and efficiency of the TPC. In the second case, the sum in Eq. 3 is running over tracks reconstructed in the TPC and selected with the following criteria: at least 70 associated space points in the TPC out of the maximum of 159, a χ 2 per TPC point of the momentum fit in the range 0.2 < χ 2 /point < 4 and a transverse momentum value in the interval 0.2 < p T < 5 GeV/c. Additionally, tracks are rejected if their distance of closest approach to the primary vertex is larger than 3.2 cm in the z direction and 2.4 cm in the (x,y) plane. In order to minimize the non-uniformities in the azimuthal acceptance, no requirement is applied on the number of ITS hits associated to tracks. In the case of the scalar product method, unit track weights w i are used in the construction of the #» Q 2 vector, and possible non-uniformities in the detector are corrected with the non-uniform acceptance correction described in [65].
Following [63], the electron elliptic flow can be measured with the event plane method using the following equation: where the brackets in the numerator indicate the average over electrons with azimuthal angle ϕ at midrapidity in all the events. The factor R 2 is the event plane resolution correction, a quantity smaller than unity that depends on the multiplicity and v 2 of the RFP. The resolution of the event plane determined with the V0 detectors is measured with the three sub-event method [48], namely the signals in the V0 detectors (both A and C sides) and the tracks in the positive (0 < η < 0.8) and negative (−0.8 < η < 0) pseudorapidity regions of the TPC. The average R 2 values in the three centrality classes used in this analysis are about 0.57 (0-10%), 0.77 (10-20%) and 0.78 (20-40%). At high p T (8 < p T < 13 GeV/c), the hadron contamination needs to be subtracted from the inclusive electron sample. In this case the v 2 of inclusive electrons is extracted from the number of electrons, N in and N out , in two 90 • -wide intervals of ∆ϕ = ϕ − ψ 2 : in-plane (− π 4 < ∆ϕ < π 4 and 3π 4 < ∆ϕ < 5π 4 ) and out-of-plane ( π 4 < ∆ϕ < 3π 4 and 5π 4 < ∆ϕ < 7π 4 ), respectively, after statistical subtraction of the hadron contamination in each of the ∆ϕ interval. In this case, v 2 {EP} is given by: The yield of electron candidates that do not originate from heavy-flavour hadron decays, which can be reconstructed only statistically, is measured in p T and ∆ϕ intervals in order to measure the elliptic flow of background electrons. The dN/d∆ϕ distributions of background electrons are then fitted in each p T interval with the following function: where N 0 and v Bkg 2 are the fit parameters. The effect of higher harmonics on v 2 estimated with Eq. 6 and 7 is assumed to be negligible.
The measurement of the elliptic flow with the scalar product method [66,67], a two particle correlation technique, is given by: where M A and M B are the multiplicities and #» Q A 2 and #» Q B 2 are the #» Q 2 vectors of two sub-events A and B, determined from TPC tracks in the positive (0 < η < 0.8) and negative (−0.8 < η < 0) pseudorapidity regions, respectively. The brackets in the numerators indicate the average over electrons with unit vector of the momentum at the primary vertex projected on the transverse plane #» u A 2 ( #» u B 2 ) in the sub-event A (sub-event B). The sub-event procedure is applied in order to avoid auto-correlations between the electron candidates and the #» Q 2 vectors, and in order to suppress non-flow contributions, like resonance decays and particles produced within jets.
The elliptic flow measurements carried out with the event plane method could lead to ambiguous results lying between the event-averaged mean v 2 value and the root-mean-square value, as a consequence of the presence of event-by-event flow fluctuations [67]. Those ambiguities are resolved using the scalar product method, that always yields to the root-mean-square value.
Inclusive electron elliptic flow and systematic uncertainties
The measured elliptic flow of inclusive electrons is shown in Figure 3 in the centrality classes 0-10%, 10-20% and 20-40% as a function of p T using the event plane (black markers) and the scalar product (red markers) methods. The full markers represent the results obtained with the central and semi-central triggers, while in the 10-20% and 20-40% centrality classes those obtained with the EMCal trigger are reported with open markers. The EP and SP methods give consistent results in the full p T region and no effects due to possible ambiguities in the EP with respect to the SP method [67] are seen in this analysis. However for p T > 3 GeV/c the v 2 values measured with the EP tend to be lower than those measured with the SP. This indicates a possible stronger suppression of the non-flow effects like jet and resonance contributions with the EP method, for which the η gap between the electron candidates and the V0 In the case of the EP method, two systematic uncertainty sources can affect the event plane resolution correction factor R 2 . The first source arises from the presence of non-flow correlations between the two TPC sub-events used to calculate the resolution. A wider pseudorapidity gap (|∆η| > 0.4) is used in the systematic studies. A maximum difference of 2% was observed in most central collisions, while in the more peripheral ones the difference was observed to be smaller than 1%. The second contribution is due to the variation of R 2 within the centrality classes used for the analysis. The inclusive electron yield is assumed to be flat within a centrality class when computing R 2 . The resulting systematic uncertainty is estimated by recomputing the R 2 value for each centrality class as weighted average of the values in finer centrality intervals (of 5 percentiles) with weights given by the corresponding electron yields. Since R 2 strongly depends on the centrality, in the most central collisions the systematic uncertainty is found to be larger (2.7% in the 0-10% centrality class) than in the more peripheral ones (1%).
For both methods (EP and SP), the systematic uncertainty due to the hadron contamination in the electron sample is estimated for p T < 8 GeV/c by comparing the inclusive electron v 2 results with the ones obtained after statistically subtracting the hadron contribution. The resulting uncertainty is found to be of the order of 1% at low p T , increasing up to 5% at p T = 8 GeV/c.
In order to study the stability of the measurements as a function of the applied selection criteria, the track selection and PID cuts are systematically varied around the value chosen in the analysis. The standard deviation of the v 2 value distribution obtained with different selection criteria in each p T interval is taken as systematic uncertainty. This contribution is small (2%) at low p T (p T < 3 GeV/c), whereas it becomes the dominant source of uncertainty at high p T , reaching an average of 35% over p T and centrality class for p T > 8 GeV/c dominated by the PID cut variation.
The events selected with the EMCal trigger could have a bias in the event plane direction induced by the triggering in the limited azimuthal coverage of the EMCal detector. According to a trigger simulation study, the effect on the elliptic flow measurement is expected to be larger for particles that do not generate a trigger signal in the detector, like hadrons, than for the particles which triggered the event (electrons, photons). The systematic uncertainty is estimated as the difference between the v 2 of charged particles in full azimuth measured in the semi-central triggered events and the v 2 of charged particles in the EMCal azimuthal coverage and triggered by the EMCal detector. The systematic uncertainty increases with p T and it is found to be of the order of 20% in the 10-20% centrality class and less than 5% in the 20-40% centrality class. The various systematic uncertainties are finally added in quadrature.
Correction for background electrons
The raw inclusive electron candidate sample consists of three main components: 1. electrons from heavy-flavour hadron decays and dielectron decays of quarkonia (e.g. J/ψ, ϒ); 2. photonic background electrons from Dalitz decays of light neutral mesons and the conversion of their decay photons in the detector material, as well as from virtual and real thermal photons from hard scattering processes, the latter converting in the material of the detector; 3. background electrons from weak K 0 → e ± π ∓ ν e (K e3 ) decays, and dielectron decays of light vector mesons.
In this analysis, electrons from quarkonium decays are included in the definition of heavy-flavour decay electrons. The only relevant contribution arises from J/ψ decays, which amounts to about 5.5% in the p T interval 3-4 GeV/c in central collisions and decreases towards higher p T . It was estimated by using an interpolation at √ s = 2.76 TeV of the p T -differential cross section measured in pp collisions at various centre of mass energies [68] and scaling with the measured nuclear modification factor [69,70].
In order to obtain the elliptic flow of heavy-flavour decay electrons, the background contributions are subtracted from the inclusive electron v 2 . The background electron yield is dominated by the contribution of photonic electrons. The background from electrons from non-photonic sources, namely weak K 0 → e ± π ∓ ν e (K e3 ) decays, and dielectron decays of light vector mesons, is indeed negligible as discussed in Section 3.4.2. Two strategies are adopted for the electron background v Bkg 2 subtraction depending on p T : the invariant mass method [46] (Section 3.4.1) is used at low p T (p T < 1.5 GeV/c), while a cocktail method [71] (Section 3.4.2) is used for p T > 1.5 GeV/c, because of the lower yield of background electrons.
Invariant mass method
Electrons from direct γ decays, γ-conversions and Dalitz-decays of π 0 and η mesons are always produced in electron-positron pairs with a small invariant mass (m e + e − ) following a Kroll-Wada distribution [72] peaked at zero. Such correlation does not hold for heavy-flavour decay electrons. This property is used in the invariant mass method to measure the photonic electron backgrounds. The fraction of Dalitz decays of higher mass mesons (ω, η ′ , φ ), estimated with the cocktail method, is found to be negligible. Photonic electrons are reconstructed statistically by pairing an electron(positron) track with opposite charge tracks identified as positrons(electrons), called associated electrons in the following, from the same event selected with the requirements listed in Table 4. The pair invariant mass distribution is computed in each p T and ∆ϕ interval of the inclusive electron tracks. The combinatorial background is subtracted using the like-sign invariant mass distribution in the same interval. A summary of the selection criteria applied on the electron-positron pairs is presented in Table 4.
Due to detector acceptance and inefficiencies, not all photonic electrons of the inclusive electron sample are identified with this method. Therefore, the raw yield of reconstructed photonic electrons is corrected for the efficiency to find the associated electron(positron) with the selection criteria described above. This efficiency is estimated with Monte Carlo simulations. A sample of Pb-Pb collisions with enhanced π 0 and η yields was generated with HIJING v1.36 [73]. The transport of particles in the detector is simulated with GEANT3 [74]. The simulated π 0 and η p T distributions are weighted so as to Associated electron cuts p T assoc (GeV/c) > 0.15 for 0.5 < p T < 3 GeV/c > 0.3 for 3 < p T < 8 GeV/c > 0.5 for 8 < p T < 13 GeV/c |y assoc | < 0. match the measured π 0 and π ± p T spectra [75,76] and the corresponding η p T spectra assuming m Tscaling [77,78], respectively. The photonic electron reconstruction efficiency increases with the p T of the electron, reaching a value of about 60% at high p T . The inclusive-to-background ratio (1 + R SB ) is calculated by dividing the inclusive electron yield by the yield of photonic electrons corrected for the efficiency to find the associated electron. (see Eq. 1) at low p T (p T < 1.5 GeV/c) is performed with a fit to the dN/d∆ϕ distributions of photonic electrons reconstructed with the invariant mass method in each p T interval (see Eq. 7). At higher p T (p T > 1.5 GeV/c), the electron yield becomes too small to perform a p T and ∆ϕdifferential measurement of the photonic electrons. Figure 7 shows the v 2 of photonic electrons measured with the invariant mass method (full markers) as a function of p T in the centrality classes 0-10%, 10-20% and 20-40%.
The systematic uncertainties of both the inclusive-to-background ratio and v Bkg 2 are estimated by varying the selection criteria listed in Table 4. For p T > 8 GeV/c the TPC and EMCal PID requirements for the inclusive electron candidates are also varied in order to take into account possible systematic uncertainties from the estimation of the hadron contamination. In addition, for the inclusive-to-background ratio the small dependence of the photonic electron reconstruction efficiency on the p T spectra of the background sources is taken into account by calculating the efficiency for different π 0 and η p T spectra. The dependence of the centrality on the systematic uncertainty of the inclusive-to-background ratio is found to be negligible. The contributions to the inclusive-to-background ratio systematic uncertainty are summarized in Table 5: the final overall systematic uncertainty is obtained summing in quadrature the different contributions. For v Bkg 2 , the systematic uncertainty of the event plane correction factor R 2 is estimated using the same procedure as for the inclusive electron v 2 and is found to be the same. Moreover, the difference between the v Bkg 10% 5% for the electron-positron pair Influence of the p T spectra 5% 10% 5% 3% of photonic sources Hadron contamination in the inclusive electron sample ---3% Table 5: Systematic uncertainties of the inclusive-to-background ratio (1 + R SB ). The centrality dependence of these systematics is found to be negligible. (see text for more details).
Cocktail method
The v Bkg 2 was also estimated using the cocktail method. A cocktail of electron spectra from background sources is calculated using a Monte Carlo event generator of hadron decays. This method requires that the momentum and elliptic flow distributions of the relevant background sources are well known.
The following electron background sources are included in the cocktail simulation: -Dalitz decays of π 0 , η, ω, η ′ , φ -Dielectron decays of η, ρ 0 , ω, η ′ , φ -Conversions of decay photons from π 0 , η, ρ 0 , ω, η ′ -Real and virtual conversion of prompt and thermal photons The contribution from dielectron decays of light vector mesons is small (below 5% of the total background electrons considered above). For the consistency with the invariant mass method, the contributions from K e3 and quarkonia (e.g. J/ψ and ϒ) decays to the inclusive electron spectrum are not included in the background cocktail. The K e3 and ϒ contributions are not expected to be relevant in the p T range of the analysis. In pp collisions at √ s = 7 TeV and √ s = 2.76 TeV, the relative contribution from K e3 decays to the electron background was observed to decrease with p T , from a maximum of 0.5% at p T = 0.5 GeV/c for the same track requirement in the first pixel layer [62]. It is expected to stay below 1% in Pb-Pb collisions in the p T range considered after taking into account the different R AA of the π 0 [75] and K ± [76].
Neutral pions play an important role in the cocktail. The p T and v 2 distributions of all light scalar and vector mesons included in the cocktail are deduced from the π 0 spectra assuming m T [77,78] and KE T [28,[79][80][81] scaling, respectively. Indeed, electrons from π 0 decays are the most important background source, except in the 0-10% and 10-20% centrality classes for high electron p T (p T > 8 GeV/c and p T > 10 GeV/c, respectively), where contribution from direct photons starts to dominate. The contribution of π 0 decays to the electron background is twofold: via the Dalitz decay π 0 → e + e − γ and via conversions in the detector material of photons from the decay π 0 → γγ. In principle, the π 0 p T and v 2 distributions used in the Monte Carlo event generator should be based on measured π 0 spectra [75] and v 2 . However, because of the higher statistical precision of the combined charged pion p T spectra [76] and the fact that neutral-pion and charged-pion p T spectra are found to be consistent, the average of the measured charged-pion p T spectra, (π + + π − )/2, is used as input for the cocktail calculations. The upper-left panel of Figure 5 shows the comparison of the neutral and chargeaveraged yields of pions in the centrality class 10-20% together with a fit to the π ± data with a modified Hagedorn function [83]. The p T spectra are extrapolated up to 25 GeV/c using the fit function. In the last p T interval of the measured inclusive electron spectra (10 < p T < 13 GeV/c), about 10% of electrons from Dalitz π 0 decays are expected to come from a π 0 with a p T larger than 25 GeV/c. At such high p T , due to the similar v 2 of all particle species at high p T , this contribution is found to be negligible. The systematic uncertainty on the heavy-flavour decay electron v 2 arising from the background sources is estimated to be smaller than 6% in the last two p T intervals 8-10 and 10-13 GeV/c. The bottom-left panel of Figure 5 shows the ratio of the π ± data, as well as π 0 data, to the fit function. The former is consistent with unity within 5% over the full p T range, whereas the latter is considered in the v Bkg The p T -dependent π ± elliptic flow [28,45,82] is used as input for the cocktail calculations. The upperright panel of Figure 5 shows the v 2 of charged pions measured in the 10-20% centrality class together with the fit function that is used in the cocktail simulations. The ratio of the data to the fit function is presented in the bottom-right panel. The function used to fit the v 2 of charged pions is an empirical function made by the convolution of trigonometric and error functions. Measurements performed with the scalar product [28] and event plane [45,82] methods have been used at low-intermediate p T (p T < 6 GeV/c) and higher p T (3 < p T < 16 GeV/c), respectively. The scalar product and event plane methods give compatible results within the uncertainties in the common p T range 3 < p T < 6 GeV/c. The v 2 values are extrapolated from p T = 16 GeV/c up to p T = 25 GeV/c. The elliptic flow of electrons from π 0 Dalitz decays is estimated from that of π 0 mesons using the PYTHIA 6 [84] event generator to simulate the Dalitz decay. The parameterized v 2 of π 0 and the one of their decay electrons are shown in Figure 6 as a function of p T .
The treatment of electrons from photon conversions in the detector material uses the GEANT4 functionality of pair production [85]. It has been implemented in the cocktail by forcing all decay photons to produce an e + e − pair immediately after their creation without propagating them through the ALICE apparatus. The contribution of electrons from photon conversions is scaled according to the radiation length of the crossed material. At low p T (p T < 3 GeV/c), electron tracks are required to be associated with two hits in the SPD. The effective converter thickness is estimated to be x/X 0 = (0.77 ± 0.07)%, including the beam pipe, air and part of the innermost pixel layer at y = 0 [62]. The indicated radiation thickness is averaged over the pseudorapidity range of the analysis. At higher p T (p T > 3 GeV/c), tracks with one hit in the SPD are also used. Therefore, the material of the second pixel layer is also taken into account, leading to an effective converter thickness of x/X 0 = (2.15 ± 0.11)% [62]. The results of the cocktail for photon conversion were found to be consistent within uncertainties with a full simulation test where the generated particles were propagated through the ALICE apparatus using GEANT3 [86]. The elliptic flow of electrons from the conversion of π 0 decay photons is found to be comparable to the one of electrons from π 0 Dalitz decays.
The contributions of direct photons, thermal photons from the hot partonic and hadronic phase and photons that could be produced in the interactions of hard scattered partons with the medium, are included in the cocktail of background electrons. These sources can give both electrons from photon conversion in the detector material and electrons from virtual photons. The production of real prompt photons was measured at mid-rapidity in Pb-Pb collisions in the p T interval 0.9-14 GeV/c [87]. The spectra are fitted and extrapolated towards lower and higher p T (0.5 < p T < 25 GeV/c). At intermediate-high p T (p T > 5 GeV/c), the p T spectrum of real prompt photons has been calculated with next-to-leadingorder perturbative QCD calculations for pp collisions at 2.76 TeV [88,89] and scaled to fit the ALICE measurements in Pb-Pb collisions [87]. This assumes that the other contributions are negligible in this p T range and that the shape of the p T spectra of real prompt photons is not modified in heavy-ion collisions, which is justified by the experimental results. At low p T , the dominant contribution of thermal photons in the measured real direct photon p T spectra was taken into account by adding an exponential term to the fit function. The p T spectra of virtual photons are obtained using the Kroll-Wada function [72]. The elliptic flow of real direct photons was measured in the centrality class 0-40% [90]. To estimate the elliptic flow in the smaller centrality classes 0-10%, 10-20% and 20-40%, the measurement is scaled by the ratio of the measured charged pion v 2 in the 0-40% centrality class. Finally, the elliptic flow of virtual photons is assumed to be identical to the one of real photons.
The elliptic flow of background electrons is estimated by summing the various background electron sources according to their relative contribution to the total background. The main background contributions are due to π 0 and prompt photons. In addition, the contributions of thermal photons (at low p T in the 0-10% and 10-20% most central Pb-Pb collisions) and η are also relevant. The total systematic uncertainty of v Bkg 2 estimated with the cocktail method is obtained by adding in quadrature the contributions from several sources, namely: -the statistical and systematic uncertainties of the v 2 and p T measurements of π ± and direct photons, -the quality of the fits and extrapolations of the π ± and direct photon spectra, -the systematic uncertainties on the KE T and m T scaling used to estimate the v 2 and p T distributions of higher mass mesons, respectively, -the approximation of the π 0 p T and v 2 distributions by the corresponding π ± spectra.
The first one leads to the largest systematic uncertainty. It is evaluated by parameterizing the data along the upper and lower ends of their statistical and systematic uncertainties added in quadrature and generating again the complete cocktail of electron spectra based on these new parameterizations. The right panel of Figure 5 shows examples of such fits for the p T dependence of the π ± v 2 in the centrality class 10-20%. The uncertainties of the measured p T spectra have a smaller influence on the resulting v Bkg 2 than those of the measured v 2 spectra. The uncertainty on the KE T scaling assumption is estimated by comparing the kaon v 2 obtained by KE T scaling to the measured one [28]. The resulting systematic uncertainty is 8% for 0-10%, 6% for 10-20% and 4% for 20-40%. These numbers are consistent with those reported in [28]. Because of their similar mass, it is expected that the elliptic flow of η and the one of K are similar and thus these numbers are taken directly for the η KE T scaling uncertainty. For the other heavier mesons the KE T scaling does not hold precisely [28,81]; however, these other particles have an extremely low weight in the cocktail, and thus these uncertainties are neglected. The m T -scaling approach ensures that, at high p T , the transverse-momentum distributions are the same for all meson species. The normalization of the heavier meson spectra relative to the pion spectrum was determined by the ratios of heavier meson yields to neutral pion yields at high p T (p T > 5 GeV/c). The values together with their uncertainties used in the analysis are taken from [78]. At low p T (p T < 3-4 GeV/c) some deviations from the m T -scaling approach are expected due to in-medium effects like radial flow. The m T -scaling based cocktail is found to be in agreement within statistical uncertainties with a cocktail based on the η/π 0 -ratio measured in pp collisions at √ s = 7 TeV [91]. Also, due to the similarity of the elliptic flow of decay electrons and conversion electrons originating from the dominating mother mesons (π 0 and η), the material budget uncertainty was found to have no significant effect.
Two additional sources of systematic uncertainty related to the electron track reconstruction were studied. First, reconstructed electron candidates have a limited p T resolution. In particular, Bremsstrahlung in the detector material shifts their reconstructed p T towards lower values. Secondly, hits in the SPD can be wrongly associated to a track with a probability increasing with decreasing p T . This leads to an increase of the amount of electrons from photon conversions occurring beyond the SPD layers in the inclusive electron sample and a degradation of the p T and ϕ resolutions of tracks used in the analysis. The resulting effects on v Bkg 2 were evaluated with the cocktail method using SPD hit mismatch probabilities and resolution maps obtained with a full simulation of the ALICE apparatus. No significant change of v Bkg 2 was observed .
The v Bkg 2 estimated with the cocktail method is shown as a function of p T (0.5 < p T < 13 GeV/c) in the centrality classes 0-10%, 10-20% and 20-40% in Figure 7, together with the one obtained with the invariant mass method (0.5 < p T < 1.5 GeV/c). The results are consistent within the systematic uncertainties in the three centrality classes.
Results
The elliptic flow of heavy-flavour decay electrons v e ± ←−HF 2 is computed using Eq. 1. The systematic uncertainties on v e ± 2 , R SB and v Bkg 2 are propagated to v e ± ←−HF 2 . The error propagation for the background subtraction is based on an approximation of a second order error propagation [92,93], where differently from the Gaussian approximation, not only linear effects of the error propagation are considered but also quadratic effects. This is necessary especially in case the non-linearity of the subtraction can not be neglected anymore. The basic concept is that the upper and lower systematic errors are both found by independently varying the uncertainties of the input variables by one sigma up and down. The value of v e ± ←−HF 2 is obtained only with the event plane method, because the charged-pion v 2 measurements with the scalar product method are not available at high p T for the estimation of v Figure 9 shows the centrality dependence of the elliptic flow of heavy-flavour decay electrons in two p T intervals (1.25-1.5 GeV/c and 2.5-3 GeV/c). In the interval 1.25 < p T < 1.5 GeV/c the contribution from charm hadron decays is expected to be dominant in the heavy-flavour decay electron sample, whereas in the higher p T interval the beauty-hadron decays should start to be relevant. In pp collisions at √ s = 2.76 TeV, beauty hadron decays are indeed the dominant source of heavy-flavour decay electrons for p T > 4.5 GeV/c [94]. A decreasing trend of v e ± ←−HF 2 towards central collisions is observed. This is consistent with a final-state anisotropy in momentum space driven by the initial geometrical anisotropy of the nucleons participating in the collision, which increases towards peripheral collisions. This result indicates that the interactions with the medium constituents transfer to heavy quarks, mainly charm, information on the azimuthal anisotropy of the system, possibly suggesting that charm quarks participate in the collective expansion of the system.
The elliptic flow of prompt D mesons was measured at mid-rapidity in the centrality classes 0-10%, 10-30% and 30-50% for p T > 2 GeV/c [47,48]. The results are similar to those of heavy-flavour decay electrons after taking into account the decay kinematics, which shifts their maximum value of v 2 to lower p T with respect to their parent D mesons. At forward rapidity (2.5 < y < 4), the elliptic flow of heavy-flavour decay muons v µ ± ←−HF 2 was measured with various methods in the centrality classes 0-10%, 10-20% and 20-40% [49]. Figure 10 shows the comparison of v e ± ←−HF 2 at mid-rapidity and v µ ± ←−HF 2 at foward rapidity obtained with the two-particle Q-cumulant method with |∆η| > 1.7. The observed v 2 of heavy-flavour decay leptons is similar at mid-and forward rapidity. Figure 11 shows the comparison of the measured heavy-flavour decay electron elliptic flow in the 20-40% centrality class with theoretical model calculations. BAMPS [95,96] is a partonic transport model based on the Boltzmann approach to multi-parton scatterings. Two versions are presented. In the first one, BAMPS el. [95], heavy quarks interact with the medium via collisional (elastic) processes computed with running strong coupling constant. The binary cross section is scaled with a correction factor in order to mimic the contribution of radiative processes, which are not included. The heavy-flavour decay electron elliptic flow and nuclear modification factor measured at RHIC are used to tune this factor. In the second version, BAMPS el. + rad. [96], radiative processes are included as well. In both approaches, the hadronisation uses a vacuum fragmentation function. TAMU [97] is a heavy-flavour transport model that incorporates energy loss via collisional processes with resonance formation and dissociation in an evolving hydrodynamic medium. The hydrodynamical expansion of the medium is constrained by the measured p T and v 2 spectra of light-flavour hadrons. The hadronisation contains a component of recombination of heavy quarks with light-flavour quarks from the QGP. Diffusion processes in the hadronic phase are also included. POWLANG [98] is a transport model based on the Langevin transport equation with collisional energy loss in an expanding, deconfined medium. Hadronisation uses a vacuum fragmentation function. A more recent version of POWLANG [99] uses an in-medium hadronisation resulting in a larger v 2 for the D meson. MC@sHQ+EPOS [100] is a perturbative QCD model which includes radiative (with Landau-Pomeranchuk-Migdal correction [101]) and collisional energy loss in an expanding medium. A component of recombination of heavy quarks with light-flavour quarks from the QGP is also incorporated in the model. The medium fluid dynamical expansion is based on the EPOS model [102]. The elliptic flow of heavy-flavour decay electrons is qualitatively described by the models including significant interactions of heavy quarks with a hydrodynamically-expanding QGP. Mechanisms like collisional processes and hadronisation via recombination transfer to heavy quarks and heavy-flavour hadrons the elliptic flow induced during the system expansion, and are able to describe the measured positive v e ± ←−HF 2 at intermediate p T . The p T dependence of v 2 reflects the interplay between significant scatterings with the constituents of an expanding medium at low and intermediate p T , and the path-length dependence of the parton energy loss in the hot and dense matter at high p T . Models which underestimate the elliptic flow of heavy-flavour decay electrons at low and intermediate p T (POWLANG and BAMPS el. + rad) underestimate as well the elliptic flow of prompt D mesons at mid-rapidity [48,103]. Similarly BAMPS el. which reproduces qualitatively the elliptic flow of heavy-flavour decay electrons, describes at mid-rapidity the prompt D meson v 2 [48] and at forward rapidity the heavy-flavour decay muon v 2 [49].
Conclusions
We presented the elliptic flow of electrons from heavy-flavour hadron decays at mid-rapidity (|y| < 0.7) in central and semi-central Pb-Pb collisions at √ s NN = 2.76 TeV measured with ALICE at the LHC. The results are presented as a function of the transverse momentum in the interval 0.5 < p T < 13 GeV/c in three centrality classes (0-10%, 10-20%, and 20-40%). The p T dependence of the heavy-flavour decay electron v 2 shows a positive v 2 at low and intermediate p T in all centrality classes with a significance of 5.9σ in the p T range 2 < p T < 2.5 GeV/c in semi-central (20-40%) collisions. This result indicates that the interactions with the medium constituents transfer to heavy quarks, mainly charm, information on the azimuthal anisotropy of the system, possibly suggesting that charm quarks participate in the collective expansion of the system. At higher p T (p T > 4 GeV/c) the measured v 2 is consistent with zero within large uncertainties. The centrality dependence of the heavy-flavour decay electron elliptic flow was studied in two p T intervals (1.25-1.5 GeV/c and 2.5-3 GeV/c). At low p T the contribution from charm hadron decays is expected to be dominant, whereas it decreases at higher p T . A decrease of v 2 of electrons from heavy-flavour hadron decays towards more central collisions is observed in particular at low transverse momentum (1.25 < p T < 1.5 GeV/c). Such a trend is expected from the increase of the initial spatial anisotropy from central to peripheral collisions. The elliptic flow of heavy-flavour decay electrons at mid-rapidity (|y| < 0.7) is found to be similar to the one of heavy-flavour decay muons at forward rapidity (2.5 < y < 4). The elliptic flow of electrons from heavy-flavour hadron decays is compared to theoretical model calculations. The anisotropy is best described by models that include significant interactions of heavy quarks with the medium and mechanisms, like collisional energy loss and hadronisation via recombination, that transfer to heavy quarks and heavy-flavour hadrons the elliptic flow produced during the system expansion. [26] S. Voloshin and Y. Zhang, "Flow study in relativistic nuclear collisions by Fourier expansion of Azimuthal particle distributions," Z.Phys. C70 (1996) | 13,403.6 | 2016-05-20T00:00:00.000 | [
"Physics"
] |
Mechanical properties of structures produced by 3D printing from composite materials
By 3D printing it is possible to create different structures with different fiber-laying directions. These structures can be created depending on the type of 3D printer and its software. The Mark Two printer allows printing Onyx, a material based on nylon in combination with microcarbon fibers. Onyx can be used alone or reinforced with kevlar, glass or carbon fibers. This article deals with 3D printing and evaluation of mechanical properties of printed samples.
Introduction
Modern 3D printers are currently able to print components from composite materials and create composite materials. Composite material consists of at least two materials having different properties. It is an artificially created heterogeneous material. One component is a reinforcement which is usually rigid (its role is to deliver the composite resistance to external load forces) and the second component is a jointing material (matrix) that can be metal, ceramic or polymer. The matrix must absorb the reinforcement phase; it is continuous and usually less rigid. The matrix protects the reinforcement, keeps it in the desired position and transfers loading to the fibers. By integrating materials with different properties into one unit, a material with improved properties called a composite material is created [1].
Characteristic properties of most composite materials are lower weight, high strength, stiffness, toughness and high fatigue strength. Some composites may have better corrosion resistance, refractoriness and heat resistance, heat insulating properties, chemical resistance, lower thermal expansion, less deformation, and other properties over traditional homogeneous materials. Composite materials can thus be defined as an useful and effective material that is made by the macroscopic combination of the two components -the reinforcement and the matrix so that the components do not dissolve or incompatible with one another and retain their individual properties but act together for better technical properties [2]. The weakness of composite materials is their higher price and worse recyclability. Some composite materials have different mechanical properties in different directions (anisotropy) and aging at raising humidity and temperature [1,3].
Production of composite materials
Composites and components made of composite materials can be manufactured using multiple technologies. The choice of technology depends on the shape of the component being manufactured, the requirements for its mechanical properties, the structure and surface quality, the cost of manufacturing the product and the required productivity [4]. Methods for producing composite materials are [5,6,7]: -applying the liquid matrix to the surface of the fibers, -powder metallurgy (cold pressing and subsequent sintering), -vacuum or pressure impregnation of the reinforcement by the liquid matrix, -infiltration of the fibers with a liquid matrix from the bottom side, from the top side and combined (pouring, filling or immersion of the reinforcement), -wetting of the reinforcement in the matrix and its subsequent shaping, -hot pressing (the matrix melts during hot pressing and the reinforcement is distributed in its volume), -hot rolling (during continuous lamination by inserting a reinforcement placed between the sheets of the matrix), -spraying a matrix with discontinuous reinforcement, -gas phase infiltration (foam composite materials), -infiltration of liquid reinforcement (coating of porous materials), -electrolytic metal deposition. One of the most recent methods of producing composite materials is nowadays manufacturing through 3D printing.
3D printing technologies
The 3D digital model must exist at the beginning of each 3D print process. This model can be created in various 3D programs. The model is "sliced" on individual layers in these programs and it is thus ready to be sent to the 3D printer reader. The printer applies the material to individual layers depending on the shape of the model and the printing process. There are several different 3D printing technologies that use different materials and a way to create the final object.
The materials are mainly different types of plastic, metal, ceramics and sand powder (similar to artificial sandstone). Plastic is currently the most widely used material -mainly ABS or PLA, even though there are a number of alternative materials such as Nylon [8].
There is no single solution for 3D printing, but it involves using different methods, procedures, and materials to achieve the desired result. There are various 3D printing technologies such as stereolithography, digital light processing, laser sintering (laser melting), fused deposition modeling (freeform fabrication), inject, selective deposition lamination and others [9, 10]. Below we will introduce only technology Fused Deposition Modeling, because this technology uses the Mark Two printer.
Fused deposition modelling / freeform fabrication
3D printing using extrusion of thermoplastic material is a simple and perhaps the most famous 3D printing process. The name for this process is Fused Deposition Modeling (FDM) -melting applied modeling. The process is based on the melting of the plastic fiber by means of a heated extrusion head and its application in a single layer to the platform. Each additional layer is applied with the previous links (since it is melted) and after cooling, the material hardens (Fig.1).
Fig. 1. FDM technology principle
The FDM process (or Freeform Fabrication -FFF process) also requires pushing the support structure to the 3D model if it contains protruding shapes. For FDM, this means using a second water-soluble material that forms a supporting structure, and after the 3D model is printed, it is easily washed it away from the model. An alternative is the use of material that is then simply separated from the model -it breaks off. Models printed by the FDM are accurate and the printing process is reliable. Printers using the FFF method print less accurate models, but their quality is constantly improving.
Mark Two printer
Mark Two printer is one of Markforged's desktop printers, which uses FDM technology when printing (Fig. 2). The printer is able to print from nylon and onyx separately, or at the same time they can be reinforced with a continuous fiber of carbon, kevlar, and glass. By selecting the reinforcement and the plastic matrix correctly, we can delete the time required for structural iterations, and the components can be used immediately after extrusion.
By reinforcing the parts with fibers in their 3D printing, the Mark Two printer in the printed part achieve unique strength, stiffness and durability. The 3D printing software comes with the printer, which makes printing simple and intuitive. Markforged Eiger software is powerful and easy to use in an internet browser. Mark Two printer also has a built-in touch screen that lets you manage your printer, easily connect to Wi-Fi and printing management [10]. Technical specifications for Mark Two printer are listed in Table 1.
Plastic materials
Onyx, Nylon
Fiber materials Carbon, Kevlar, Glass fiber
The minimum layer thickness [mm] 0.1
3D print structures and fills
Onyx is a material based on extremely rigid nylon in combination with micro-carbon fibers. It is stronger, harder and more resistant to heat than other plastic 3D printing materials. It is the ideal material for the production of parts that require good look in compliance with industry requirements. The material provides toughness of nylon with added stiffness of fiber reinforced plastic, heat resistance up to 145° C and a high resistance to adverse conditions. The final product does not require any post-processing because its smooth and matte surface does not look like a piece that was printed on a 3D printer. Onyx can be used alone or reinforced with kevlar, glass or carbon fibers. The parts reinforced by these fibers extend beyond the boundaries of the normally 3D extruded plastic. According to Markforget, parts printed with Onyx are 30% stronger and stiffer than similar parts made in other 3D printers. All products printed with Onyx are ready for use right after printing. Material properties for Onyx reported by the manufacturer are shown in Table 2 [11]. Mark Two is capable of printing different structures at different percentages filling of the printed components. However, the percentage fill must be less than 100% in order to print individual structures. The printer software allows you to choose from three types of filler structures: triangular, hexagonal and rectangular filler. Figure 3 shows the individual fill patterns displayed in the Mark Two printer software.
Fig. 3. Fill patterns displayed in the Mark Two printer software
The structure sampler at different percentages of the filler was made for illustration . The triangular structure is denoted by the letter T, the hexagonal structure by the letter H and the rectangular fill by the letter R. Fill in % of the print is indicated by a number expressing the percentage fill (for example triangular filler of 60% = T60).
Experimental measurements
The influence of height and number of layers to the mechanical properties of the material was verified experimentally. Specimens for tensile tests were made on the basis of standard EN ISO 527-5 to verify the mechanical properties of the material Onyx. A series of tensile tests on specimens created by 3D printing were performed at 100% filled material [12][13][14]. Two types of layers were used to perform the tests (layer thickness 0.1 mm and 0.2 mm) and different layers were used (even and odd). The results of experimental measurements are reported in Table 3 and shown in Fig. 8. Figure 8 is defined as the stress-displacement dependence for the purpose of verifying the mechanical properties presented by the manufacturer. Ruptured specimens after tensile tests are shown in Figures 9 and 10. Fig. 9. Ruptured specimen made from 5 layers Fig. 10. Ruptured specimen made from 10 layers A set of specimens of structures H20, T20 and R20 was also prepared to perform experimental measurements [15,16]. Tensile tests were performed on these samples and the results were reported into Table 4. The graphical dependence (force-displacement) for individual fills is shown in Fig. 11. All specimens were made with the same external dimension (358 mm). Because the specimens were printed with a 20% fill and do not have a constant cross section, only the force needed to rupture them was evaluated. . 11. The graphical dependence of the force on displacement for individual fills The experimental results from the tensile tests show that the largest load at 20% of the filler takes specimens with a rectangular fill structure and the smallest load endures samples with a triangular fill structure.
Conclusion
Through a series of experimental tests, the mechanical properties reported by the manufacturer were verified. Based on the test results, it can be argued that the thickness of the layer has no significant effect on the mechanical properties of the material, but this does not apply when the number of layers is changing.
The mechanical properties of the material are lower in an odd number of layers than in the even number of layers. The specimen breaks along a plane in which a smaller number of layers are stored when the odd number of layers is used.
Based on experimental measurements, we recommend using the even number of layers when printing to maintain the best mechanical properties of the printed parts. Further experimental measurements should be performed on specimens with different fillings (40%, 60% and 80%) and structures (triangular, hexagonal and rectangular). The authors also plan | 2,570.4 | 2019-01-01T00:00:00.000 | [
"Materials Science"
] |
Descriptions of Attack Angle and Ideal Lift Coecient for Various Airfoil Proles in Wind Turbine Blade
The angle of attack is highly sensitive to pitch point in the airfoil shape and the decline of pitch point value induces smaller angle of attack, which implies that airfoil profile possessing closer pitch point to the airfoil tip reacts more sensitively to upcoming wind. The method of conformal transformation functions is employed for airfoil profiles and airfoil surfaces are expressed with a trigonometric series form. Attack angle and ideal lift coefficient distributions are investigated for various airfoil profiles in wind turbine blade regarding conformal transformation and pitch point. The conformed angle function representing the surface angle of airfoil shape generate various attack angle distributions depending on the choice of surface angle function. Moreover, ideal attack angle and ideal lift coefficient are susceptible to the choice of airfoil profiles and uniform loading area. High ideal attack angle signifies high pliability to upcoming wind, and high ideal lift coefficient involves high possibility to generate larger electric energy. According to results obtained pitch point, airfoil shape, uniform loading area, and the conformed airfoil surface angle function are crucial factors in the determination of angle of attack.
Introduction
According to growing greenhouse emissions and global warming the exploitation of renewable and pollution free energies is significantly required to alternative fossil fuel energy.
Representative sources of renewable energy are solar and wind. Wind energy has stood in the spotlight progressively due to the increased demand of scientific and industrial advancements, and wind supports possibly more that 20% of global electricity in the year of 2030 [1]. By the advantage of superior efficiency, wider operational range, and reliability, horizontal axis wind turbine (HAWT) is an example structure as a mass power production during the last several decades.
Flow field behavior around wind turbine are very complicate owing to turbulence generation, vortices, and stall flow. Numerous researches have investigated the aerodynamics occurring around wind turbines to understand the detailed process of kinetic energy extraction from wind. Blade element momentum (BEM) theory, Vortex method (VM), and Computational fluid dynamic (CFD) are widely known approaches. BEM is the combination of momentum and blade element theories by dividing the wind turbine blade into independent elements. The method is not appropriate for heavy loaded states, that is, the axial induction factor is greater than 0.5 [2,3]. The assumption of the flow field is inviscid is added to explicate VM. The wind turbine blade and wake are regarded as vortex particles. The influences of tip vortices can be predicted using VM, while it is difficult to investigate the effects of flow separation with VM [4,5]. CFD is a mathematical process for solving the numerical solutions of complex nonlinear partial differential equations involving fluid flow. CFD enables to describe the physical phenomena of laminar, transitional, and turbulent flows. Moreover, the behavior of streamlines, pressure, and velocity contours as actual flow around a wind turbine can be described with the help of CFD [6], and CFD has been used widely to predict HAWT performances.
The determination of airfoil shape for wind turbine blades is fundamental task for designing wind turbine rotors [7]. Airfoil design in the wind turbine is to accomplish a high aerodynamic performance that produces high electric energy in the designed wind turbine. By virtue of computer technologies many numerical tools are developed to investigate the optimization states of airfoil shapes. Hicks et al. [8], Eppler [9], Tangler and Somers [10], are early authors to compose numerical optimization in airfoil design. Conformal mapping method and velocity distribution are taken into account to design airfoil shape by researchers [11,12]. Echjijem and Djebli [13] considered the correction of the axial and tangential induction factors in the design of wind turbine blade, and Lim and Kim [14] studied multi-objective airfoil shape optimization using adaptive hybrid evolutionary algorithm. Lim and Kim found that the cases of lift maximum and high angle of attack show multi-modality in the design spaces.
However, the separated design process of airfoil and blade fails to grant an optimum state, and integrated design of airfoil and blade is required. 2D airfoil and 3D integrated design approach is addressed by Sartori et al. [15]. The airfoil shape is designed to increase computational efficiency, whereas limited accessible airfoil geometry is appeared. Wang et al. [16] suggested an integrated method that describes airfoil profiles with a trigonometric series form and series of polynomial equations using conformal transformation. The method yields direct and accurate shapes of airfoil and airfoil shape is controlled by the coefficients in series.
Wei et al. [17] presented an integrated method for designing airfoil families of large wind turbine blades. They included rotor diameter, tip speed ratio, and local speed ratio to express optimal airfoils, and a shape perturbation function is applied to the geometry of the prescribed airfoils. Kumar et al. [18] simulated airfoil shape for optimum wind characteristics using a computer program JAVAFOIL to drive the relationship of angle of attack with coefficients of lift and drag. But, most of previous works have analyzed numerically the influences of critical factors in the aerodynamic performance of specified airfoil shapes.
In the present study, by the method of conformal transformation functions for airfoil profiles and airfoil surfaces are expressed with a trigonometric series form, which depicts various airfoil profiles with the appropriate control of the coefficients of series. The attack angle distributions are described analytically around the circumference of various airfoil shapes and compared. Even, pitch point is controlled to clarify the differences of attack angle distributions. Ideal angle of attack and ideal lift coefficients are expressed by dint of the area of uniform for various airfoil profiles.
Airfoil Profiles
Any airfoil profiles can be obtained by a conformal transformation of a circle and expressed with Fourier expansions [19, p.46]. Let us define the coordinates of and ′ by, respectively, Due to the general transformation of ′ relating to plane given by the and can be represented with With the values at the specified 2 equally spaced intervals in the range 0 ≤ ≤ 2 , that is, 0, , 2 , ⋯ , (2 −1) , the λ, , and of the function are determined as and the function of is described with Note that the function ( ) describes the surface angle of airfoils. The conformal mapping from ′-plane to -plane caused by the transformation yields a circle in the -plane into a curve resembling a wing section in the -plane, where = 4 (see Figure 1). The c represents the airfoil chord length. The coordinates of ξ are defined as ξ = x + iy, which provides the expression of the coordinates of the airfoil with Then the angle of attack can be written by (a) (b) Figure 1. Airfoil profile transformed of a circle by conformal mapping: (a) angle of surface, (b) relative flow angle onto blade.
Ideal design of mean lines
The mean line is regarded as the locus of midway points between the upper and lower surfaces of the section. Mean lines under the action of a uniformly distributed loading from ⁄ = 0 to ⁄ = * and decrease linearly to zero at ⁄ = 1 have been calculated in Ref [19, p.74], and the ordinates are expressed as The implies the ideal lift coefficient. The ideal angle of attack for these mean lines is
Results and discussions
Three types of ( ) and five types of ( ) are chosen to describe of angle attack and ideal lift coefficient for various airfoil shapes. The functions chosen are exhibited below, and the airfoil shapes depicted by the chosen functions are displayed in figure 2. Figure 4 portrays the attack angle distributions of Type_3 airfoil profiles described by 1 ( ). As shown in Figure 4(a) and 4(b), the attack angle distributions surge with further fluctuation as RCP value decreases, which signifies that airfoil shape with smaller RCP value is more susceptible to the upcoming wind. But, the magnitude of attack angle is getting smaller with the decay of RCP, and the variation of angle attack meager in Type_3 airfoil of RCP ≥ 4. Figures 5 and 6 represent the angles of attack for NACA64418 and S809 airfoil profiles, respectively. The magnitude of attack angle distribution is getting larger as the value of RCP grows on both NACA64418 and S809 airfoil shapes. But, unlike Type_3 airfoil, there is no variation in the number of distribution fluctuation. On the whole the decline of RCP value induces smaller angle of attack in magnitude, which implies that airfoil profile possessing pitch point close to the airfoil tip reacts weakly to upcoming wind.
Conclusions
In this study analytical analysis has been developed to investigate attack angle and ideal lift coefficient distributions for various airfoil profiles in wind turbine blade. Pitch point and uniform loading area are taken into account, and airfoil shape functions of wind turbines and surface angle functions of airfoil are expressed with series using conformal transformations.
Angle distributions of attack appear with various forms depending on the conditions of airfoil shape, pitch point, and surface angle function. Ideal attack angle and ideal life coefficient are very sensitive to the variation of uniform loading area. Through results obtained the determination of proper pitch point, loading area, and airfoil shape are essential factors to control the angle of attack, and the results may be useful in designing wind turbine airfoils.
Data Availability
The data used to support the findings of this study are available from the corresponding author upon request.
Conflicts of Interest
The author declares that there are no conflicts of interest. | 2,241.4 | 2021-06-30T00:00:00.000 | [
"Engineering"
] |
Centimeter-scale suspended photonic crystal mirrors
Demand for lightweight, highly reflective and mechanically compliant mirrors for optics experiments has seen a significant surge. In this aspect, photonic crystal (PhC) membranes are ideal alternatives to conventional mirrors, as they provide high reflectivity with only a single suspended layer of patterned dielectric material. However, due to limitations in nanofabrication, these devices are usually not wider than 300 $\mu$m. Here we experimentally demonstrate suspended PhC mirrors spanning areas up to 10$\times$10 mm. We overcome limitations imposed by the size of the PhC and measure reflectivities greater than 90% on 56 nm thick mirrors at a wavelength of 1550 nm -- an unrivaled performance compared to PhC mirrors with micro scale diameters. These structures bridge the gap between nano scale technologies and macroscopic optical elements.
Photonic crystal (PhC) membranes are suspended dielectric sheets patterned with sub-wavelength, low-index two-dimensional periodic structures [1]. These patterns give rise to resonances that couple out-of-plane radiation to in-plane leaky modes, and can be engineered to transform a flat membrane into a mirror [2], a lens [3], or even a curved mirror [3][4][5]. Here we study a PhC consisting of a periodic lattice of holes in a membrane, whose hole radius and lattice constant can be tuned to reflect light at a wavelength of choice. When fabricated from materials with low optical absorption such as low-pressure chemically vapor-deposited silicon nitride (LPCVD SiN), one can realize mirrors with sub-wavelength thicknesses and reflectivities > 99 %, mostly limited by scattering losses, as shown in [6]. LPCVD SiN thin films also enable the combination of PhC mirrors with low thermal noise mechanical oscillators, due to their high intrinsic stress, thin geometry, and weak coupling to undesired thermal modes [7,8].
Microfabrication processes have so far restricted suspended PhC mirrors to areas around 300 × 300 µm 2 [6]. This size sets an upper bound to the waist of incident Gaussian beams, since wider waists do not completely interact with the PhC, resulting in decreased reflectivity. But the waists also have a lower bound: very small waists have a high divergence and couple to undesired PhC modes, which leads to shifting, broadening and shallowing of the high-reflectivity crystal resonance. These adverse finite-size effects have been consistently measured in very thin mirrors with thicknesses below 0.1λ, where λ is the wavelength of the reflected light [7,[9][10][11]. The ability to fabricate larger PhC mirrors with increasingly thinner membranes could greatly facilitate the combination of high reflectivity and low mechanical losses [7]. These properties indicate the potential that PhC mirrors may have for reducing thermal mirror coating noise which stands as a limit in precision measurements such as atomic clocks [12], frequency-stabilized lasers [13], and gravitational wave detectors [14]. At the centimeter scale, PhC mirrors could have more immediate applications as deformable mirrors with adjustable wavefront [15], or evanescent field sensors with a large interaction area [16,17].
In this letter we experimentally demonstrate freestanding SiN photonic crystal mirrors with thicknesses of 56 and 210 nm and areas of up to 10 × 10 mm 2 . Not only do we increase the area of suspended PhC mirrors by nearly 4 orders of magnitude compared to previous works, we also show that these large aspect-ratios allow us to achieve high reflectivity from membranes thinner than previously measured. We observe greater than 90 % reflectivity of 1550 nm light from mirrors with a thickness of 0.038λ (56 nm) -a significant increase compared to previous devices with similar thickness and wavelength [9]. Such large structures allow studying the spectrum of PhC membranes as a function of incident beam waist with less constraints from finite size effects.
Our suspended PhC mirrors are fabricated from highstress (1 GPa) LPCVD SiN films deposited on 200 µm Si wafers. The geometry of the PhC structures is optimized for each desired film thickness to a wavelength of 1550 nm using finite-difference time-domain (FDTD) simulations [1]. The structures are patterned on the SiN films using electron beam lithography and a plasma etching process (CHF 3 + O 2 ). Stitching errors occur about every millimeter due to stage drifts during the beamwrite and are on the order of 1 µm wide. One of the fundamental challenges for large aspect-ratio membranes is suspending them without causing any fractures. Typically liquid etchants such as KOH or TMAH are used to release free-standing SiN structures from their Si substrates. However, such wet processes produce a number of forces, like turbulences and surface-tension at the interfaces, which can easily destroy the fragile suspended PhC mirrors. These methods also leave residues that negatively impact the optical performance of the mirrors, requiring additional liquid cleaning steps that decrease the the fabrication yield, specially for large area devices [18]. and a photograph of a 10 mm-wide, 210 nm-thick PhC mirror next to a commercial 1/2 inch mirror for size comparison (bottom). The rectangular shaped patterns within the PhC are stitching errors from the mainfields of the beamwrite, which do not affect the measured reflectivity significantly. The inset shows a scanning electron microscope picture of the actual photonic crystal. The full mirror is made up of around 6 · 10 7 holes. (b) Illustration of the cross section of the mirror. The thin membrane is made of SiN and is supported by a silicon chip. (c) FDTD simulation of a reflected light mode on a PhC membrane. (d) Simplified setup used to characterize the reflection of PhC mirrors. We focus a wavelength-tunable laser beam perpendicularly onto the membrane. The radius of the incident beam is controlled with a lens system. For each radius, we acquire the reflection (D2) and transmission (D3) in relation to a reference beam (D1) that is split off the laser output using a polarization beam splitter. More details can be found in Appendix A.
In order to overcome these limitations, we have developed a stiction-free RIE-ICP plasma release using SF 6 [19]. A hot piranha solution consisting of sulfuric acid and hydrogen peroxide is first used to remove surface contaminations on the unreleased structures. This is followed by a diluted HF solution to smoothen the SiN surface [20] and remove surface-oxide from the silicon which allows for an even release of the membrane. Finally, we suspend the PhC mirrors using the SF 6 plasma release. Figures 1(a)-(c) show a sketch and a photograph of a 10 mm-wide, 210 nm-thin mirror, a scanning electron microscope picture of the PhC pattern, and numerical simulations of the reflected optical field.
In order to characterize the optical properties of the PhCs, we fabricate three devices with different thickness and size: two 210 nm-thick mirrors, 4 × 4 mm 2 and 10 × 10 mm 2 -large; and a 56 nm-thick, 1.6 × 1.6 mm 2 -large one. We measure the mechanical spectrum of the fabricated devices to match those of bare square membranes with the same intrinsic stress. This indicates that despite the unconventionally large areas, the material stress remains high, which should guarantee the membrane's flatness, an important point when developing high reflectivity mirrors. This is also a relevant observation when estimating the thermal displacement noise of this type of device. More details can be found in Appendix B.
The devices are characterized by focusing a wavelength-tunable laser beam perpendicular to the PhC mirrors ( Fig. 1(d)). We measure the reflected and transmitted power and compare it to a reference beam that does not interact with the devices. For calibration, we use a commercial broadband mirror at the same position as the PhC mirrors. The laser is tuned from 1530 to 1630 nm. The recorded signal is normalized to the reference arm and to the calibration mirror to obtain the reflectivity spectra for multiple beam waists. We vary the beam radius between 8 µm and 1.1 mm using a lens system placed in front of the PhC membranes. This allows us to analyze the behavior of PhC membranes with different thicknesses to laser beams of varying sizes. Figure 2 shows a selection of measured spectra of the 210 nm-thick, 4 × 4 mm 2 -large and the 56 nm-thick devices. While the PhC is completely released, for testing purposes the chip itself is not fully etched through (cf. Fig. 1(b)). This results in a parasitic interference pattern with a periodicity of 1.8 nm on top of the expected PhC spectra, corresponding to a 200 µm-thick Si etalon. Since the frequency of this interference is well defined, we post-process it by band-pass filtering the data. Appendix C contains the full set of acquired spectra, as well as a detailed description of the data processing.
The spectra of the 210 nm-thick PhC mirror, shown in Fig. 2(a), exhibit a resonance at 1549 nm that varies little with the incident beam waist. At 1573 nm a parasitic resonance emerges whose width increases as the waist becomes smaller. This can be understood by considering the decomposition of a Gaussian beam with waist w 0 into plane waves [21]. The decomposition in terms of incidence angle is weighted by a Gaussian distribution with a standard deviation equal to the beam divergence θ = λ/πw 0 . A large waist w 0 has a small divergence θ, which is a good approximation to a plane wave with a zero angle of incidence. As w 0 decreases, θ becomes larger, and so plane waves with larger angles of incidence have a stronger weight on the decomposition. These waves can couple to PhC modes other than the resonance of interest, giving rise to parasitic features such as the one observed. We can apply the same reasoning to explain the increase in maximum reflectivity of the main resonance: the device geometry was optimized assuming a plane wave with normal incidence. Hence, beams with a large waist approximate this condition better, which Figure 2. Reflectivity spectra of the PhC mirrors. Shown is a selection of measured reflectivity spectra of PhC mirrors with film thickness of (a) 210 nm and (b) 56 nm. Each spectrum shows the reflection of a Gaussian beam with the specified waist. As the waist increases, the incident beam approaches the behavior of a plane wave, for which the devices are optimal, and so the maximum reflectivity increases. Due to the finite size of the 56 nm PhC mirror, its reflectivity drops as the incident beam becomes larger than the PhC area. The data were digitally processed to remove parasitic interferences from the substrate (see Appendix C for details).
results in a reflectivity closer to the optimized one.
In Fig. 2(b) we observe that the main resonance of the 56 nm-thick membrane exhibits stronger shifts in wavelength, width and maximum reflectivity with varying beam waist, in comparison to the 210 nm-thick device. As explained in the work of Bernard et al. [9], the spectral response of plane waves incident on a PhC mirror depends on the angle of incidence. This dependence is stronger for thinner devices and results in large resonance wavelength shifts. Therefore, as the beam waist decreases -and its divergence increases -the reflectivity of thin devices is more strongly attenuated. On the other hand, due to the small size of the 56 nm-thick PhC mirror (area of 1.6 × 1.6 mm 2 vs. 4 × 4 mm 2 for the 210 nm-thick device) beams with waists larger than 280 µm are partially scattered outside the PhC and exhibit a decreasing maximum reflectivity (see below). Figure 3 shows the maximum reflectivity of all PhC membranes as a function of the incident beam waist. As described in the previous paragraphs, larger beam waists approximate the design conditions of the PhCs better, reducing the amount of light that couples to unwanted modes. As such, the maximum reflectivity increases for larger beams. We verify this behavior with simulations and plane wave decomposition: starting with the geometry parameters that resulted from the FDTD optimiza- tion and that were patterned on the SiN membranes, we simulate the reflectivity of plane waves with varying angles of incidence at the resonance wavelength using rigorous coupled-wave analysis (RCWA) [22]. The reflectivity at each beam waist is then the weighted sum of the simulation results, following a Gaussian distribution with standard deviation θ, which is further described in Appendix D.
The reflectivity of the 56 nm-thick PhC mirror decreases when the beam radius measures between 280 and 390 µm. Considering that the field amplitude of a Gaussian beam falls as e −r 2 /w 2 0 , where r is the distance from the beam's center, we expect 99 % of the field to be within a diameter of 6 × w 0 . Since the PhC measures 1.6 × 1.6 mm 2 , beams with waists larger than 1.6/6 mm = 270 µm will have larger field components reflecting off the area outside the PhC. This allows us to observe a smooth transition between two regimes: one, for small waists, where the PhC response is limited by a large beam divergence and another one for large waists, where the limitation is the finite size of the device. Between these two bounds we see a plateau where the maximum reflectivity >90 % is approximately constant. To the best of our knowledge, this is the highest reported reflectivity of a 56 nm suspended PhC mirror, operating in a regime with lower beam divergence and finite size limits.
In conclusion, we fabricate and characterize the first suspended PhC mirrors that span areas up to squarecentimeters, with reflectivities exceeding 99 %, which are only limited by our measurement precision. Previous attempts focused on devices not wider than 300 µm, resulting in strong limits to the maximum achievable reflectivity, in particular for devices thinner than 0.13λ. By measuring the reflectivity spectrum of the PhC mirrors for varying incident beam waists, our work shows that these devices are indeed strongly affected by finite size effects. In particular, we observe a reflectivity of 90 % for a 0.036λ-thick PhC mirror at a wavelength of 1550 nm, whereas previous reports of devices with similar thickness were limited to 62 % [9,11]. Despite the presence of fabrication errors in the lithography process for the largest device (see Fig. 1(a)), we suspect that its performance becomes insensitive to small defects in the PhC lattice for large beam waists, since the reflectivity shows no appreciable changes with increasing waists (see Fig. 3, 210 nm data). Since larger incident beams sample a larger area of the PhC structure, we observe that the reflectivity seems robust to imperfections in the 2D array of holes that arise from drifts or poor stitching during lithography. It is also important to note that these mirrors could be improved even further with more sophisticated methods of lithography. Electron beam lithography is prone to stage drifts during exposure and secondary back-scattering of electrons from the substrate which produce uneven dosing -both of these effects can lead to an inhomogeneous lattice constant and variations in hole size. We envision scaling these devices further to full wafer sizes by using techniques such as nano-imprint lithography, lithography stepping, or interference lithography [23]. Due to its high intrinsic stress, LPCVD SiN PhC membranes should remain relatively flat even at larger areas. Together with the low optical absorption of SiN, this is a promising platform for light sails in future space probes propelled by light, such as the Breakthrough Initiative Starshot [24]. In addition, high-stress SiN membranes have been shown to have high thermal noise suppression which becomes better with thinner, larger membranes [7]. At large scales, SiN PhCs could thus be an interesting route towards low-noise suspended mirror coatings. In Appendix E, we include a first-order estimate of the thermal displacement noise such devices would have, and make a baseline comparison of their performance to the well-documented mirror coatings used on LIGO testmasses.
Furthermore, the fact that these mirrors are suspended allows them to be used in a variety of applications that profit from mechanical tuning of mirrors. Deformable mirrors could be realized with these PhC structures [15], for example through electrostatic-tuning with arrays of electrodes close to the mirror, or even as displacement noise tunable mirrors, using techniques such as optomechanical feedback control [25]. Further experiments are planned to study the transversal mode composition of the reflected beam and to properly characterize the devices' optical absorption and scattering using a high finesse optical cavity. These developments open up a new paradigm in photonics -one that steers away from the focus on simply miniaturizing components, but instead tries to bring the performance of nano-engineered materials to large scales. Figure A1. Schematic of the complete characterization setup. See text for a detailed description.
APPENDIX A: SETUP
In order to characterize the optical properties of the PhCs, we use the setup outlined in Fig. A1. A fiber coupled Santec TSL510 wavelength-tunable laser is used as a light source. Its polarization is adjusted with a fiber polarization controller (FPC) and the beam is brought into free-space using a triplet collimator (Thorlabs TC12APC-1550). The first polarization beam splitter (PBS) is used as a polarizer to mitigate the effect of polarization drifts in the fiber part of the setup. The second PBS splits light into the beam that is going to interact with the sample (incident beam), and a reference beam that is detected by D1. We use the reference beam to remove the effect of power oscillations from the measured spectra that are not related to the sample. Between the two PBSs we place a half-waveplate (λ/2) to control the power ratio between the incident and reference beams. After the second PBS, the incident beam is focused onto the sample using a lens set (between 1 and 3 lenses) which are adjusted to change the waist from 8 to 420 µm. Light reflected by the sample is sent into the second PBS. We place a quarter-waveplate (λ/4) in the incident beam path such that the reflected beam is separated from the incident beam by the PBS and then detected by D2. Light transmitted by the sample is recorded by D3.
For every lens system a commercial broadband-coated mirror is placed at the sample position and record reference and reflection spectra. These serve as calibration and remove effects such as losses in the optical path from the sample reflectivity spectra. The sample is then placed back and care is taken to ensure good tip/tilt alignment with respect to the optical beam, since the response of the PhC is very sensitive to the incident angle. Using flip mirrors we are also able to send the transmitted or reflected beam into an infra-red CCD. The camera helps during the tip/tilt alignment of the sample, or acts as a reference during the alignment of the lens system.
The reflectivity spectrum R is calculated as where V PhC and V cal are the voltage signals of the reflected beams from the PhC and the calibration mirror, V ref PhC and V ref cal are the reference signals of the corresponding PhC and calibration mirror measurements, and R cal is the reflectivity of the calibration mirror, which is specified to be 99.8(3) %. We consider all measurement uncertainties to be independent from each other, and estimate the uncertainty in reflectivity ∆R via the method of uncertainty propagation To estimate the uncertainty of the beam waist, the same propagation method was applied. As uncertainty parameters, the position of each lens (with a count varying between 1 and 3) and its focal length is taken into account. The beam was propagated through the lens system by means of the complex beam parameter and ABCD matrices.
The photodetectors D1, D2, D3 are home-built surfacemount-device circuits equipped with a JDSU ETX500 photodiode. By means of electronic design and spectral characterization, a linear response to the optical input power is guaranteed.
APPENDIX B: MECHANICAL MODES OF PHC MIRROR
In order to get a better understanding of the mechanical properties of the PhC mirrors, a displacement spectrum was recorded for a 4 × 4 mm 2 mirror. The device was mounted in a vacuum chamber and a homodyne detector measured the phase quadrature of the back reflected light. Figure A2 shows a spectrum recorded in the center of the mirror and another spectrum measured at the edge of it. The off-center spectrum displays mechanical modes which have no net-effect on centered beams, i.e. modes which are mirror symmetric on two orthogonal axes. The fundamental mechanical frequency of a bare square membrane is given by where L is the length the membrane, ρ is the material density (2.7 g/cm 3 for SiN), and σ is the tensile pre-stress in the film, which we take to be 1 GPa, a value defined by the parameters of the LPCVD deposition process. A square membrane with the same dimensions and material properties as the one discussed here has a fundamental frequency of 108 kHz. Comparing this to the value measured for our device (117 kHz) leads us to conclude that the pre-stress remains high even for these unconventionaly large suspended areas.
(1, 1) Figure A2. Measured mode spectrum. Shown is the spectrum of the back reflected light from a 4 × 4 mm 2 PhC sample detected with a homodyne detector. The optical power for this measurement was set to 1 mW, the resolution bandwidth to 100 Hz and the spectrum was averaged 50 times. The device was driven with a piezo actuator connected to a white noise generator (peak-to-peak voltage 100 mV) inside a vacuum chamber at 1 · 10 −5 mbar. Electronic and displacement noise from the mounting-frame were subtracted from the displayed data. We calibrated the noise from the mounting-frame by measuring a spectrum with the laser beam focused on the frame. The purple trace (top) shows data obtained with the laser focused in the center of the device, while for the green trace (bottom) the laser was focused onto the edge of the PhC mirror. The latter was done to record modes which have no net-effect on the reflected beam, i.e. a (2, 2) mode. The theoretically expected mode frequencies are highlighted on the upper horizontal axis and match the measured spectrum very closely. To simplify the analysis, we model the structure as a simple square membrane without holes. Starting from the fundamental mode frequency of the device, we can calculate the frequencies of all higher-order modes [26], which we plot on the upper horizontal axis in Fig. A2. We observe a very accurate fit of the measured higher-order modes (the deviation is around 1 %). The measured spectrum also allows to predict the noise performance of an optical cavity made with such PhC mirrors [27]. Figure A3 shows the full, unprocessed set of measured reflectivity spectra for the (a) 210 nm and (b) 56 nm-thick devices. We measured the spectra for several incident beam waists, which are indicated in the figure legends. The spectra follow the expected Fano resonance shape, characteristic for this type of device.
APPENDIX C: POST-PROCESSING OF SPECTRAL DATA
In addition, we also see a parasitic oscillation with a periodicity of 1.8 nm. This is because the devices are suspended but the substrate is not etched through. In fact, to facilitate the testing process, the membranes are undercut by only a few µm on top of the 200 µm silicon substrate (cf. Fig. 1(b)). The observed periodic pattern arises from interference of reflections from the substrate interfaces. Using the thickness of the silicon substrate and a refractive index of 3.5, we calculate a free spectral range of 1.7 nm for a wavelength of 1550 nm, which is in excellent agreement with the observed oscillations. The periodicity observed on the measured spectra is equal for all measurements and as such, we remove it digitally using the procedure described below.
The Fourier transformations of the unprocessed reflectivity spectra show peaks (marked by the arrows in Fig. A4) that are well defined and common to all measurements, which we associate with the described etalon effect. These are obtained with the fft.rfft and fft.rfftfreq commands of the Python numpy library.
To remove these parasitic features from the Fourier transforms, we apply a Tukey filter, with filter parameter 0.9, around the identified peaks. The filter was generated using the function signal.tukey from the scipy library. Finally, the filtered spectra are obtained by performing the inverse Fourier transform using the fft.irfft command. These can be seen in Fig. A5. We carefully verify that filtering does not change the reading of the maximum reflectivity. Figure A6 shows the raw data of the 210 nm-thick, 10 mm-wide device. This device was attached to a singleside polished carrier wafer using an index matching oil. Since the bottom surface of the substrate is rough, the interference between interfaces is no longer visible. Therefore this data set did not require any post-processing.
APPENDIX D: SIMULATED REFLECTIVITY SPECTRA FOR GAUSSIAN BEAMS
To simulate the expected reflectivity spectra of the PhC membranes, we use a rigorous coupled wave analysis (RCWA) [22] combined with a plane wave decomposition [28]. On the one hand, choosing a RCWA implies that the simulated spectra are valid only for periodic structures, i.e. spectral changes caused by diffraction effects at the membrane's edge cannot be recreated. As this approach commonly starts with a plane wave as the incident electromagnetic field, it also requires to implement a composition of plane wave spectra when dealing with Gaussian beams. On the other hand, a finite element analysis (FEA) can in principle be set up to compute spectra of a finite, e.g. 10 × 10 mm 2 large, PhC membrane excited by a Gaussian beam of waist w 0 . However, the simplicity of a FEA approach has disadvantages when it comes to hardware, especially memory, requirements. To faithfully simulate the structure, the model volume has to cover about 20 × 20 × 1 mm 3 and still capture the details of the nano-scale membrane, which increases the memory usage drastically. A RCWA only discretizes the actual PhC membrane, such that the reflected field can be retrieved at any point above or below the structure. Finally, having simulated a set of plane waves via RCWA allows to assemble Gaussian beams of any size. For our requirements, the RCWA approach therefore is most appropriate.
We simulate two different unit cells: Each cell, composed of 140 modes, is excited at a certain wavelength with 66 2 plane waves of various polar and azimuthal angles of incidence. To verify that the structure is polarization insensitive, the wavelength-and angle scan is conducted for both s-and p-polarization. The simulation is built around an open source RCWA package [29], which rotates the s and p component of the incident field with respect to the incident angles. To align the polarization uniformly for all angles, the s-and p-electric field component E are transformed as and for a s-and p-polarized beam, respectively. Here the polar angle is denoted by φ, while θ is the azimuthal angle. This set of transformations inverts the global rotation implemented in the software package.
(A6) Figure A7 illustrates the results of the simulations for a 56 nm and 210 nm unit cell with the parameters given above. Due to a small mismatch in the cell parameters the absolute resonance frequency of the measured and simulated spectra deviate from each other slightly, however the overall features of the measurement are recreated faithfully. The individual simulations of s-and ppolarization exhibit virtually no difference, which is important as we probe the membranes with a circularly polarized beam. From the data plotted in Fig. A7, the maximum achievable reflectivity can be readily extracted by determining the peak reflectivity for each wavelength and beam waist scan. In figure A8 the results from the main text are plotted again and the simulated maximum reflectivity is shown for both polarizations. A zoom into the last two percent helps reading out the measured values.
APPENDIX E: ESTIMATION OF THERMAL DISPLACEMENT NOISE
Thermal mirror coating noise is currently one of the main limitations to the sensitivity of high-precision experiments including atomic clocks, frequency stabilized lasers and gravitational wave detectors. Widely used in these communities are distributed Bragg reflector (DBR) coatings made of alternating layers of dielectric materials. One challenge with DBR coatings is that their reflectivity has a natural trade-off with the number of layers used (and therefore the total thickness). Increases in coating thickness are usually associated with increases in coating's thermal Brownian noise. Attaining high reflectivity requires DBR surfaces which are commonly microns thick, while PhC mirrors can realize similarly high reflectivities with a membrane which is only the thickness of a single DBR layer. Additionally, their suspended geometry makes them into an easily deformable mirror surface, which potentially provides mechanical isolation from substrate (i.e. test mass) noise, and the possibility to dynamically tune the mechanical properties using optomechanical techniques.
In order to assess the potential that suspended PhC membranes could have in these types of applications, we perform a simplified calculation of the thermal noise per- formance of suspended PhC mirrors in this section and compare it to the thermal coating noise of the a-LIGO experiment [30].
For large LPCVD SiN mirrors we estimate the biggest noise contribution to be due to the thermal displacement noise, which for a square membrane is given by [31] where Q is the mechanical quality factor, k B the Boltzmann constant, T is the membrane's temperature, m eff the effective mass of the membrane's fundamental mode, and ω m its frequency given by Eq. (A1). The effective mass can be estimated with m eff = m/4 [32], where m is the physical mass. It is further reduced by a factor of 0.3, which accounts for the mass lost to the PhC holes. There are numerous limiting factors to the mechanical quality of a membrane [26,33]: thermoelastic damping, surface defects, Akhiezer damping, etc. For LPCVD SiN membranes, the most relevant factors are acoustic radiation losses and damping from collisions with gas particles. The acoustic radiation losses into the substrate generally scale as the ratio between L and the thickness h: Q rl ∝ L/h [26,33]. Considering previously measured radiation limited quality factors of 4 · 10 7 for L/h = 5 · 10 4 , we can extrapolate the radiation limit for arbitrary sizes of the PhC mirror. In addition, the quality factor limited by gas damping is given by [34] Q p = π 2 3 2 ρh ω m 2π where R is the ideal gas constant, p is the pressure, and m g is the molecular mass of the background gas molecules. The final Q is given by Q −1 = i Q −1 i , where Q i are the various contributions mentioned above.
In order to estimate the thermal displacement noise of suspended PhC mirrors, we need to assume some parameters. We chose those of the a-LIGO experiment, since its DBR coated mirrors are well known and characterized in terms of noise properties. This allows us to make a first-order comparison of how suspended PhC mirrors would operate when scaled up to the same size of the a-LIGO mirrors.
We take a SiN film thickness of 210 nm, a lateral size L = 350 mm, and effective mass m eff = 12 mg. We assume the mirrors are placed in a vacuum chamber at room temperature with a pressure of p = 7 × 10 −9 hPa and that the main background gas component is hydrogen [30]. These parameters result in a fundamental mechanical frequency of ω m /2π = 1200 Hz and a pressure-limited fundamental mode mechanical quality factor Q p ∼ 10 8 . Considering a detection frequency of 100 Hz, we find a thermal displacement noise of around 10 −17 m/ √ Hz. For comparison, the thermal coating noise of the mirrors used in a-LIGO is of the order of 10 −20 m/ √ Hz. These estimates are mainly limited by the environment pressure, which sets an upper bound to the mechanical quality factor. By decreasing the pressure further it could be possible to improve the thermal displacement noise significantly. Furthermore, suspended mirrors have the additional advantage that they can be adjusted, for example either through the addition of tuning electrodes or optomechanical techniques, in order to further reduce the noise performance in the desired regime.
It is important to note that the focus of this calculation is the estimation of thermal Brownian noise associated with the mirror coatings. The presented calculations and mirror designs are heuristic in nature and only allow one to make estimates comparing different mirror coating noise performances. It is however not entirely clear for example, how the Brownian noise related to the substrate (or test mass) would couple to such a suspended mirror.
This could be relevant for monolithic cavities in quantum optomechanics experiments at room temperature, where substrate thermal noise is the dominant source of heating in laser cooling experiments [32]. In addition, it has been shown that at increasingly large aspect ratios the substrate thickness becomes a significant variable in a membrane's mechanical quality factor [7]. A massive substrate could work well in experiments which require large test masses. How these effects translate to the cmscale remains an open question. | 7,721 | 2017-07-25T00:00:00.000 | [
"Engineering",
"Materials Science",
"Physics"
] |
Detection of alpha particle contamination on ultra low activity-grade integrated circuits
We propose to apply the superheated droplet detector (SDD) technology to the measurement of alpha-particle emissivity on integrated circuits of ultra-low activity grade (< 1 /khcm2) for high reliability applications. This work is based on the SDDs employed within our team to the direct search for dark matter. We describe the modifications in the dark matter SDDs with respect to fabrication, signal analysis and characterization, in order to obtain a device with the adequate detection sensitivity and background noise.
Introduction
Soft Errors (SE) are non-destructive functional errors induced by energetic ion strikes.An important parameter is the critical charge required to change the logical state of a stored data bit.With the continuous technology downscaling, the decreased node capacitances and operating voltages reduce the critical charge, thereby increasing device sensitivity to SE. Electronic devices in aircrafts, space missions and nuclear power plants are specially selected for their reduced intrinsic SE rate (SER) and resistance against radiation-induced SE.
There are two primary sources of terrestrial SE: alpha-particles ( ) emitted from the radioactive impurities in materials nearby the sensitive volume (packaging, solder bumps, etc) and atmospheric neutrons (n) which produce highly ionising charged particles on their interaction with the component materials.The -induced SER increases more rapidly with decreasing critical charge and can overcome the n-induced SER even with Ultra Low Activity (ULA) materials, i.e., with alpha emissivity below 10 −3 h −1 cm −2 [1].
Although fast and thermal neutron-induced SE reappeared in advanced integrated circuits (IC) [1,2] they can be kept negligible even below 28 nm with improved Si technology and carrier gases depleted in 10 B [3]. Alpha contamination remains therefore a major concern of nanoelectronic companies for commercial, industrial, aerospace and defense applications where reliability is mandatory.Qualification methodologies for ULA ICs have included variable-dependent measurements or underground tests (in a place devoid of cosmic radiation with negligible local -and n-backgrounds).Evidence of any contamination is apparent in less than 6 months underground, but measuring the -SER with any precision after 1-2 year testing is not possible with any of these methods [4].
Industry roadmaps call for instruments with detection limits of 10 −3 h −1 cm −2 in the energy range 1-10 MeV for measurement times of less than 1 week with sample sizes ∼1500 cm 2 at a cost < 50 kEUR [5].These conditions cannot be fulfilled by any of the current commercial proportional counters, since their backgrounds (5 count/h) are a factor of 5 too high [6].Promising alternatives based on ionisation counters are under development and evaluation for ultra-low background -emissivity measurements, but no general consensus has been obtained up to now.One of the problems is the internal contamination by radonemitting isotopes that simulate 's from the sample and moreover the cosmic bias that induces a lab-lab variability of the measurement accuracy [7,8].
In this work we propose a new approach to measure -emission rates, based on the superheated droplet detectors (SDD) developed by our team towards the direct search for dark matter (DM) [9].Similarly to IC, SDD are sensitive to 's and n's.Until now, their development aimed to achieve minimal n-background signal, as events caused by DM mimic n-interactions and are extremely rare ( 1 count/y in 1 kg target material).In the proposed application the focus is reversed, having -detection as its main purpose.As our current SDDs can embed small samples of a few cm 2 , we will primarily consider the measurement of individual devices.A target value of < 10 −3 h −1 for the technique sensitivity is thereby set.
Underground testing of the standard DM SDD demonstrated an intrinsic background in the order of 10 −4 count/h and 10 −3 count/h for n and , respectively [9] with a detection efficiency of ∼95% [10].The background signal being the critical parameter to qualify an instrument's ability for low-level measurements, our SDD has an intrinsic -background signal 100 times smaller than that of the ionisation counter, and a comparable detection sensitivity.
In this paper we describe the main challenges towards the implementation of the new methodology and report preliminary results.
Detector fabrication
Intensive R&D is underway towards the elaboration of an SDD with a sample embedded in a central position.The close contact between the droplets and the sample is mandatory, as attenuation by any interface material results in a significant sensitivity loss.On the other hand the introduction of irregularities in a moderately superheated material triggers spontaneous nucleations that produce acoustic noise and reduce detector lifetime.We have recently defined a post-fabrication method based on a liquid detector material and recompression stages that yield a smooth sample-detector interface with a distribution of droplets in the vicinity of the sample.Operation at a lower superheat [11] via modification of the thermodynamic parameters or the superheated liquid is under consideration aiming at further noise reduction.
Event localisation and discrimination
Alphas emitted by the sample are located in its vicinity, in the central volume of the detector.In contrast, those originating in Rn diffused through the detector walls and from emitters i-DUST 2016 in the detector container are localised near the glass-gel interface [12].A technique towards the spatial localisation of events was developed based on the analysis of time delays among the signal detection by the various microphones of an array.Tests with a hot probe yielded a spatial resolution of 2 cm 3 that is adequate to identify events originating from a fiducial volume surrounding the sample [13].
Furthermore, the evaluation of the acoustic signals revealed that -and n-events produce different amplitudes, larger ones corresponding to 's as a result of a greater bubble expansion power from the formation of various proto-bubbles.At signal amplitudes of ∼100 mV there is a 20 mV gap between the and n-distributions which is clearly resolved by the signal acquisition system (resolution 0.3 mV) [9].
We will proceed with the concomitant application of the localisation and particle discrimination routines in order to extract a signal free from any radiation rather than 's from the volume of interest, thereby decreasing noise and increasing device -sensitivity.A schematic view of the detection/discrimination system is given in Fig. 1.Current investigations are focussed on the fine acoustic characterisation of the detector (e.g.model of sound propagation in the detector material, reflections in the detector container, dependence of sound speed with thermodynamic conditions) for an improved event localisation.
Response to alpha particles
Most SDD applications are concerned with the detection of neutrons or heavy recoiling atoms [11], whereas in this work we focus on the detection of 's.Our initial investigations of the intrinsic SDD response to 's were performed using spectroscopy-grade liquid sources that are homogeneously dispersed in the gel during the stirring phase of the fabrication process.Different emitters (Sm, U and Th) and activities are considered.The nucleation rate as a function of temperature for 238/232 U in a C 2 ClF 5 SDD at 1 bar is shown in Fig. 2, which displays a different variation from that corresponding to the local radiation background (measured with an undoped SDD).
Different bubble shapes and sizes and moreover different detection efficiencies were observed for the various emitters.The influence of energy on the detector response is under investigation using a simplified model of the SDD response that considers the Bragg i-DUST 2016 peak [14] and will be further developed via Monte Carlo simulations coupled to stopping power and energy deposition calculations [15].The correlation between bubble geometries and the acoustic signals will be evaluated.Such experiments using liquid sources will be explored to extract important parameters (e.g.Harper parameter [16]) for modelling detector response.
Neutron-induced alpha background
For SDD measurements at ground-level, production of 's within the fiducial sample volume upon neutron interaction with light elements should be addressed.The detector gel was evaluated by Ion Coupled Plasma Mass Spectroscopy with respect to B and Li and for completion, Sm, U and Th.Only upper limits were obtained corresponding to the measurement blanks: 5 ppm Li, 30 ppm B, 1 ppm Sm, 1 ppm U and 10 ppm Th.The upper limits for emitters correspond to an intrinsic -background much larger than measured.As for B, the measured upper limit corresponds to a production rate of alphas in the fiducial volume of a (1.5 × 1.5) cm 2 sample, exposed to ∼1 n th cm −2 h −1 thermal neutrons at ground-level [17] of ∼10 −2 h −1 , which exceeds the order of magnitude of the target values for ULA levels.Measurements with improved detection sensitivity are therefore necessary.Furthermore, the variability of neutron fluence rates (geomagnetic, terrain, altitude, solar, weather) justify an evaluation of the neutron environment at the detector location.Although we favour the application of standard techniques such as Bonner spheres, the SDD themselves can provide an alternative methodology for environmental neutron spectrometry [18].
Future developments
Additional questions to be addressed include the investigation of the SDD response to solid sources, and a series of test measurements at ground-level and underground -the latter intended to qualify the developed methodology.Measurements will initially focus on standard, calibrated sources and gradually include actual integrated circuits.We are primarily focused on evaluating the following Field Programmable Gate Arrays from i-DUST 2016 Xilinx [19]: (i) Spartan 6 (45 nm), which has been tested underground with published -SER values on the order of 135 FIT (1 FIT=1 error per 1E9 hours of use); (ii) Virtex 6 (40 nm), with a particularly low -SER of 9 FIT/Mb; (iii) 7-series parts (28 nm) with -SER=22 FIT/Mb; (iv) 20 nm and possibly 16 nm devices (Virtex and Kintex UltraScale).necessary.
Ideally, the underground measurements will be performed at the site where Phase II of SIMPLE was run (GESA room of Laboratoire Souterrain a Bas Bruit) in order to take advantage of the work made in the past towards the reduction and characterisation of the environmental neutron and alpha radiation levels.An effort was made to suppress Rn in the detector by continuous purging of the room air, circulation of the water bath and detector pressurization.The alpha background achieved (measured: 2 × 10 −3 h −1 ) has order of magnitude of the aimed sensitivity [9].As the value agrees with estimates of the Rn contribution, we expect to suppress the majority of the background -events using the spatial localisation algorithms.The environmental neutron field in GESA (originating mainly from radioimpurities in its concrete walls) was reduced by two orders of magnitude with the installation of a water-based shielding [20].The residual neutron background was characterised in detail using Monte Carlo simulations, their outputs being normalized to the measured activities of U/Th in the experiment materials [21].The on-detector thermal neutron fluence rate of ∼1 × 10 −4 n th cm −2 h −1 (calculated) will induce a negligible rate of -events in the sample region (see Section 2.4).The fast neutron background (calculated: 2 × 10 −4 n cm −2 h −1 ) induces a reduced event rate in the detector (measured: 9 × 10 −5 evt h −1 ) that does not compromise its lifetime and can be rejected based on signal analysis.
Conclusions
We propose an innovative approach to the measurement of -emissivity on ULA-grade integrated circuits, using the SDDs developed by our team for dark matter search.SDDs are of interest because its measured intrinsic -background signal is two orders of magnitude lower than that of the most promising device under development for industry application, with a competitive sensitivity.
Additional noise reduction is achieved through the simultaneous application of spatial localisation and particle discrimination routines.The anticipated spatial resolution allows the measurement of individual (e.g.discard) devices rather than the large finished wafers evaluated by counters.
The fabrication of SDDs embedding a sample at both reduced spontaneous nucleation rate and high sensitivity is under investigation.Modifications relatively to the standard SIMPLE fabrication protocol are necessary, requiring a revision of the SDD response parameters.The application of liquid sources homogeneously distributed in the detector volume provides a benchmark for the investigation and verification of the physics underlying the detector operation.
In order to evaluate SDD noise at ground-level, the gel contamination by elements with significant (n, ) cross sections must be quantified with detection limits improved relatively to the measurements herein reported.The noise evaluation may benefit from the characterisation of the neutron environment at the SDD location.
In the final phase of the project, samples will be measured in an underground facility for the qualification of the methodology.The neutron background in the GESA room of LSBB has been characterised and is known to be, together with that from 's, appropriately low to conduct the experiment.
Figure 1 .
Figure 1.Schematic view of the SDD (in horizontal position) with a 5-microphone arrangement for the spatial localisation of the nucleations.The inset graph represents the amplitude (A) histograms of the acoustic signals corresponding to nucleations induced by recoiling nuclei following neutron interactions (n) and alpha-induced events ( ), clearly separated by a gap.
Figure 2 .
Figure 2. Temperature dependence of the response of a 150 ml SIMPLE SDD, doped with a 1mg/ml U solution and undoped (background). | 3,011.4 | 2016-01-01T00:00:00.000 | [
"Physics",
"Engineering"
] |
Comparing the Effect Size of School Level Support on Teachers’ Technology Integration
. Teachers are expected to lead the innovative use of Information Communication and Technology (ICT) at the classroom level of context. However, research literature shows that a number of factors influence their ICT pedagogical practices. Therefore, the present study investigates the influence of school level support on teacher educators’ technology integration. A mixed method is used to collect data through three focused interviews (N= 19) and self-completion survey (N=136). The data collected is analysed both qualitatively and quantitatively. The result shows support for the model hypothesized and suggests that the ICT pedagogical practices of the teacher educators do not predict their technology integration. Also, there was evidence that the school level context influenced teachers’ ICT competence, which is necessary for successful technology integration.
Introduction
The spread of digital technologies across the world attest to the significant role that Information Communication and Technology (ICT) plays in our everyday life.Different sectors of every economy have recognized the possibilities that technology avails.In the education sector for example, ICT has the potential to reform the classroom experience towards developing students' future skill sets [1].Nevertheless, literature shows continuous discussions surrounding the relationship between the various factors influencing users, from personal characteristics to other external factors [2,3,4].While the process of successfully integrating ICT in the classroom remains a struggle, teachers are expected to play a prominent role [5].Therefore, the aim of this study is to investigate the influence of the school context on teachers' technology integration.Specifically, two research questions are answered in this study: How do the study constructs predict the teachers' technology integration?What is the influence of the school level context on these constructs?
The Theoretical Model
The Technological Pedagogical Content Knowledge (TPACK) framework developed by [6] provides a theoretical basis for understanding how teachers successfully integrate technology in their classrooms.The TPACK framework follows from [7]'s model that depicts the integration of the knowledge constructs (pedagogy and content, PCK) that teachers require to teach.Accordingly, TPACK consists of the interrelationships between and among the three primary knowledge constructs that teachers require for teaching with technology: content (CK), pedagogy (PK), and technology (TK).Although the framework also takes cognizance of the context within which the teachers' knowledge constructs are situated, context is not explicated in many TPACK related studies [8].However, some studies argue that the context within the TPACK framework is not adequately delineated nor robust [9,10].Of the context levels enumerated in a number of studies, the support from the institution or schoollevel context has been highlighted as one crucial level that directly impacts the teachers' decision to use ICT in the classroom [3,[8][9][10][11].
On this basis, the present study will compare the impact of school level support on teachers' technology integration.Four main constructs are considered in the hypothesized model of this study, namely: Technology integration, teachers' ICT competence, their knowledge for integrating technology and ICT pedagogical practices.These constructs, which are founded on the TPACK framework and previous studies are discussed next.
Teachers' Technology Integration (TTI)
The technology Integration of teachers is the focus of this study.Integration of technology has become necessary in the nowadays digital era and thus, in the learning environments, teachers are expected to effectively apply technology in their teaching of subjects.To understand this integration process for teachers, the TPACK framework was conceptualized [6] and has been applied in diverse studies [12].
Teachers' ICT Competence (TIC)
Teachers' ICT competence is one main factor necessary for successful integration of technology [13][14][15].In addition, these studies have shown the positive and direct influence of teachers' technological knowledge (TK) on their technology integration (TPACK).
Teachers' Knowledge for Integrating Technology (TKIT)
[16] define the teachers' knowledge for technology integration as a combination of TCK and TPK, an adaptation from the TPACK model.In the same study, the teachers' knowledge for integrating technology was positively associated with the technology integration.Implying therefore, that teachers who are good at integrating technology consider themselves to be flexible and highly skilled such that they can make sound pedagogical choices while selecting appropriate technologies that are suitable for their specific teaching subjects [17].
Teachers' ICT Pedagogical Practices (TIPP)
Computer or ICT experience (which results from practice with ICT tools) is positively associated with teachers' technology integration according to prior studies [15,18].In other words, teacher's ICT integration practice which involve decisions on appropriate ICT tool and frequency of use, substantially influences their technology integration [17].
Methodology
Convenience sampling technique was used in the selection of three public colleges of education from the southern part of Nigeria.Thereafter, a mixed method was applied in the collection of data from Teacher Educators (or TEs) of various classroom subjects.
Qualitative Data
First, focused interview [19] was used to collect data qualitatively, which was analysed using open, focused and theoretical coding [20].Altogether, there were nineteen TEs in the three focused interviews conducted (seven females and twelve males).For both school one and two, a group of six TEs were present while school three consisted of seven TEs.
Quantitative Data
A paper based self-completion survey was used to collect data from 136 teacher educators.Subsequently, a partial least square -structural equation modelling (PLS-SEM) approach [21,22] was used to develop the study's model depicting the relationships among the factors considered for TEs' technology integration.Consequently, the data analysis through the application of WarpPLS 6.0 software [23] provided results on the structural and measurement model.The questions used to measure the items of the constructs of the study were derived from previous on teachers' technology integration studies.Measures for teachers' technology integration, teachers' ICT competence, their knowledge for integrating technology were derived from the design by [24], which used five scale Likert (from strongly disagree to strongly agree).Measures for ICT pedagogical practices were derived from the study by [25] using a four-point scale Likert ranging from never to almost always, which evaluates how often they used ICT and for which classroom tasks.
The assessment for Common method bias (CMB) [26] among the constructs of the study using the full variance inflation factors (VIF) analysis [27] showed that they ranged between 1.07 and 3.12.Consequently, the data collected is not suggestive of CMB since the VIFs are below 3.3 threshold.
Result of Qualitative Data Analysis
In summary, the analysis of the nineteen TEs' responses show that in school one, the TEs perceived that their school was in support of their technology integration through the provision of laptops, IT support and free access to a digital library where they and their students could access relevant course information for assignment completion.In school two, the TEs complained about poor school infrastructure (e.g., no internet access) and thus, they perceived that their school did not promote technology integration.Although the school had computer laboratories, there were only a few functional computers (about 2 or 3) which could not cater for their class size.The case of school three appeared to be a mixture of the others.The TEs in school three acknowledged that previously, the school organized regular staff trainings in the use of ICT and that there were school policies in place that made such trainings a condition for obtaining job promotions.However, at the time of the interview, such traditions had waned.
Result of Quantitative Data Analysis
The Measurement Model.The reliability and validity of the constructs along with their measures are examined in the measurement model.Reliability is assessed using the Cronbach Alpha coefficient, Composite Reliability Coefficient and the ability for items to load on their theoretically assigned constructs.For reliability, values higher than 0.70 are recommended [21,22].For validity, an indicator's loading should load more strongly on its own construct than on its cross loadings and the average variance extracted should be higher than 0.50 [22].Table 1 shows that the model satisfied these conditions.The Structural Model.The Goodness of Fit [28] was 0.69, which is large in terms of the effect size [29].A summary of the study's model for each school is presented in Table 2. Common to all three schools is that TIPP was not significantly associated with the TEs' TTI.In addition, a closer inspection of the school 2 model result shows the existence of reliability and validity problems.For instance, the AVE for TIC was lower than the 0.50 benchmark (0.43); the TKIT loaded more strongly on its cross loading with TTI than on itself; the VIFs for TKIT and TTI were 4.2 and 4.4 individually; One of the items measuring the TIC construct loaded poorly.
Discussion
This study investigates the influence of the school level context on TE's technology integration by comparing the effect sizes of the main constructs of the study.Hypothetically, the study's model was supported.
In response to the first research question, both constructs of TE's ICT competence and their knowledge for integrating technology were significantly associated with their technology integration (β=0.18,p<0.05; β=0.69, p<0.001 respectively).Support for this finding is offered in previous studies [13][14][15][16] albeit, the study by [4] shows a significant but indirect influence.Surprisingly, the construct TE's ICT pedagogical practices, was not significantly associated with their technology integration and contrary result was obtained in past research [18].However, a possible explanation for the observed non-significant relationship is that, the sample consisted majorly of older TEs who are above 40 years of age and 66% having over ten years teaching experience which implies they may be less confident at determining effective ICT pedagogical practices.[4,[14][15][16] highlight similar teacher characteristics as factors both directly and indirectly influencing teachers' technology integration.
In relation to the second research question, the result shows considerable difference between the schools.School two, shows that the TEs' competence did not predict their technology integration unlike the other schools.This result suggests that the lack of school support triggers a non-significant relationship with TE's ICT competence.Past research offers credence to the fact that school support influences TEs ICT competence, readiness and their technology integration practice [1][2][3][4][9][10][11].
Limitations and future research
The generalization of the result should be made with caution as the study sample consisted of TEs of three schools situated in the southern part of Nigeria.Future research can consider impact of school support within private schools, other levels of education (e.g., universities) or system level support on teachers' technology integration.In addition, ICT pedagogical practices that are considered effective such that they actually predict the technology integration of teachers can be examined more thoroughly.
Conclusion
As developments in ICT continue to positively influence learning environments, much is expected from teachers in advancing technology integration.Using a mixed method, this paper showed that considerable difference exists on TEs' technology integration when their perception of school support is compared.Theoretically, the model of the study was proven useful, as such, the study adds to the literature on technology integration of TEs and the school level influence.The TPACK framework provided to a large extent the basis for this study.Practically, the study showed the need for TEs to align their ICT pedagogical practices to their technology integration.To fill this gap, professional development for teachers can be designed as previous studies have reiterated [4,11].
Figure 1 ,
shows the result of the hypothesized model.The regres-sion coefficients for the model are R 2 = 0.69 and Q 2 = 0.69.Two of the three exogenous variables predicted the endogenous variable in the model.
Table 1 .
Composite Reliability, Cronbach Alphas, Average Variance Extracted and Interconstruct correlations.Note: CAC = Cronbach Alphas Coefficient, CRC = Composite Reliability Coefficient, AVE = Average Variance Extracted.The off-diagonal elements depict the correlations among constructs while the bold fonts in the leading diagonals are the square roots of AVEs.
Table 2 .
Comparison of result for the schools. | 2,665.6 | 2020-01-01T00:00:00.000 | [
"Education",
"Computer Science"
] |
Lactic Acid Bacteria in Biopreservation and the Enhancement of the Functional Quality of Bread
© 2013 Muhialdin et al., licensee InTech. This is an open access chapter distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/3.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. Lactic Acid Bacteria in Biopreservation and the Enhancement of the Functional Quality of Bread
Introduction
LAB have a long history in preserving foods from spoilage microorganisms -they are commonly used in food fermentation, may produce several metabolites with beneficial health effects and, thus, are generally recognized as safe (GRAS).The increasing resistance of food spoilage microorganisms to current preservatives, the consumer's high demand for safe, minimally processed foods and the hazards associated with the use of high doses of chemical preservatives has led to the need for finding safer alternatives in food preservation.The application of LAB with the simultaneous control of factors that affect fungal growth can help to minimize food spoilage.The selection and addition of novel isolates of LAB may be the key to reducing the use of chemicals, enhancing nutrients and extend the shelf life of bakery products.In this chapter, the focus will be on the use of LAB as biopreservative agents to extend the shelf life of bakery products and the inhibition of the common spoilage fungi of bread.
Sources of LAB
LAB are found in many habitats and occur naturally in a variety of food products, such as dairy, vegetables and meat products (Carr et al., 2002), all of which are rich in the nutrients required for the fastidious metabolism of LAB (Björkroth & Holzapfel, 2003;Hammes & Hertel, 2003).Some LAB are associated with the mouth flora, intestine and vagina of mammals (Whittenbury, 1964), while others are present in fermented seafood, such as Lactobacillus plantarum (IFRPD P15) and L. reuteri (IFRPD P17), which are reported to be associated with plaa-som fermented Thai fish (Saithong et al., 2010).LAB are the most important bacteria used in the fermentation industry of dairy products, such as yogurt, cheese, sour milk and butter, and in combination with yeast are commonly used to ferment cereal products such as dough (Lavermicocca et al., 2000;Muhialdin et al., 2011a;Ryan et al., 2008).
Spoilage fungi in food
The economic losses and the health hazards of the mycotoxins produced by spoilage fungi are the main concerns of the food industry (Gray & Bemiller, 2003).According to Gerez et al., (2009) the spoilage of bakery products by fungi is more common in countries with a high humidity and temperature.Pitt and Hocking (1999) estimated that about 5-10% of food production is spoiled by the growth of yeast and fungi in food materials.Similarly, in Western Europe, the growth of the spoilage fungi of bread is estimated to reach more than 200 million Euros per year (Legan, 1993;Schnürer & Magnusson, 2005).The history conditions of the food can be a major factor in determining any fungal spoilage -for example, stored and processed foods are more sensitive to spoilage when compared with fresh and prepared foods.Aspergillus and Penicillium species are the most common spoilage fungi for many foods and feeds while Fusarium species are reported to attack the cereal grains in the field (Samson et al., 2000).
Common techniques to control spoilage fungi in bakery products
Two types of techniques/factors are commonly used to control spoilage fungi: physical ones such as drying, freeze drying, cold storage, modified atmosphere storage, irradiation, the pasteurization of packaged bread and heat treatment; and chemical ones, in general based on the use of organic acids such as propionic acid and its salts (Farkas, 2001;Legan, 1993).Heat treatment is one of the most important physical factors in controlling fungi growth and mycotoxin production, as mycotoxins are destroyed by heat, although the effectiveness of destruction is affected by the food matrix and the composition of the mycotoxin (Scott, 1984).Mycotoxins have different heat stability -for example, ochratoxin A is highly stable even at 200 ºC (Trivedi et al., 1992), aflatoxins are destroyed only at temperatures of approximately 250 ºC (Levi, 1980), while zearalenone and fumonisin require high temperatures between 150-200 ºC to be efficiently destroyed (Bennett et al., 1980).Microwaves are effective in destroying mycotoxins -the aflatoxin in peanuts is reported to be destroyed using microwaves at a power level of 1.6 kW for 16 min and at 3.2 kW for 5 min (Luter et al., 1982).Among the physical methods, a modified atmosphere and gamma irradiation are preferred to the chemical methods and they have been used successfully in grain storage (Shapira & Paster, 2000).
Chemical methods that use weak acids and salts such as propionic, sorbic and benzoic acids, are usually applied only to inhibit the growth of spoilage microorganisms.The allowable concentrations of sorbate, propionate and ethanol have a limit up to 0.2% (wt/wt), 0.3% (wt/wt) and 2% (wt/wt) respectively.The use of such low concentration may not be sufficient to prevent the growth of spoilage fungi (Dantigny et al., 2005;European Union, 1995).Propionic acid is inhibitory to fungi and Bacillus spores and has commonly been used to preserve bakery products.Its activity relies on the un-dissociated form which, at low pH, has optimum activity (Coda et al., 2008;Pattison et al., 2004).The use of propionic acid at a concentration of 4% led to the appearance of cancer-like tumours in rats and eventually led to the prohibition of the use of calcium propionate in some European countries (Pattison et al., 2004).There is a major concern with microorganisms that can develop resistance to chemical preservatives, namely food spoilage and human pathogen fungi resistant to antibiotics and chemicals additives, such as sorbic and benzoic acids (Brul & Coote, 1999;Lourens-Hattingh & Viljoen, 2001).Calcium propionate has been reported to inhibit the growth of many fungi but, after a lag phase, it stimulated the growth of resistant strains of Penicillium roqueforti (Suhr & Nielsen, 2004).Interest in natural bio-preservation from LAB has been on the rise as an alternative to chemical preservatives.
Significance of the metabolites of LAB
LAB are well known for their antifungal activity, which is related to the production of a variety of compounds including acids, alcohols, carbon dioxide, diacetyl, hydrogen peroxide, phenyllactic acid, bacteriocins and cycle peptides (Gerez et al., 2009;Lavermicocca et al., 2000;Magnusson et al., 2003;Prema et al., 2008).These compounds were added to several foods in order to conserve them from food-borne and spoilage microorganisms.Organic acids are the main product of LAB in the fermentation systems of the raw materials.The main acids produced by LAB are lactic acid and acetic acid, besides certain other acids depending upon the strain of LAB (El-Ziney, 1998).These acids will be diffused through the membrane of the target organisms in their hydrophobic un-dissociated form and then used to reduce the cytoplasmic pH and stop metabolic activities (Piard & Desmazeaud, 1991).Other factors that contribute to the preservative action of the acids are the sole effect of pH, the extent of the dissociation of the acid and the specific effect of the molecule itself on the microorganisms (Axelsson, 1998).
Bacteriocins exhibit good potential for use in the food industry and as bio-preservation agents (Ennahar et al., 1999).Bacteriocins are small, ribosomally synthesized, antimicrobial peptides or proteins that display inhibition activity toward related species, with no reports about fungal inhibition (Cotter & Ross, 2005).The notable property of LAB supernatant is the heat stability of the antifungal compounds present in it.This will promote the use of LAB supernatant and/or antifungal compounds in heat-treated foods.The supernatant of certain LAB observed to be active within a wide range of pH, starting from as low as 3 and up to 9 depending upon the strain (Muhialdin et al., 2011b).This could be considered as a major factor whereby LAB are used in food preservation when compared with the chemical preservative which are usually active at low pH between 3 and 4.5.Additionally, LAB have a broad spectrum of antifungal activity against several food spoilage and mycotoxin-producing fungi while commercial preservatives are usually used to control only one or few fungi.
Bioactive compounds as antifungal agents
Several lactobacilli species are reported to have antifungal activity (Gerez et al., 2009;Muhialdin et al., 2011b;Plockova et al., 2001;Stiles et al., 1999).The antifungal compounds consist of organic acids, reuterin, hydrogen peroxide and other peptides (Table 1).The organic acids are active at low pH and the activity relies on the un-dissociated form of the acids.Recently, interest has dramatically increased in the use of bioactive peptides produced by LAB as an antifungal agent.The use of protein-like compounds are preferred over the use of acids because their activity is present over a wide range of pH and they are heat stable compounds which are ideal for use in heat processed foods (Muhialdin et al., 2011a).
Method for determining antifungal activity
Rapid, reliable and sensitive methods for the detection of the antifungal activity of LAB becomes essential in the search for new replacements for chemical preservatives with potential industrial applications.
Dual agar overlay method
This method has been described by several authors (Magnusson & Schnürer, 2001;Ström et al., 2002;Hassan & Bullerman, 2008) and it is accurate and simple for determining the antifungal activity of LAB isolates.The method consists of inoculating the LAB cells in two 2-cm-long lines and/or small circle spots on a MRS agar surface then incubating the plates at 30 °C for 24-48 h in anaerobic jars.The plates are overlaid with 10 ml of malt extract soft agar (2% malt extract, 0.7% agar; Oxoid) containing different concentrations of the spore inoculant of 10 4 and 10 5 spore/ml.The plates are then incubated aerobically at 30 °C for 48-72 h.The inhibition activity is indicated by the clear zones around the bacterial streaks.The scale for measuring the activity can be recorded as follows: -, no activity; +, no fungal growth on 0.1 to 3% of the plate area; ++, no fungal growth on 3 to 8% of the plate area; and+++, no fungal growth on 8% of plate area.Another way to measure the activity is by recording the clear zone diameter around the isolates streak, which refers to the inhibition of the fungi growth.The dual agar overlay method is also a good method for the screening of the antifungal activity of the supernatant of LAB isolates.The supernatant can be mixed with the de Man, Rogosa and Sharpe (MRS) agar or potato dextrose agar (PDA) and poured into Petri dishes followed by a similar step, mentioned previously.The supernatant can be added to the agar before it is autoclaved in order to determine the heat stability of the antifungal compounds present in the supernatants, which is a good indicator of whether the supernatant is used in heat processed foods.
Agar well diffusion method
The well diffusion method is another approach for determining the antifungal activity of LAB, described as a simple, accurate and flexible method.It is suitable to determine the inhibition activity of LAB supernatant.A fungi numbering 10 4 -10 5 spore/ml are mixed with the selected agar and allowed to solidify.The wells can be made on a variety of agar surfaces -for example, wells are made on potato dextrose agar if the target is a fungi or on a nutrient agar if the target is a bacteria; the wells are made by using a sterilized cork borer with a diameter of 3 or 5 mm.50 µl of the same agar is added to each well in order to seal the base so as to avoid leakage.The cell-free supernatants are then added to wells in amounts of 30-80 µl and incubated at room temperature for 3-6 h in order to allow the supernatant to be diffused through the agar.The antifungal activity is recorded by measuring the clear zones' diameters around the wells.
Dry weight of biomass
The reduction of the biomass of the fungi can be a tool for determining the growth inhibition activity of the supernatant.50 ml of the supernatant is inoculated into a 250 ml flask containing the growth medium for the target fungi and then the suspension of the fungi spores is added at a concentration of 10 5 .The fungal mass is harvested on filter paper and dried in an oven at 50 °C for 2 days.The average of the fungal biomass inhibition can be calculated by comparing the weight of treated fungi with the positive control which contains the fungi and the growth medium with no supernatant.
Micro-titter 96 well plate
The method is simple, inexpensive and practical for determining antibacterial and antifungal activity.The supernatant of LAB is placed into the wells of 190 µl and inoculated with 10 µl of a conidial suspension containing about 10 4 -10 5 spore/ml.The plates are then incubated at 25-30 °C.The control is a conidial suspension placed in the wells in equal amounts without the addition of the LAB supernatant.Fungal growth is observed by the naked eye and determined by measuring the optical density at 560-580 nm, starting from 0 h and repeated every 24 h with a spectrophotometer.The result can be obtained by comparing the OD readings of the control with the treated wells.The method is appropriate for evaluating the MIC, heat stability, enzyme activity and effects of pH for the LAB supernatant.
Shelf life
Traditionally, chemical preservatives and fungicides are used to inhibit fungal growth but concerns about environmental pollution and consumer health, along with problems of microbial resistance, favour the demand for alternative methods in controlling the growth of fungi (Druvefors et al., 2005).The shelf life of bread has been reported to be extended when certain LAB strains were added to bread formulations (Muhialdin et al., 2011a;Ogunbanwo et al., 2008;Rizzello et al., 2010;Ryan et al., 2011) (Table 2).The use of safe microbes in bread to extend the shelf life of the product is a great research area.Since LAB isolates are safe for use in foods, they are a significant alternative to chemical preservatives.Several researchers in the area of the bakery industry have successfully added LAB to dough and these strains grew well, producing the desired antifungal compounds in the dough.
Various fungi isolated from bakeries were inhibited by L. plantarum (LB1) and L. rossiae (LB5) isolated from raw wheat germ.Organic acids and peptides synthesized during fermentation were responsible for the antifungal activity; formic acid had the highest inhibition activity (Rizzello et al., 2011).However, the inhibitory compounds characterized were different, depending upon the LAB strains and flour type used.Dal Bello et al., (2007) characterized lactic acid, phenyllactic acid (PLA), cyclic dipeptides cyclo (L-Leu-L-Pro) and cyclo (L-Phe-L-Pro) produced by L. plantarum FST 1.7 and found them to inhibit the growth of Fusarium spp. in wheat bread.Ryan et al., (2008) reduced the use of calcium propionate from 3000 ppm to 1000 ppm when using sourdough fermented with L. plantarum FST 1.7 (LP 1.7) and L. plantarum FST 1.9 (LP 1.9), in which the growth of A. niger, F. culmorum and P.
expansum was delayed for over six days while the growth of P. roqueforti appeared after three days of incubation at 30 °C.L. plantarum VTT E-78076.Pediococcus pentosaceus VTT E-90390 was reported to inhibit the growth of rope-forming Bacillus subtilis and Bacillus licheniformis in laboratory conditions and in the bread when the selected strains were inoculated to sourdough and subsequently 20-30 g of the inoculated sourdough was added to 100 g of wheat dough (Katina et al., 2002).Lavermicocca et al. (2000) found that L.
Flavour
Flavour is one of the most valued sensory attributes in bread -volatile and non-volatile compounds produced during the fermentation of dough contribute to bread's flavour.Reports show that the fermentation of dough with LAB can enhance the aroma and flavour (Ryan et al., 2011;Muhialdin et al., 2011a).The growth of fungi is responsible for the formation of off-flavours and the production of mycotoxins; adding LAB to dough can prevent the growth of fungi and enhance the flavour of bread.The produced compound plays an important role for any technological application to enhance the flavour, such as diacetyl which gives a buttery flavour.Sourness in white bread indicates spoilage in contrast to the sourness of sourdough bread; for this reason, the search for new LAB for application in white bread becomes essential.Finding a new LAB strain that produces less acid and does not drop the pH below 4 will mark a good strategy for resolving such an issue.The addition of L. paracasi D5 and L. fermentum Te007 in the production of white bread resulted in an improved aroma and a pleasant caramel-like flavour in the baked bread itself (Muhialdin et al., 2011a).
Quality and acceptability
The quality of bread produced with LAB as a starter culture was reported to improve the texture and the quality of bread by increasing the air cells (Coda et al., 2008;Katina et al., 2002;Lavermicocca et al., 2000).Baker's yeast -also referred to as 'baking yeast' (Saccharomyces cerevisiae) -has the ability to ferment different carbohydrates and produce CO2; the most important factor involving baking yeast in bread manufacturing is to leaven the dough during the bread's preparation.The presence of antimicrobials in the dough is used to inhibit the growth of spoilage microorganisms that can affect the growth of the baker's yeast and delay the fermentation of dough, thereby resulting in economic losses to the bakery industry (Pattison & von Holy, 2001).Baking yeast is a excellent producer of the necessary flavour and aroma compounds from the products of secondary metabolism (Evans 1990).Pattison & von Holy (2001) found that the presence of propionic salts reduced the baking yeast activity by up to 34.4% in an in vitro study carried out using several natural antimicrobials with positive control calcium propionate.In comparison, lactic acid and acetic acid displayed slight effects on the activity reduction of the yeast compared with the positive control.Baking yeast and lactic acid bacteria commonly have live symbiotically in the natural ecosystem of fermenting food and beverages (Kenns et al., 1991).The volume of the dough was increased by adding sourdough containing L. amylovorus DSM 19280 when compared with chemical acidification (Ryan et al., 2011).Rizzello et al. (2010) reported the improvement of bread texture properties and the delaying of the staling of the bread because of the anti-staling effect produced by LAB and the synthesis of antifungal compounds.As mentioned previously, S. cerevisiae is responsible of leaving the dough and giving the most desirable texture to the bread.
The key role in achieving the optimum growth and activity of the bakery yeast is played by selecting a LAB that does not exhibit inhibition activity against the bakery yeast.Before choosing the LAB to be added to the dough as a co-starter, a simple experiment can be conducted in order to examine the tolerance of the bread yeast to the selected LAB strain.In a test tube mix of 10 ml water, 5 g of white flour, the LAB strain and baking yeast, we incubate and observe the production of gas at the top of the tube, which is a good indicator of the yeast activity.Ogunbanwo et al. (2008) isolated LAB from retted cassava and studied the effects of lactic acid bacteria as a starter co-culture in combination with S. cerevisiae in order to produce cassava-wheat bread.The improvement in the nutritional contents, physical properties and the extension of the shelf life were reported.Bread produced using L. acidophilus and L. brevis had the highest acceptability on average in relation to the bread produced with other strains of LAB.The use of LAB in bread in terms of improving the quality of wheat bread, bread volume and crumb structure has been reported (Clarke et al., 2002;Zannini et al., 2009).
Enhancement of a specific nutrient
LAB fermentation in dough has been approved for enhancing the nutritional value and digestibility of bread.Vitamin B, organic acids and the free amino acids produced through the fermentation of LAB can enhance the nutrients' presence in bread.The human body cannot synthesize B-group vitamins and this is why the body needs an external source of the vitamins.Certain LAB has been proven to synthesize B-group vitamins during the fermentation of foods; at the same time, LAB are considered to be the perfect vehicle for delivering the vitamins to the human body.
There are reports about the production of B-group vitamins by LAB isolates.Keuth and Bisping (1993) described the production of Riboflavin (Vitamin B 2) by Streptococcus and Enterococcus isolated from tempeh (Indonesian fermented food).Folates were observed to be produced by L. plantarum in low amounts (Sybesma et al., 2003).Vitamin B 12 (Cobalamin) was also produced by L. reuteri as well as the other groups of vitamin B (Santos et al., 2008).LAB enzymatic activity by proteases that take place during dough fermentation will release small peptides and free amino acids, which are considered to be important nutrients that should be present in bread in high quantities (Thiele et al., 2002).Essential amino acids, including lysine, threonine, phenylalanine and valine were reported to be produced by LAB (Gerez et al., 2006).The enzymes produced by LAB including amylases, proteases, phytases and lipases improve the food quality through the hydrolysis of polysaccharides, proteins, phytates and lipids.Anti-nutrients such as phytic acid and tannins can be reduced by LAB fermentation in food, leading to increased sensory properties of the bread (Chelule et al., 2010).The growth of fungi in food materials can cause the synthesis of allergenic spores and hazardous mycotoxins, which will lead to the reduction of the nutritional value of food stuffs.Adding 4% of fermented sourdough to the white wheat flour improved the texture and physical sensation of the bread.Furthermore, it enhanced the free amino acids, protein digestibility, phytase and antioxidant activities (Rizzello et al., 2010).
Starter cultures for the bread industry
Lactic acid bacteria were reported as being used as a starter culture or co-culture in the bread industry with success in terms of survivability in dough (Lavermicocca et al., 2000;Rezzillo et al., 2011).The use of lactic acid bacteria as an antifungal agent or as a starter culture for bakery and processed foods can solve two global issues; firstly, it can extend the shelf life of the food products, which will reduce their cost and the need for low temperatures, secondly, it will satisfy the high demand of modern consumers for high quality food that is free of chemicals.Above all, the product must be safe with an extended shelf life and good sensory properties.
Production of LAB cells and inhibitory compounds 10.1. Growth medium
The growth of LAB and the production of antifungal compounds are largely affected by the food matrix itself (Helander, 1997).Most of the studies regarding the antifungal activity of LAB were done using the universal MRS agar.As demonstrated earlier, there are few studies that evaluate the ability of LAB isolates to produce the active compounds in non-defined media as well as few in situ studies.The challenge for the food industry is the need for the high production of biomass and the bioactive compounds using an inexpensive fermentation growth medium.A defined medium is all well and necessary for laboratory screening purposes but it is not suitable for heavy industrial plant.The question here is whether the selected LAB can produce the biomass and maintain the antifungal activity.In our laboratory, L. fermentum Te007, Pediococcus pentosaceus Te010, L.
pentosus G004 and L. paracasi D5 were used to ferment white bread dough and they maintained the antifungal activity, as detected using MRS agar, indicating that these isolates produced the antifungal compounds in the bread dough (Muhialdin et al., 2011a).
Pediococcus pentosaceus Te010 was further investigated for its ability to grow in formulated media from plant extracts supplemented with the basic growth needs of LAB, such as vitamins, carbohydrates, nitrogen sources and salts.The results indicated that the selected isolate was able to grow in the formulated media and maintain the production of the antifungal activity but, unfortunately, the compounds have not yet been characterized (unpublished data).
Growth conditions
The growth conditions of any microbe are the key to success during the fermentation process.As for LAB, the generally optimum temperature for growth is 37 °C for 48 h in anaerobic conditions.This is not exactly what can be applied for the production of antagonistic fungal inhibitor compounds.Some of the LAB are psychrophilic and prefer low temperatures for their growth while others are thermophilic and prefer high temperatures for their growth.This should be considered as a significant factor because the optimum growth temperature has a significant impact on the production of antifungal compounds.
As well as temperature, the incubation time has a significant effect on the production of antifungal compounds with respect to the availability of nutrients in the growth medium and the production of primary or secondary metabolites.
Future research
The high demand by consumers for foods free of chemical preservatives has led to increasing amounts of research to provide alternatives for these chemicals.LAB provides technologically practicable alternatives for the replacement of chemical preservatives.The achievement of selecting LAB as starter cultures or co-cultures in fermentation processes can improve the desired properties of bread, at the same time providing consumers with new chemical-free foods.There is a need to study the interaction between the food matrix and the kinetics of the starter culture of LAB in bread; such studies will contribute to the bread industry by increasing the yield of the antifungal and nutritional compounds produced by LAB.Besides using the LAB cells in bread formulations, the use of the supernatant of LAB should be considered, especially the supernatant of LAB that are grown in non-conventional media such as plant extract and other cheap materials.
Additional studies on the contribution of bioactive molecules to the quality and shelf life of foods will surely widen the use of LAB strains as a novel bio-control strategy in bakery products.
Conclusion
LAB can be used as a starter culture or a co-culture in the bread industry to enhance the sensory properties of bread and extend the shelf life.The nutritional value of the bread is enhanced due to the production of free amino acids, organic acids and a variety of Group-B vitamins.The antifungal compounds produced by LAB are important for the food industry for replacing or reducing the use of chemical preservatives.Several methods have been developed to determine the antifungal activity of the cells and the free cell supernatant.Natural sources of food preservatives -especially LAB -are important and reflect one possibility for fulfilling the needs of modern consumers of bakery products that are free of chemicals.Challenges are evident in finding new and novel isolates of LAB that can be applied in bread and which do not affect the activity of the yeast or inhibit their growth.Future works should consider the use of the LAB supernatant as well as the cells because the active compounds can be present in the supernatant.Inexpensive media are also important for high-scale industry, especially the use of plant extracts that are rich in carbohydrates and which can be supplied in bulk over the course of the year.
Table 1 .
observed that sourdough made with L. amylovorus DSM 19280 had a longer shelf life compared with bread produced with calcium propionate.The selected strain inhibited the growth of Fusarium culmorum FST4.05,Aspergillus niger FST4.21,Penicillium expansum FST4.22,Penicillium roqueforti FST4.11 and L. amylovorus DSM 19280 and produced seventeen antifungal compounds.Lactic Acid Bacteria in Biopreservation and the Enhancement of the Functional Quality of Bread 159 Antifungal compounds produced by lactic acid bacteria and their target fungi
Table 2 .
Delay of the appearance of fungal growth on bread with added lactic acid bacteria cells plantarum 21B inhibited the bread spoilage fungi Aspergillus, Fusarium, Penicillium and Eurotium; the active compounds were phenyllactic and 4-hydroxyphenyllactic acids.The growth of Aspergillus niger appeared after two days in the control sample while L. plantarum 21B delayed the growth of the stated fungi for seven days at 20 °C. | 6,399.4 | 2013-01-30T00:00:00.000 | [
"Biology"
] |
Tuning the Biological Activity of Camphorimine Complexes through Metal Selection
The cytotoxic activity of four sets of camphorimine complexes based on the Cu(I), Cu(II), Ag(I), and Au(I) metal sites were assessed against the cisplatin-sensitive A2780 and OVCAR3 ovarian cancer cells. The results showed that the gold complexes were ca. one order of magnitude more active than the silver complexes, which in turn were ca. one order of magnitude more active than the copper complexes. An important finding was that the cytotoxic activity of the Ag(I) and Au(I) camphorimine complexes was higher than that of cisplatin. Another relevant aspect was that the camphorimine complexes did not interact significantly with DNA, in contrast with cisplatin. The cytotoxic activity of the camphorimine complexes displayed a direct relationship with the cellular uptake by OVCAR3 cells, as ascertained by PIXE (particle-induced X-ray emission). The levels of ROS (reactive oxygen species) formation exhibited an inverse relationship with the reduction potentials for the complexes with the same metal, as assessed by cyclic voltammetry. In order to gain insight into the toxicity of the complexes, their cytotoxicity toward nontumoral cells (HDF and V79 fibroblasts) was evaluated. The in vivo cytotoxicity of complex 5 using the nematode Caenorhabditis elegans was also assessed. The silver camphorimine complexes displayed the highest selectivity coefficients (activity vs. toxicity).
Introduction
Cancer is a leading cause of death worldwide, representing a serious health problem to human societies. Despite significant advances, cancer diagnosis and treatment remain major challenges [1]. Conventional treatment approaches include surgery, radiation therapy, and chemotherapy, used as single treatments or in combination. However, the success of any treatment depends on the type of cancer, its location, and its progression stage [2,3].
Metal-based compounds have been largely used in the therapeutic field due to their unique properties, including their ability to easily undergo redox reactions, variable coordination modes, and reactivity toward organic substrates [4]. Since the discovery of cisplatin, the toxicity of the most promising complex against the nematode C. elegans was also evaluated to gain further insights into the use of these complexes on a living organism.
Results
Three sets of complexes based on copper, silver, and gold metal sites were synthesized using camphorimine ligands of the mono-(A; OC6H14NY: Y= C6H5 ( 1 A); C6H4NH2 ( 2 A)) and bicamphor (B; (OC6H14N(μ-C6H4)NC6H14O)) types ( Figure 1). The electronic and steric characteristics of the monocamphor complexes were tuned through the imine substituent (Y) at the camphor ligands ( 1 A, 2 A). The new complexes 2, 4, and 8 were fully characterized by conventional techniques (NMR, FTIR, and elemental analysis). No structural characterization by X-ray analysis was achieved due to the inability to obtain suitable crystals. However, the structural characterization of related camphorimine complexes showed that coordination to the metal typically involved the nitrogen atom of the imine group [23].
Cytotoxic Activity
The cytotoxic properties of the camphorimine complexes were evaluated using the MTT assay toward the cisplatin-sensitive ovarian cancer cells A2780 and OVCAR3, as well as the normal HDF and V79 fibroblasts. The overall observation was that the copper complexes exhibited lower anticancer activity than the silver and gold complexes ( Table 1), regardless of the oxidation state of the copper site Cu(I) (1,3) or Cu(II) (2,4), or the mono-(1, 2, 4) or bicamphor (3) characteristic of the camphorimine ligands. Apparently, the Cu(II) complexes (2, 4) displayed lower cytotoxicity than Cu(I) complexes (1, 3) toward normal cells (V79 and HDF). The electronic and steric characteristics of the monocamphor complexes were tuned through the imine substituent (Y) at the camphor ligands ( 1 A, 2 A). The new complexes 2, 4, and 8 were fully characterized by conventional techniques (NMR, FTIR, and elemental analysis). No structural characterization by X-ray analysis was achieved due to the inability to obtain suitable crystals. However, the structural characterization of related camphorimine complexes showed that coordination to the metal typically involved the nitrogen atom of the imine group [23].
Cytotoxic Activity
The cytotoxic properties of the camphorimine complexes were evaluated using the MTT assay toward the cisplatin-sensitive ovarian cancer cells A2780 and OVCAR3, as well as the normal HDF and V79 fibroblasts. The overall observation was that the copper complexes exhibited lower anticancer activity than the silver and gold complexes ( Table 1), regardless of the oxidation state of the copper site Cu(I) (1,3) or Cu(II) (2,4), or the mono-(1, 2, 4) or bicamphor (3) characteristic of the camphorimine ligands. Apparently, the Cu(II) complexes (2, 4) displayed lower cytotoxicity than Cu(I) complexes (1, 3) toward normal cells (V79 and HDF).
The gold complexes (8,9) displayed IC 50 values ca. two orders of magnitude lower than the copper complexes (Table 1) for cancer cells (A2780 and OVCAR3) or normal cells (HDF and V79 fibroblasts), with a slightly higher selectivity (SI). These results indicate a better anticancer performance of the gold compared to the copper complexes. However, among the camphorimine complexes under study (Cu, Ag, and Au), the silver complexes displayed the most promising results. Although their IC 50 values toward cancer cells were higher than those of the gold complexes, they exhibited a very low toxicity toward normal cells and a high selectivity (SI) toward A2780 and OVCAR3 cancer cells (Table 1), which is a highly relevant aspect concerning biological applications.
A closer look into the cytotoxic activity vs. the characteristics of the silver complexes suggested that the lipophilicity of the ligand and the geometry of the complex were non-innocent parameters concerning their cytotoxic activity. Although further results are necessary to support the observation, according to the lipophilicity data (partition coefficient in octanol/water predicted using ACDC software) for complexes 5 ( 1 A, 2.94 ± 0.58) and 7 ( 2 A, 2.25 ± 0.59), an increase in the lipophilicity enhanced the anticancer selectivity. A direct relationship between the antimicrobial activity of the silver camphorimine complexes and their lipophilicity was previously reported [28]. using Bu 4 NBF 4 /CH 3 CN as electrolyte. c SI = selectivity index = IC50(HDF) IC50(OVCAR3) > 100, which indicates that, at 100 µM, the cellular viability (% control) was higher than 80% and could not be determined with the GraphPad prism software. d E red 1/2 [28].
The camphorimine ligands by themselves displayed no cytotoxic activity, as assessed under similar experimental conditions (>100 µM, data not shown).
The IC 50 values measured for each complex (Table 1) demonstrate that they exhibited similar cytotoxicity toward the two ovarian cancer cell lines. Therefore, the subsequent studies were performed with the OVCAR3 cells.
For comparative purposes, the activity of salt precursors CuCl and CuCl 2 , AgNO 3 and Ag(CH 3 COO), and KAu(CN) 2 , was evaluated using the OVCAR3 cells, and the respective IC 50 values were calculated (Table 1). With the exception of complexes 4 (Cu(II)) and 7 (Ag(I)), all the other complexes had lower IC 50 values than the corresponding metal precursors.
The cytotoxic activity of the reference drug cisplatin was evaluated in both ovarian cancer cells, using the same experimental conditions. The IC 50 values found at 24 h incubation were higher than those found for the silver and gold complexes, 21 ± 5.0 µM and 13 ± 4.7 µM for the A2780 and the OVCAR3 cells, respectively.
The cytotoxicity against the noncancer cell lines was determined to calculate the selectivity index (SI value), a parameter used to express a compound's in vitro efficacy. The cytotoxicity screening was conducted using two normal fibroblasts cell lines to obtain the selectivity index. As can be observed from Table 1, the IC 50 values obtained for the two cell lines differed, particularly for copper complex 1 and silver complexes 6 and 7. Therefore, the HDF human cell line was selected for the calculation of the SI values.
Results were analyzed on the basis of the assumption that an SI value <2 indicates general toxicity of a compound, while an SI value ≥10 indicates that the compound has potential to be further investigated as a therapeutic drug [29]. The IC 50 values obtained for HDF were compared to those obtained for OVCAR3 (Table 1). We found that the majority of the compounds had SI values higher than 2, with the copper complexes being less selective. The silver complexes were more selective, particularly complex 5, that exhibited a high degree of cytotoxic selectivity (SI > 50).
Complex Stability in Solution
Since biological studies are carried out in aqueous media at physiological pH, it is necessary to ensure that the complexes do not precipitate in the aqueous milieu and that they are stable on the timescale of the studies. The stability in cellular medium of the complexes was evaluated for 48 h, using UV/Vis spectroscopy [30]. The absorption spectrum was recorded for each complex dissolved in (a) 100% DMSO, (b) colorless DMEM with 1% DMSO, and (c) colorless DMEM with 1% DMSO + 10% FBS [30]. For the copper complexes, the results demonstrated a depletion of intensity in the characteristic peaks of the spectrum with the addition of DMEM and FBS. The disappearance of the initial absorption band between 200 and 300 nm for the copper complexes ( Figure 2) suggests the occurrence of some degradation during the study (48 h), slightly lower in the case of complex 1. The Ag(I) and Au(I) complexes were found to be more stable than the copper complexes, as confirmed by the maintenance of their absorption bands between 300 and 400 nm (in the three different compositions and with temporal evolution; Figures 3 and 4).
The results indicate that these complexes maintained their original form in solution, even after 48 h incubation time. As low concentrations were used in the biological studies, we expect that both the stability and the solubility were not impaired.
Complex-DNA Interaction
The obtained results show that the copper complexes were less cytotoxic and less stable in culture medium. Therefore, we focused our studies mostly on the silver (5 and 7) and gold complexes (8 and 9) having the monocamphor ligands 1 A and 2 A, respectively. Complex 1 was also included for comparison. We evaluated the complexes' ability to interact with DNA, by visualizing in vitro conformational changes in ΦX174 supercoiled DNA using agarose gel electrophoresis assays [30]. As shown in Figure 5, none of the complexes led to changes in the electrophoretic mobility of φX174 DNA. Consequently, it is possible to conclude that none of them interacted significantly with DNA molecules. These results strongly suggest that their cytotoxicity was mediated by a mechanism of action distinct from that of cisplatin, which was previously shown to bind to DNA and induce extensive electrophoretic mobility changes in DNA [30]. The cytotoxicity against the noncancer cell lines was determined to calculate the selectivity index (SI value), a parameter used to express a compound's in vitro efficacy. The cytotoxicity screening was conducted using two normal fibroblasts cell lines to obtain the selectivity index. As can be observed from Table 1, the IC50 values obtained for the two cell lines differed, particularly for copper complex 1 and silver complexes 6 and 7. Therefore, the HDF human cell line was selected for the calculation of the SI values.
Results were analyzed on the basis of the assumption that an SI value <2 indicates general toxicity of a compound, while an SI value ≥10 indicates that the compound has potential to be further investigated as a therapeutic drug [29]. The IC50 values obtained for HDF were compared to those obtained for OVCAR3 (Table 1). We found that the majority of the compounds had SI values higher than 2, with the copper complexes being less selective. The silver complexes were more selective, particularly complex 5, that exhibited a high degree of cytotoxic selectivity (SI > 50).
Complex Stability in Solution
Since biological studies are carried out in aqueous media at physiological pH, it is necessary to ensure that the complexes do not precipitate in the aqueous milieu and that they are stable on the timescale of the studies. The stability in cellular medium of the complexes was evaluated for 48 h, using UV/Vis spectroscopy [30]. The absorption spectrum was recorded for each complex dissolved in (a) 100% DMSO, (b) colorless DMEM with 1% DMSO, and (c) colorless DMEM with 1% DMSO + 10% FBS [30]. For the copper complexes, the results demonstrated a depletion of intensity in the characteristic peaks of the spectrum with the addition of DMEM and FBS. The disappearance of the initial absorption band between 200 and 300 nm for the copper complexes ( Figure 2) suggests the occurrence of some degradation during the study (48 h), slightly lower in the case of complex 1. The Ag(I) and Au(I) complexes were found to be more stable than the copper complexes, as confirmed by the maintenance of their absorption bands between 300 and 400 nm (in the three different compositions and with temporal evolution; Figures 3 and 4). The results indicate that these complexes maintained their original form in solution, even after 48 h incubation time. As low concentrations were used in the biological studies, we expect that both the stability and the solubility were not impaired. DNA using agarose gel electrophoresis assays [30]. As shown in Figure 5, none of the complexes led to changes in the electrophoretic mobility of ϕX174 DNA. Consequently, it is possible to conclude that none of them interacted significantly with DNA molecules. These results strongly suggest that their cytotoxicity was mediated by a mechanism of action distinct from that of cisplatin, which was previously shown to bind to DNA and induce extensive electrophoretic mobility changes in DNA [30].
Production of ROS
ROS are highly reactive and unstable molecular species, leading to oxidative stress and triggering the activation of cellular death mechanisms. The main species include superoxide (O2 •− ), hydrogen peroxide (H2O2), peroxynitrite (ONOO − ), and hydroxyl radical (OH • ) [31]. The preferred molecular targets are mainly proteins, DNA and mitochondrial DNA, and lipids. In particular, ROS can disrupt the lipid membrane and increase membrane fluidity and permeability [32]. A great number of new drugs are being developed to elevate ROS levels inducing oxidative stress incompatible with cell viability [33].
The molecular probe dichlorodihydrofluorescein diacetate (H2DCF-DA) was used to assess the levels of ROS, e.g., hydrogen peroxide, hydroxyl radicals, and peroxynitrite, generated in response to the effect of the complexes. This compound suffers oxidation and produces a fluorescent compound (DCF) in the presence of ROS [31]. The induction of [31]. The preferred molecular targets are mainly proteins, DNA and mitochondrial DNA, and lipids. In particular, ROS can disrupt the lipid membrane and increase membrane fluidity and permeability [32]. A great number of new drugs are being developed to elevate ROS levels inducing oxidative stress incompatible with cell viability [33].
The molecular probe dichlorodihydrofluorescein diacetate (H 2 DCF-DA) was used to assess the levels of ROS, e.g., hydrogen peroxide, hydroxyl radicals, and peroxynitrite, generated in response to the effect of the complexes. This compound suffers oxidation and produces a fluorescent compound (DCF) in the presence of ROS [31]. The induction of intracellular ROS by the compounds (metal precursors and copper, silver, and gold complexes) was analyzed at λ exc. = 492 nm 517 nm emission using a Varioskan LUX scanning multimode reader (Thermo Fisher Scientific).
As depicted in Figure 6, all the complexes induced the production of ROS (relative to untreated cells) in OVCAR3 cells. The metal precursors were much less effective in inducing ROS generation when incubated with OVCAR3 cells, according to the fluorescence intensity (fold change relative to control well below 1, Supplementary Figure S1). A correlation among the cytotoxic activity, the levels of ROS, and the redox potentials (Table 1) was apparent, since the Au(I) complexes displayed the lower reduction potentials (Table 1), the higher levels of ROS, and the higher cytotoxic activities ( Figure 6, Table 1). The Ag(I) complexes that were reduced at intermediate values between gold and copper complexes displayed intermediate IC 50 values ( Table 1) and levels of ROS ( Figure 6).
ing ROS generation when incubated with OVCAR3 cells, according to the fluorescence intensity (fold change relative to control well below 1, Supplementary Figure S1). A correlation among the cytotoxic activity, the levels of ROS, and the redox potentials (Table 1) was apparent, since the Au(I) complexes displayed the lower reduction potentials (Table 1), the higher levels of ROS, and the higher cytotoxic activities ( Figure 6, Table 1). The Ag(I) complexes that were reduced at intermediate values between gold and copper complexes displayed intermediate IC50 values (Table 1) and levels of ROS ( Figure 6). The ROS species superoxide (O2 •− ) can be detected with NBT, a cell-permeant dye that can cross the cell membrane and be reduced by intracellular free radicals (superoxide The ROS species superoxide (O 2 •− ) can be detected with NBT, a cell-permeant dye that can cross the cell membrane and be reduced by intracellular free radicals (superoxide anions) to form formazan particles, which can be detected as blue precipitates in the cells. As shown in Figure 7, complexes 1, 5, and 9 increased the ROS levels in a dose-dependent manner, with ROS production being considerably higher when compared with controls (untreated cells).
Membrane Lipid Peroxidation
Lipid peroxidation is a process in which ROS react with C=C double bonds in lipids, leading to a mixture of products such as hydroperoxides and malondialdehyde (MDA), one of the final products of polyunsaturated fatty-acid peroxidation in the cells. The MDA level is commonly known as a biomarker for lipid peroxidation [34]. anions) to form formazan particles, which can be detected as blue precipitates in the cells. As shown in Figure 7, complexes 1, 5, and 9 increased the ROS levels in a dose-dependent manner, with ROS production being considerably higher when compared with controls (untreated cells).
Membrane Lipid Peroxidation
Lipid peroxidation is a process in which ROS react with C=C double bonds in lipids, leading to a mixture of products such as hydroperoxides and malondialdehyde (MDA), one of the final products of polyunsaturated fatty-acid peroxidation in the cells. The MDA level is commonly known as a biomarker for lipid peroxidation [34].
Measurement of MDA relies on the detection of thiobarbituric acid (TBA)-reactive compounds generated from the decomposition of lipid peroxidation products. This reaction, which takes place under acidic conditions at 95 °C, results in the formation of an MDA-TBA adduct that can be quantified by its absorbance at 532 nm. Results in Table 2 show that the content of MDA in OVCAR3 cells treated with 1, 5, and 9 was low but higher than the basal level of lipid peroxides in the untreated cells (7 ± 4 pmol/10 6 cells). Additionally, the MDA levels induced by the complexes correlated with the levels of ROS, pointing the involvement of ROS production in the mechanism of action of complexes under study and, consequently, the peroxidation of the membrane lipids, as supported by the correlation between the production of ROS and the levels of lipid peroxides, particularly for complexes 5 and 9.
One of the ROS species conceivably responsible for MDA formation is superoxide (O2 •− ) formed through electron transfer to the camphorimine complexes. In processes involving metal sites, superoxide production is enhanced at potentials close to 0 V [35]. Among the camphorimine complexes under study, the silver complexes were those that better fit the potential requirements (Table 1) to enable superoxide formation and lipid peroxidation on cancer cells. The highest levels of lipid peroxides formed in the presence of camphorimine complexes were registered for cells treated with the silver complex 5 (Table 2), which was reduced at a potential close to 0 V ( = 0.12 V). Reduction of Au(I)Au(0) at 9 and Cu(I)Cu(0) at 1 occurred at much lower potentials (Table 1). Different levels of lipid peroxidation in cancer and healthy cells conceivably drove the high selectivity (SI) found for the silver camphorimine complexes (Table 1). Measurement of MDA relies on the detection of thiobarbituric acid (TBA)-reactive compounds generated from the decomposition of lipid peroxidation products. This reaction, which takes place under acidic conditions at 95 • C, results in the formation of an MDA-TBA adduct that can be quantified by its absorbance at 532 nm. Results in Table 2 show that the content of MDA in OVCAR3 cells treated with 1, 5, and 9 was low but higher than the basal level of lipid peroxides in the untreated cells (7 ± 4 pmol/10 6 cells). Additionally, the MDA levels induced by the complexes correlated with the levels of ROS, pointing the involvement of ROS production in the mechanism of action of complexes under study and, consequently, the peroxidation of the membrane lipids, as supported by the correlation between the production of ROS and the levels of lipid peroxides, particularly for complexes 5 and 9. One of the ROS species conceivably responsible for MDA formation is superoxide (O 2 •− ) formed through electron transfer to the camphorimine complexes. In processes involving metal sites, superoxide production is enhanced at potentials close to 0 V [35]. Among the camphorimine complexes under study, the silver complexes were those that better fit the potential requirements (Table 1) to enable superoxide formation and lipid peroxidation on cancer cells. The highest levels of lipid peroxides formed in the presence of camphorimine complexes were registered for cells treated with the silver complex 5 (Table 2), which was reduced at a potential close to 0 V (E red p = 0.12 V). Reduction of Au(I)→Au(0) at 9 and Cu(I)→Cu(0) at 1 occurred at much lower potentials (Table 1). Different levels of lipid peroxidation in cancer and healthy cells conceivably drove the high selectivity (SI) found for the silver camphorimine complexes (Table 1).
Caspase-3/7 Activation
Caspases are a family of cysteine proteases playing central roles in the regulation of cellular processes such as programmed cell death. Among them, caspase-3 and -7 are considered executioners of the apoptosis pathways. We investigated the possible activation of apoptotic events in OVCAR3 cells treated by camphorimine complexes 1, 5, and 9. As shown in Figure 8, the ability of the complexes to activate caspase-3/7 in vitro could be correlated with their cytotoxicity. OVCAR3 cells treated with complex 1 exhibited low caspase activation, almost comparable with the controls (untreated cells). Cells treated with complexes 5 and 9 exhibited higher caspase-3 and -7 activation levels. Interestingly, complexes 5 and 9 were also found to induce high ROS levels in OVCAR3 cells. Caspases are a family of cysteine proteases playing central roles in the regulation of cellular processes such as programmed cell death. Among them, caspase-3 and -7 are considered executioners of the apoptosis pathways. We investigated the possible activation of apoptotic events in OVCAR3 cells treated by camphorimine complexes 1, 5, and 9. As shown in Figure 8, the ability of the complexes to activate caspase-3/7 in vitro could be correlated with their cytotoxicity. OVCAR3 cells treated with complex 1 exhibited low caspase activation, almost comparable with the controls (untreated cells). Cells treated with complexes 5 and 9 exhibited higher caspase-3 and -7 activation levels. Interestingly, complexes 5 and 9 were also found to induce high ROS levels in OVCAR3 cells.
Complex Cellular Uptake
The cellular uptake is an important parameter to consider in the evaluation of the effects of metal-based complexes as therapeutic agents. To be effective, complexes must enter the cancer cells and reach their targets. The uptake of the specific metal complexes can be assessed quantitatively in bulk cell extracts using analytical techniques such as ICP-MS and PIXE. In addition, the micro-distribution of the relevant elements can be examined in single cells using the PIXE technique implemented in nuclear microscopy.
In this work, the metal intracellular concentrations were assessed by PIXE or ICP-MS in OVCAR3 cells treated with selected copper, silver, and gold complexes (1, 5, and 9). The selection was made taking into account, for each metal complex, its biological potential to be further studied as a therapeutic drug. Due to the high detection limit of PIXE for silver (300 ± 52 μg/g), the concentration of silver in the cells incubated with complex 5 was
Complex Cellular Uptake
The cellular uptake is an important parameter to consider in the evaluation of the effects of metal-based complexes as therapeutic agents. To be effective, complexes must enter the cancer cells and reach their targets. The uptake of the specific metal complexes can be assessed quantitatively in bulk cell extracts using analytical techniques such as ICP-MS and PIXE. In addition, the micro-distribution of the relevant elements can be examined in single cells using the PIXE technique implemented in nuclear microscopy.
In this work, the metal intracellular concentrations were assessed by PIXE or ICP-MS in OVCAR3 cells treated with selected copper, silver, and gold complexes (1, 5, and 9). The selection was made taking into account, for each metal complex, its biological potential to be further studied as a therapeutic drug. Due to the high detection limit of PIXE for silver (300 ± 52 µg/g), the concentration of silver in the cells incubated with complex 5 was determined by ICP-MS. Table 3 summarizes the results obtained for cells treated with complexes 1 (copper), 5 (silver), and 9 (gold). Results clearly showed an expressive uptake of silver and gold by OVCAR3 cells, whereas a limited uptake of copper was registered taking into account the concentration of the complex in the cell medium. Table 3. Total cellular uptake of OVCAR3 cells treated with complexes 1 (Cu), 5 (Ag), and 9 (Au) using the IC 50 equivalent concentrations of 70 µM (1, 24 h), 20 µM (5, 6 h), and 20 µM (9, 6 h). The results are the mean ± SD values of concentrations expressed in ng (Cu, Ag, or Au)/million OVCAR3 cells. As copper is a physiological trace element, untreated OVCAR3 cells were also included as a control sample for elemental analysis. The concentration of endogenous copper in OVCAR3 cells (12 ± 3.4 ng per million cells) was significantly lower than the concentration of copper determined in OVCAR3 cells treated with complex 1.
Complex
The distribution of copper and gold in treated cells was inspected by nuclear microscopy, making use of the PIXE technique to map and assess elemental contents in single cells. The nuclear microscopy techniques offer several advantages, regarding relatively high spatial resolution and sensitivity for a wide range of elements with physiological roles and those with pharmaceutical interest, in whole cells, while preserving most of their in vivo conditions [24].
Limited information could be obtained regarding the cellular distribution of Cu, due to its low concentration in cells. In contrast, the direct visualization of Au in cells treated with complex 9 clearly showed the uptake of Au and its profuse distribution across OVCAR3 cells, as illustrated in Figure 9. In fact, the modest uptake observed in extracts of cells treated with complex 1 is reflected in the uncharacteristic map of copper distribution across cells. In contrast, the gold uptake by cells treated with complex 9 suggests that the metal accumulated in the cell and spread in both the cytoplasm and the nucleus. The cellular localization of the metal is crucial to infer cellular targets [36]. However, further studies are needed to unravel possible targets. The reported results showed that cytotoxicity did not directly translate in higher uptake. The relevance of the correlation of metal uptake with the cytotoxic activity may be due to variations in the interaction of metal complexes with cellular components [37].
Toxicity Assessment of [Ag(NO 3 )( 1 A)] (5) Using the In Vivo Model C. elegans
The nematode C. elegans has been used as an alternative model to assess toxicity effects in mammal models. Although the experiments performed with these lower organisms need further validation, they are complementary to those performed using in vitro models, may have a good predictive power for effects in humans, and are part of the policy to reduce, refine, and replace animal testing (3R policy).
The toxicity of the complex 5 toward C. elegans was screened following the survival of synchronized L4 nematodes after exposure to different concentrations of the complex every 24 h for a total of 96 h (4 days). After 24 h of incubation in the presence of the complexes, the lethal concentration (LC 50 ) for [Ag(NO 3 )( 1 A) 2 ] was estimated as 144.7 ± 1.2 µM ( Figure 10A). The visual inspection of the cultures after 24 h of incubation revealed that the worms swam in a coordinated and fast manner for concentrations of complex 5 below 100 µM ( Figure 10C and Figure S2). For higher concentrations of the compound, the movements of the surviving worms were sluggish and uncoordinated, while some worms were even paralyzed, presenting a distinct body posture (Supplementary Figure S2). Increasing the exposure time decreased the LC 50 2 concentrations equal to or less than 10 µM, the survival rate, body size, and movement of nematodes were similar to the nematodes in the control (1% DMSO) ( Figure 10B,C). The reproductive capacity of C. elegans exposed to [Ag(NO 3 )( 1 A) 2 ] from the last larval stage (L4) to adulthood was also evaluated using different concentrations of the complex. The results show that the nematodes were able to progress into adulthood and produce eggs when exposed to concentrations of Ag(NO 3 )( 1 A) 2 not higher than 5 µM.
Toxicity Assessment of [Ag(NO3)( 1 A)] (5) Using the In Vivo Model C. elegans
The nematode C. elegans has been used as an alternative model to assess toxicity effects in mammal models. Although the experiments performed with these lower organisms need further validation, they are complementary to those performed using in vitro models, may have a good predictive power for effects in humans, and are part of the policy to reduce, refine, and replace animal testing (3R policy).
The toxicity of the complex 5 toward C. elegans was screened following the survival of synchronized L4 nematodes after exposure to different concentrations of the complex every 24 h for a total of 96 h (4 days). After 24 h of incubation in the presence of the complexes, the lethal concentration (LC50) for [Ag(NO3)( 1 A)2] was estimated as 144.7 ± 1.2 μM ( Figure 10A). The visual inspection of the cultures after 24 h of incubation revealed that the worms swam in a coordinated and fast manner for concentrations of complex 5 below 100 μM ( Figure 10C and Figure S2). For higher concentrations of the compound, the movements of the surviving worms were sluggish and uncoordinated, while some worms were even paralyzed, presenting a distinct body posture (Supplementary Figure S2). Increasing the exposure time decreased the LC50. The LC50 values at 48 h, 72 h, and 96 h were, respectively, 55.18 ± 1.13 μM, 20.74 ± 1.06 μM, and 16.12 ± 1.057 μM. Upon 72 h of exposure to Ag(NO3)( 1 A)2 concentrations equal to or less than 10 μM, the survival rate, body size, and movement of nematodes were similar to the nematodes in the control (1% DMSO) ( Figure 10B,C). The reproductive capacity of C. elegans exposed to [Ag(NO3)( 1 A)2] from the last larval stage (L4) to adulthood was also evaluated using different concentrations of the complex. The results show that the nematodes were able to progress into adulthood and produce eggs when exposed to concentrations of Ag(NO3)( 1 A)2 not higher than 5 μM.
Discussion
The current research on metal-based complexes is expected to contribute to the development of novel drugs, to increase the arsenal of available chemotherapeutics. Platinum(II) drugs like cisplatin and its analogues have been widely used in the clinic to fight against several types of cancers, acting by specifically targeting the DNA. A great percent-
Discussion
The current research on metal-based complexes is expected to contribute to the development of novel drugs, to increase the arsenal of available chemotherapeutics. Platinum(II) drugs like cisplatin and its analogues have been widely used in the clinic to fight against several types of cancers, acting by specifically targeting the DNA. A great percentage of patients undergoing chemotherapy receive a platinum drug, either alone or in combination with another chemotherapeutic drug. Despite their important role in cancer treatment, platinum drugs display systemic dose-dependent toxicity and, frequently, drug resistance, which leads to treatment failure. These limitations have strongly motivated the interest in the search for novel metal-based drugs as alternatives to cisplatin. Several metal complexes other than Pt-based have been developed and evaluated as prospective antitumor agents. For a great number of complexes, the mechanisms of action often rely on DNAindependent processes such as targeting specific cellular proteins and/or disruption of cellular signaling pathways often accompanied by oxidative stress. In addition to their ability to cause damage to lipids, proteins, and DNA, ROS are often used by eukaryotic cells as signaling molecules.
Cisplatin has been the most used drug for the treatment of ovarian cancer. These types of tumors at a later stage have a very poor prognosis and frequently acquire resistance to cisplatin. In the search for metal-based anticancer agents as alternative to cisplatin, earlier studies by Carvalho et al. showed that silver complexes with camphor ligands can exhibit interesting anticancer activities against both cisplatin-sensitive (A2780) and cisplatin-resistant (A2780cisR) ovarian cancer cells [22,23].
Results demonstrated a different cytotoxic profile for the three set of complexes. As the ligands did not induce significant cytotoxicity, it is possible to assume that the differences in cytotoxicity were not directly related to the ligands but related to the metal precursors used, particularly the silver and gold salts. The complexes presented herein highlight the importance of the metal site and the type of ligands for exploring metal-based complexes with potential biological applications.
When compared to the silver and gold camphorimine complexes, copper complexes present considerably lower cytotoxic activity, with IC 50 values in the range 40-70 µM for both ovarian cancer cell lines. This observation could be the result of poor stability of the copper complexes in cell culture media, together with their low cellular uptake, as confirmed by UV/Vis spectra and PIXE, respectively. No appreciable differences in activity were observed for Cu(I) and Cu(II) complexes with the monocamphor ( 1 A, 2 A) and bicamphor ( 1 B, 2 B) ligands (complexes 1-3), suggesting that the copper oxidation state is not a factor contributing to the complex cytotoxicity. In addition, the lower activity of these copper complexes is consistent with unchanged concentrations of cellular endogenous elements (e.g., P, K, Ca, and Zn), both in individual cells and in cell pellets.
Gold complexes also showed no appreciable differences in activity whether the complexation was with the monocamphor 1 A or 2 A ligands (8,9). However, in contrast with copper complexes, cellular uptake of gold was significantly higher, and the complexes exhibited higher cytotoxicity.
The silver nitrate (AgNO 3 ) and silver acetate (Ag(CH 3 COO)) derived complexes showed distinct patterns of activity, attributed to the characteristics of the metal core. Silver acetate is slightly less cytotoxic than silver nitrate, and the derived complexes followed the same trend (7 vs. 5).
The high activity of the binuclear complex 6 with two silver atoms per molecule strengthens the relevance of the metal in the process.
Despite the relevant activity of the silver and gold complexes, the metal ion homeostasis in OVCAR3 cells seemed to be relatively preserved, since concentrations of most physiological elements were unchanged, with the exception of potassium for complexes 5 and 9.
This change in potassium concentrations may be a consequence of the increased lipoperoxidation and membrane permeability caused by ROS.
The mechanisms of action of these complexes cannot be attributed to the interaction with the DNA, as observed by electrophoresis using single-stranded DNA. None of the complexes led to changes in the electrophoretic mobility of φX174 DNA. We, therefore, conclude that none of the complexes interact significantly with the DNA molecule, in contrast to what has been found for cisplatin.
A great number of anticancer drugs in clinical use act by inducing oxidative stress in cancer cells and consequently cell death. The generation of ROS by the copper, silver, and gold complexes in the OVCAR3 cells (mainly peroxides and superoxide) was evaluated using a fluorescent probe and the tetrazolium salt (NBT) for the investigation of the oxidative metabolism in cells. The results obtained show that the silver and gold complexes induced the generation of ROS in a dose-dependent manner. Among the copper complexes, only complex 1 followed a similar trend.
ROS can react with membrane lipids to generate lipid peroxides that are further degraded into malondialdehyde (MDA) and 4-hydroxy-2-noneal (4-HNE). These endproducts of lipid peroxidation have a cytotoxic role by promoting cell death.
After treatment of OVCAR3 cells with complexes 1, 5, and 9, the MDA content was low but higher than the basal level of lipid peroxides in the untreated OVCAR3 cells. The MDA levels correlated with the ROS levels, suggesting that the mechanism of action of complexes 1, 5, and 9 involves, at least partially, the generation of ROS.
In addition to cultured cancer and normal cells, we used the nematode C. elegans to evaluate the toxicity of the most promising complex 5 in a living organism. Results showed that the LC 50 at 24 h was 144.7 µM, well above the 2.24 µM determined for the OVCAR3 cells. These results encourage the continuation of our studies on higher organisms. Studies continue to explore the mechanism of action, particularly for complex 5 that revealed a promising biological profile and excellent selectivity, with cytotoxicity toward ovarian cancer cells while sparing normal cells.
To sum up, this study showed that metal camphorimine complexes could be prospective anticancer drugs with a better profile than cisplatin. Additionally, the study provided evidence for the biological properties of complexes being tuned by the metal, with the characteristics of the camphorimine ligands having a nonappreciable effect on the activity.
Materials and Methods
The complexes were synthesized under nitrogen using Schlenk and vacuum techniques. [43] were prepared according to reported procedures. Gold potassium dicyanide, silver nitrate, silver acetate, copper chloride, camphor, and amines were purchased from Sigma Aldrich-Merck (Darmstadt, Germany). Acetonitrile (PA-grade) was purchased from Carlo Erba (Val-de-Reuil, France), purified by conventional techniques [44] and distilled before use. The FTIR spectra were obtained from KBr pellets using a JASCO FT/IR 4100 spectrometer. The NMR spectra ( 1 H, 13 C, DEPT, HSQC, HMBC) were obtained from DMSO solutions using Bruker Avance II+ (300 or 400 MHz) spectrometers. The NMR chemical shifts are referred to TMS (δ = 0 ppm). The redox properties were studied by cyclic voltammetry using a three-compartment cell equipped with Pt wire working and secondary electrodes and interfaced with a VoltaLab PST050 equipment. The cyclic voltammograms were obtained from NBu 4 BF 4 solutions in CH 3 CN (0.10 M) as electrolyte. The potentials were measured in volts (±10 mV) versus SCE at 200 mV/s using [Fe(η 5 -C 5 H 5 ) 2 ] 0/+ (E = 0.382 V; CH 3 CN) as the internal reference. The window of potential was established using a solution of the freshly prepared electrolyte.
Complex Cytotoxicity Activity
The complex cytotoxic activity was evaluated in human ovarian cancer cells A2780 (Sigma-Aldrich, Darmstadt, Germany) and OVCAR3 (ATCC), human dermal fibroblasts (HDF, Sigma-Aldrich), and hamster lung fibroblasts V79 (ATCC). Cells were grown in RPMI 1640 medium (ovarian and V79 cells) supplemented with 10% FBS or fibroblast growth medium (HDF) and incubated at 37 • C, 5% CO 2 , in a humidified atmosphere (Heraeus, Hanau, Germany). Cell viability was assessed by the MTT assay [45,46]. In a typical experiment, cells were seeded in 96-well plates at a density of 10 4 cells/well in 200 µL medium and allowed to adhere overnight. The medium was then discarded, and 200 µL of fresh medium containing each compound in the concentration range 10 −7 -10 −4 M was added to the cells for 24 h treatment. Complexes were first dissolved in DMSO and then in medium to prepare the serial dilutions. After 24 h incubation, the solutions were aspirated, and 200 µL of MTT solution (0.5 mg/ mL) was added to each well. After 3 h, at 37 • C, the MTT solution was aspirated, and the formazan crystals formed were solubilized with DMSO. The absorbance at 570 nm was measured using a plate spectrophotometer (Power Wave Xs, Bio-Tek, Santa Clara, CA, USA). The IC 50 values were calculated from dose-response curves using the GraphPad Prism software (vs. 5.0).
Detection of ROS by H 2 DCF-DA
Intracellular ROS levels, mainly H 2 O 2 , were measured using dihydro-2 7 dichlorofluorescein diacetate (H 2 DCF-DA) [45,47]. This cell-permeable molecular probe is de-esterified within the cell and turns to highly fluorescent 2 ,7 -dichlorofluorescin (DCF) upon oxidation with ROS. For the assays, OVCAR3 cells (2 × 10 4 cells /well) were seeded in 96-well plates and left to adhere overnight. The medium was then replaced with a solution of 10 µM H 2 DCF-DA in colorless DMEM (FluoroBrite™ DMEM, Gibco ® , Waltham, MA, USA) and cells were incubated at 37 • C for 30 min. Then, the medium was aspirated, and cells were incubated with the compounds in fresh medium at selected concentrations for 1 h. DCF fluorescence was measured using a Varioskan Lux multimode microplate reader (ThermoFisher Scientific, Waltham, MA, USA) at 492 nm excitation and 517 nm emission. Results of fluorescence were expressed as the fold change in fluorescence levels compared with controls.
Generation of Superoxide Radicals (NBT Assay)
The nitro blue tetrazolium (NBT) assay was carried out adapting a previously described method [35]. This assay was used to determine the ability of cells to produce superoxide anion upon treatment with the compounds. During the treatment, NBT is reduced by superoxide anion, resulting in dark-blue formazan particles. Briefly, after incubation of OVCAR3 cells with the camphorimine ligands and corresponding complexes in medium at selected concentrations for 1 h at 37 • C, 20 µL of a 10 mg/mL NBT solution in water was added to the cell's medium, and incubation was subsequently prolonged for 1 h at 37 • C. Then, the medium was discarded, and the blue formazan particles were dissolved in 200 µL of 90% DMSO (90% DMSO:10% NaOH 0.1 N with 0.1% SDS). The resulting NBT formazan was measured at 560 nm using a plate spectrophotometer.
Lipid Peroxidation (MDA) Assay
The malondialdehyde (MDA) content in lipid extracts of OVCAR3 cells was measured using a colorimetric kit (BioVision, Milpitas, CA, USA), a method that relies on the reaction with thiobarbituric acid (TBARS assay) [48]. Briefly, OVCAR3 cells (5 × 10 5 cells/2 mL medium) were seeded in six-well plates and left to adhere for 24 h. Then, after treatment with the complexes at selected concentrations for 24 h at 37 • C, the medium was removed, the cells were washed with PBS, trypsinized, and centrifuged. The resulting cell pellet was treated following the kit recommended protocol. In brief, the cells were lysed and centrifuged, and then 200 µL of the supernatant was added to 600 µL of thiobarbituric acid (TBA) to generate the red-pink MDA-TBA adduct (TBARS) incubating the mixture for 1 h at 95 • C. Then, 200 µL aliquots were then taken and transferred to a 96-well plate for MDA quantification at 532 nm. An MDA calibration curve with MDA standards was made in parallel with the samples, using the same procedure.
Complex Interaction with DNA
The DNA binding activity of the metal complexes was assessed through their ability to alter the electrophoretic mobilities of the covalently closed circular (ccc) and open circular (oc) forms of ΦX174 supercoiled DNA as previously described [30]. Briefly, a mixture containing 200 ng of φX174 DNA (Promega, Madison, WI, USA) and different concentrations of the metal complexes was prepared. After incubation for 24 h at 37 • C in the dark, the samples were run in a 0.8% agarose gel in TAE buffer for 3 h at 90 V. The gel obtained was then stained using a 3× GelRed ® (Biotium, Fremont, CA, USA) solution in H 2 O and imaged in an AlphaImagerEP (Alpha Innotech, San Leandro, CA, USA).
Apoptosis (Caspase-3/7 Assay)
The activities of caspase-3 and -7 were assessed using the Caspase-Glo ® 3/7 assay (Promega, Madison, WI, USA). The assay kit provides a proluminescent caspase-3/7 substrate (DEVD-aminoluciferin) and luciferase in a reagent optimized for caspase-3/7 activity, luciferase activity, and cell lysis. In the presence of caspase 3/7, this substrate is cleaved, and aminoluciferin is released and consumed by luciferase, which generates a luminescent signal proportional to the caspase activity present in the cells. The assay was carried out in a 96-well plate format with the OVCAR3 cells treated with complexes 1, 5, and 9 for 24 h at concentrations below their IC 50 according to a previously described method [46]. After 24 h of incubation with the complexes, 100 µL of medium was removed from each well. Caspase 3/7 ® reagent was added in a 1:1 ratio, and the plate was shaken in an orbital shaker for 30 s at 300−500 rpm. The plate was them incubated at RT for 1.5 h, protected from light. Dichlorofluorescein (DCF) fluorescence was measured at 492 nm excitation and 517 nm emission wavelengths, using a Varioskan LUX scanning multimode reader (Thermo Fisher Scientific, Waltham, MA, USA). Results (mean ± SD) were expressed as relative luminescent units (RLU).
Complexes Cellular Uptake
The intracellular concentrations of copper, silver, and gold were determined using the particle-induced X-ray emission (PIXE) technique, installed at the Van de Graaf accelerator of Instituto Superior Técnico. For this purpose, OVCAR3 cells were incubated with complexes 1 (24 h) and 9 (6 h), at concentrations corresponding to the IC 50 , i.e., 70 µM for complex 1 and 20 µM for complex 9. The cell pellets obtained by centrifugation after washing the cells with PBS to remove the culture medium were freeze-dried and subjected to microwave-assisted acid digestion. The detailed methodology encompassing sample treatment, PIXE analysis, and concentration calculations was previously described [49]. The elemental concentrations were obtained in µg/g (of dry or wet material) and converted to µg/10 6 cells. The minimum detection limits on a dry weight basis for Cu and Au were 7.2 ± 0.5µg/g and 47 ± 2 µg/g, respectively.
Imaging Copper and Gold Distribution in Cells
OVCAR3 cells (ca. 1 × 10 6 ) were prepared for nuclear microscopy experiments by seeding the cells on a 100 nm thick silicon nitride membrane (Silson Ltd., Southam, UK), contained in six-well plates, and incubated overnight as described previously [27]. Cells were incubated with complexes 1 and 9 at concentrations corresponding to the IC 50 (45 µM for 24 h and 30 µM for 3 h, respectively). After incubation, the cells were analyzed at the nuclear microscopy facility of the C2TN/IST with a 2.0 MeV proton beam focused down to 3 × 4 µm 2 dimensions [50]. Images of the micro-distributions of Cu and Au in OVCAR3 cells, as well as minor and trace physiological elements (e.g., P, S, K, and Fe), were obtained using the PIXE multielemental technique. Images of whole OVCAR3 cells were taken with 30 × 30 µm 2 scan sizes. Acquisition of data imaging and spectral analysis was performed using OMDAQ 2007 (Oxford Microbeams Ltd., Oxford, UK) [51].
In Vivo Studies Using the Nematode Caenorhabditis elegans
The C. elegans Bristol strain N2 was used in the present work. The nematode strain, obtained from the Caenorhabditis Genetic Center, was maintained at 20 • C on Nematode Growth Medium (NGM) agar plates seeded with Escherichia coli OP50 under standard conditions and synchronized using standard protocols and as previously described [52][53][54]. L4 synchronized worms, prepared as previously described [53,54], were exposed to [Ag(NO 3 ) ( 1 A) 2 ] (5) complex final concentrations of 0, 1, 2.5, 5, 10, 25, 50, 100, 250, and 500 µM in M9 buffer (22.04 mM KH 2 PO 4 , 42.27 mM Na 2 HPO 4 , 85.56 mM NaCl, and 1 mM MgSO 4 ) supplemented with 0.2% (w/v) of dead E. coli OP50, for 96 h at 20 • C, in a final volume of 500 µL (24 wells) [55]. The total number of living and dead worms per well was assessed at 24, 48, 72, and 96 h timepoints with the aid of a Zeiss Stemi 2000-C stereomicroscope. The survival of live worms was computed by tapping the plate and counting the moving worms. Three independent experiments were performed, and each well contained 15 ± 5 L4 worms (total number of worms n = 1543). Concentration-response curves and Kaplan-Meier curves were drawn using GraphPad Prism (GraphPad Software, San Diego, CA, USA). Concentrations that resulted in the death of 50% of the tested organisms (LC 50 ) were determined by fitting the concentration response curve to a four-parameter dose-response curve. Worm images were captured using an AxioCam 503 color device coupled to the Zeiss Stemi 2000-C Stereo Microscope.
Conclusions
The cytotoxic activities of nine camphorimine complexes [Cu(I) (1, 3), Cu(II) (2, 4) Ag(I) (5, 6, 7), and Au(I) (8,9)] and their precursors [CuCl, CuCl 2 , Ag(NO 3 ), and Ag(CH 3 COO)] against A2780 and OVCAR3 ovarian cancer cells were evaluated showing that the Ag and Au complexes and their metal precursors are highly active, while the Cu complexes and their precursors presented a moderate to low activity. The characteristics of the camphorimine ligands, either of the mono-or bicamphor type, displayed just a slight effect on the cytotoxicity of the complexes, which was attributed to the lipophilic character of the camphorimine substituent ( 1 A: 2.94 ± 0.58; 2 A: C 6 H 4 NH 2 , 2.25 ± 0.59). The free camphorimine ligands did not induce appreciable cytotoxicity (IC 50 > 100 µM).
The stability of the complexes in cellular media was evaluated by UV/Vis spectroscopy, showing that the silver and gold complexes were stable in the cell medium, maintaining their original form. In contrast, the copper complexes displayed instability in the absence of FBS the medium serum supplement.
The anticancer activity of the complexes followed the order Au(I) > Ag(I) > Cu(I) ≈ Cu(II), with the silver complexes (5)(6)(7) showing the highest selectivity toward the ovarian cancer cells, as confirmed by the selectivity indices.
The cytotoxicity of complexes 1, 5, and 9 correlated well with their cellular uptake and stability. In fact, the quantification by PIXE of the metal in the OVCAR3 cells indicated only vestigial concentrations of copper (1), while reasonable levels of silver (5) and gold (9) were observed.
The herein results point to the mechanism of cell death promoted by the ability of the camphorimine complexes under study to induce different types of oxygen radicals (ROS), namely, peroxides and superoxide, which enhanced the formation of lipoperoxides, as demonstrated for selected compounds (1, 5, and 9).
The cytotoxicity of the complexes toward the nontumoral HDF and V79 fibroblasts was evaluated showing that, in general, all the complexes were more cytotoxic toward the ovarian cell lines than toward the nontumoral cells. Compared to cisplatin, the silver camphorimine complexes had a better biological profile. To get further details on the toxicity of complex 5 that displayed the highest selectivity toward the OVCAR3 ovarian cancer cells, the in vivo model C. elegans was used, showing that the complex was nontoxic for concentrations (5 µM) well above the complex IC 50 (2.24 ± 0.48 µM).
Supplementary Materials:
The following supporting information can be downloaded at https://www. mdpi.com/article/10.3390/antibiotics11081010/s1: Figure S1. Production of ROS (relative to untreated cells) in OVCAR3 cells; Figure S2. Toxicological evaluation in the C. elegans in vivo model. | 12,013.4 | 2022-07-27T00:00:00.000 | [
"Chemistry",
"Biology"
] |
Ras signaling regulates osteoprogenitor cell proliferation and bone formation
During endochondral bone development, osteoblasts are continuously differentiated from locally residing progenitor cells. However, the regulation of such endogenous osteoprogenitor cells is still poorly understood mainly due to the difficulty in identifying such cells in vivo. In this paper, we genetically labeled different cell populations of the osteoblast linage using stage-specific, tamoxifen-inducible Cre transgenic mice to investigate their responses to a proliferative stimulus. We have found that overactivation of Kras signaling in type II collagen-positive, immature osteoprogenitor cells, but not in mature osteoblasts, substantially increases the number of their descendant stromal cells and mature osteoblasts, and subsequently increases bone mass. This effect was mediated by both, the extracellular signal-regulated kinase (ERK) and phosphoinositide 3 kinase (PI3K), pathways. Thus we demonstrate that Ras signaling stimulates proliferation of immature osteoprogenitor cells to increase the number of their osteoblastic descendants in a cell-autonomous fashion.
Bones are formed and maintained by multiple types of bone cells. 1 Mineralized bone matrix is produced by osteoblasts. Osteoblasts produce a large amount of bone matrix proteins including type I collagen and osteocalcin. Osteoblasts then die or further differentiate into osteocytes that are embedded in the bone matrix. 2,3 Bone is constantly remodeled throughout life. During this process, osteoblasts are continuously differentiated from locally residing mesenchymal progenitor cells. Thus, proliferation and differentiation of the osteoblast progenitors need to be well coordinated to maintain adequate bone mass and function.
However, characteristics, kinetics and regulation of such endogenous osteoprogenitor cells are still poorly understood, primarily due to the lack of proper tools for in vivo analysis of such cells.
Recently, it has been shown that a subset of early osteoprogenitor cells show a promoter activity of the type II collagen gene (Col2a1); a lineage tracing study using Col2-creER and Cre reporter transgenic mice in which tamoxifen injection genetically labels Col2-positive cells shows that Col2-positive cells include self-renewing early osteoprogenitor cells. 4 Upon lineage commitment, osteoprogenitor cells start expressing Sp7 (Osterix; Osx). [3][4][5] In contrast, mature osteoblasts and their descendants can be exclusively labeled by the use of short promoter fragments of the type I collagen gene (Col1a1). 3,6 In this study, using stage-specific, tamoxifen-inducible Cre transgenic lines, we demonstrate that Ras signaling regulates proliferation of Col2-positive osteoprogenitor cells and controls bone mass, whereas Ras overactivation shows little effect in mature osteoblasts. Thus, the difference of responsiveness to Ras signaling discriminates differentiation stages of cells of the osteoblast lineage.
Col2-positive cells are self-renewing osteoprogenitors.
To determine the fate of osteoblast-lineage cells in different differentiation stages, we genetically labeled cells using stage-specific, tamoxifen-inducible Cre transgenic mice and R26R-tdTomato Cre reporter mice. We crossed R26R-tdTomato reporter mice 7 with Cre transgenic mice expressing tamoxifen-inducible Cre recombinase driven by a type II collagen (Col2a1) promoter (Col2-creER), 8 an osterix (Sp7; Osx) promoter (Osx-creER), 9 or a 3.2 kb-long type I collagen promoter (Col1-creER) 9 (Figure 1a). We injected a single dose of tamoxifen into pregnant mothers at E18.5 to label Cre-expressing cells. Tamoxifen induces Cre recombination and subsequently tomato expression, and thus Cre-expressing cells as of tamoxifen injection and their descendants will express tomato red fluorescent protein.
As recently shown in postnatal mice, 4 a small number of Col2-creER-expressing (Col2-positive) cells were labeled in the bone marrow 2 days after tamoxifen injection (Figures 1b and e, Supplementary Figures S1A, S1D). Over time, these cells produced a significant number of descendants that differentiated into bone stromal cells, osteoblasts and osteocytes (Figures 1c,d and f-h, Supplementary Figures S1B, S1C, S1E, S1F).
As expected, Osx-creER-expressing (Osx-positive) and Col1-creER-expressing (Col1-positive) cells were abundantly present on bone surface at early time points after tamoxifen injection. In these models, numbers and localization patterns of RFP-labeled cells appeared relatively constant during the 1-month chase period (Figures 1i-n, Supplementary Figures S1G-S1N). Col1-creER-expressing cells and their descendants are mainly osteoblasts and osteocytes (Figure 1n, Supplementary Figure S1N), whereas Osx-creER labels stromal cells, osteoblasts and osteocytes (Figure 1k, Supplementary Figure S1J). Tamoxifen injection into Osx-creER at E18.5 does not label cells in the secondary ossification center (Supplementary Figure S1H). Because the secondary ossification center is not yet formed at E18.5, this finding suggests Ras signaling regulates osteoprogenitor cell proliferation and bone formation G Papaioannou et al that Osx-positive cells and their descendants in the primary ossification center unlikely migrate into the secondary ossification center to serve as a source of osteoblasts.
Expression of an oncogenic Kras in Col2-positive cells increases the number of their descendant cells and trabecular bone mass. Mechanisms that regulate proliferation, differentiation and maintenance of endogenous osteoprogenitor cells in bone are still largely unknown. The recent finding that a self-renewing endogenous osteoprogenitor population can be genetically labeled using Col2-creER and R26R-tdTomato transgenic mice provided an opportunity to investigate the regulation of osteoprogenitor cells in vivo.
One of major regulators of cell proliferation is the Ras signaling pathway. The small GTPase, Ras, mediates the extracellular proliferative stimuli to downstream intracellular signaling molecules, including the extracellular signalregulated kinase (ERK) and phosphoinositide 3 kinase (PI3K) pathways, to stimulate cell cycle progression. Thus, we hypothesized that Ras-mediated signaling pathways might regulate osteoprogenitor cell proliferation.
In order to study the effect of overactivation of Ras signaling in osteoprogenitor cells in vivo, we expressed an active form of Kras (Kras G12D ) 10 in Col2-positive cells that were simultaneously labeled with Tomato red fluorescent protein using Col2-creER transgenic mice. Expression of Kras G12D and Tomato was induced at E18.5 by a single dose of tamoxifen injection into pregnant mothers.
Two days after tamoxifen injection, only small numbers of Tomato-expressing cells were found in the metaphyseal region of both Kras G12D A similar phenotype was observed in the humerus as in the tibia upon Kras activation in Col2-postive cells (Supplementary Figures S2C-S2D). Microcomputed tomography (μCT) analysis showed that there was a significant increase in the bone volume fraction, trabecular number and trabecular thickness and a decrease in trabecular separation (Figures 2k-p). The cortical bone parameters were unchanged. There were no overt changes in tartrate-resistant acid phosphatase (TRAP) staining (Supplementary Figures S2I-S2J), suggesting that bone-resorbing osteoclasts were not affected.
In addition to the increased bone mass, H/E staining revealed a substantial increase in the number of stromal cells between the trabeculae (Figures 3a and b Figure 4m). These stromal cells weakly expressed Col1a1 while they were negative for the mature osteoblast marker, Bglap that encodes osteocalcin (Figures 3c-f).
As expected, Kras G12D expression increased the number of cells that are positive for phosphorylated ERK1/2 (p-ERK) over time (Figures 3g-j). The PI3K pathway, another important pathway downstream of Kras, was also found activated in the stromal cells of Kras G12D mice, as demonstrated by the increase in phosphorylation of Akt (p-Akt) (Figures 3k and l).
To assess the proliferation of stromal cells, BrdU assay was performed. As expected, the BrdU labeling index of the stromal cell population in the Kras G12D mouse was increased at postnatal day P10 (Figures 3m-q).
Overactivation of Ras signaling influences cell survival. In order to test whether oncogenic Ras expression affects cell survival, a cell death assay (TUNEL assay) was performed to compare the apoptosis rate in the primary spongiosa of Kras G12D mice and wild-type mice (Supplementary Figures S3E-S3G). Although a tendency for increased apoptosis in Kras G12D mice was observed, the difference in cell death signals counted was not statistically significant (control versus mutant: 11 ± 4.6 versus 19.7 ± 4 P = 0.07, n = 3 each). This suggests that the increase in proliferation of stromal cells is the dominant mechanism for bone increase in the Kras G12D mice.
We then wanted to address the question whether the effect of Kras overexpression in Col2-positive cells was age-specific. Activating Kras at P20 in Col2-positive cells caused a similar increase in bone and stromal cells, suggesting that Col2-positive cells are continuously present and serve as MAPK and PI3K are the main signaling pathways responsible for the increase in bone with Kras activation. Kras signals mainly through the mitogen-activated protein kinase (MAPK) and PI3K pathways. 11 In order to investigate whether activation of these signaling pathways was responsible for the bone phenotype of Kras mice, we pharmacologically inhibited the ERK and PI3K pathways. We injected U0126, an inhibitor of ERK kinase (MEK), or LY294002, a PI3K inhibitor from E18.5 through P21. Both MEK inhibition (Figures 4h and k) and PI3K inhibition (Figures 4i and l) partially, but significantly, rescued the phenotype in Col2-creER; Kras G12D mice injected with tamoxifen at E18.5, as demonstrated by the decreased stromal cell number and trabecular bone (Figure 4h, i, k, l, m and comparison with figures 4g, j). In both MEK inhibition and PI3K inhibition, their downstream molecules (p-ERK and p-Akt signals respectively) were suppressed after the treatment with inhibitors ( Supplementary Figures S4A-S4F). These findings suggest that activation of both MAPK and PI3K pathways contribute to the bone phenotype of Kras G12D mice. Kras G12D expression in Col1-positive cells does not increase stromal cells or bone mass. Next, we investigated the effect of Kras activation in lineage-committed osteoblasts. We used Osx-creER and Col1-creER to target osteoblasts in early and late differentiation stages, respectively. A single dose of tamoxifen was injected into mice at E18.5 to induce expression of Kras G12D and Tomato in Osx-positive or Col1-positive cells. Kras G12D expression in Osx-positive cells caused a phenotype similar to, but somewhat milder than, that of the Col2-creER model (Figures 5a-d). Tomato-positive Osx-positive cells and their descendants were found in both bone and stromal compartments (Figures 5e-h).
In contrast, activating Kras in the Col1-positive cells caused no significant changes in bone or stromal cells at P28 (Figures 5i-l), despite that Kras G12D expression significantly increased ERK phosphorylation in osteoblasts ( Supplementary Figures S5A-S5D). Consistent with this result, there was no significant increase in tomato-positive Col1-positive cell descendants (Figures 5m-p). These results suggest that Ras activation has no stimulatory effect in differentiated osteoblasts.
Discussion
In this study, we investigated the role of Ras signaling in three different cell populations of the osteoblast lineage, that is, Col2-, Osx-and Col1-positive cells, during bone development.
Kras overactivation in Col2-positive or Osx-positive cells in bone at E18.5 led to a significant increase in number of their descendant cells and trabecular bone mass. In contrast, Kras overactivation in Col1-positive cells did not show significant effects in cell number or bone mass, suggesting that Col2-and Osx-positive cells, but not Col1-positive cells, include proliferative osteoblast progenitors. This study also demonstrates that Ras signaling is an important positive regulator of proliferation of early osteoprogenitor cells.
Multiple signaling molecules, including receptor tyrosine kinases (RTKs), 12 have been implicated in regulation of proliferation and survival of bone progenitor cells. 13,14 Kras, a small GTPase activated by RTKs, triggers downstream effector pathways, such as the MAPK (mitogen-activating protein kinase), PI3K (Phosphatidylinositol 3'-kinase) and Ral-GEF (Ras-like small GTPases) pathways, to regulate cellular functions including proliferation, differentiation and apoptosis. 15 Multiple Rasactivating molecules, including fibroblast growth factors (FGFs)/ FGF receptors, 16 epidermal growth factors (EGFs)/ EGF receptors 17 and insulin-like growth factors (IGFs) and their receptors, 18 have been implicated in regulating bone development. Ras signaling has been shown to increase stem/progenitor cell proliferation in multiple tissues. Kras activation has been shown to increase proliferation of bone marrow hematopoietic cells. [19][20][21] Additionally an oncogenic Kras increases proliferation of mouse embryonic fibroblasts 22 and facilitates selfrenewal of a subtype of alveolar stem cells. 23 Additionally Ras activation by partial loss of Nf1 gene in osteoprogenitor cells was found to increase proliferation and cause premature apoptosis. 24 In the present model apoptosis was not found significantly increased; thus, we conclude that the increase in proliferation is the dominant effect of Kras activation in osteoprogenitor cells.
However, there have been relatively limited studies that investigate the role of Ras-MAPK signaling pathway in osteoblast progenitor cells in bone in vivo. It has been shown that the ERK signaling pathway, a major downstream mediator of Ras, in mesenchymal progenitor cells promotes osteoblast differentiation and bone formation during early skeletal development. 25 Nonetheless, the proliferative effect of ERK signaling specifically in osteoprogenitor cells has not been addressed. In another study in which a dominant negative or a constitutively active MEK1 was expressed in relatively mature osteoblasts, ERK signaling stimulated osteoblast differentiation without obvious changes in proliferation. 26 The result of this study is consistent with our finding that Kras overactivation in Col1-positive mature osteoblasts had little effect in bone mass or stromal cell proliferation. In our study, we found that ERK inhibition significantly reduced the number of stromal cells in Kras G12D mice, suggesting that ERK overactivation is, at least in part, responsible for the proliferative effect of Kras G12D expression in Col2-positive osteoprogenitors. We also found that PI3K inhibition partially reduced stromal cells and partially rescued the bone phenotype caused by Kras G12D expression. Thus our study demonstrates that in addition to the ERK pathway, the PI3K pathway also plays an important role in osteoprogenitor proliferation.
To investigate the pathways downstream of Kras we injected mice with small molecule inhibitors of MEK and PI3K. With the dosage and timeframe of these experiments we did not observe significant changes in the mouse body size or condition. The wild-type control mice injected with MEK inhibitor showed no appreciable changes in bone.
Over-expression of active Kras in Col2-Cre-positive cells is not physiologically present during development, and therefore our findings do not necessarily demonstrate that endogenous Ras signaling is a physiologic regulator of osteoprogenitor cells. Nevertheless, using this system, we are able to show that Col2-positive or Osx-positive cells, but not Col1-positive cells include osteoprogenitor cells that can be discriminated by responses to Ras signaling. Additionally these experiments show that MAPK and PI3K pathways activation in the above cell populations can activate bone formation.
The loss of balance between bone formation and bone resorption results in osteoporosis. 27 Since treatment options to increase bone formation are currently limited, 28 novel bone anabolic therapies are highly desired. Our study shows that stimulating Ras signaling in endogenous osteoprogenitor cells can be a valid treatment strategy for osteoporosis.
Materials and Methods
Mice. Col2a1-creERT2, 8 Osx-creERT2, 3 Col1-creERT2, 9 and Cre-dependent Kras transgenic, loxP-stop-loxP-Kras G12D10 mice have been described elsewhere. The Cre reporter, Rosa26-loxP-stop-loxP-tdTomato mice were acquired from Jackson Laboratory (Bar Harbor, ME, USA). 7 All procedures were conducted in compliance with the Guideline for the Care and Use of Laboratory Animals approved by Massachusetts General Hospital's Institutional Animal Care and Use Committee (IACUC). Mice were in a mixed genetic background. Comparisons were made between littermates. Tamoxifen injections were given i.p. at a dose of 0.1 mg/ g to pregnant females as described elsewhere. 4 Histology. For histological analysis mice were dissected, fixed in 10% formalin overnight and decalcified in 10% EDTA for a period ranging from 1 to 14 days, depending on the age of the mice. For H/E staining, BrdU staining, immunohistochemistry and in situ hybridization, samples were paraffin processed and cut. For fluorescent reporter analysis decalcified samples were cryoprotected in 30% sucrose/ phosphate buffer saline (PBS) solutions then in 30% sucrose/PBS:OCT (1:1) solutions, each overnight at 4°C. Samples were embedded in OCT compound (TissueTek, Sakura, Torrance, CA, USA) and transferred to dry ice to solidify OCT. Samples were cryosectioned at the thickness of 15 μm using a cryostat (Leica CM1850). Nikon Eclipse E800 microscope was used for imaging. Images were merged with Spot Advanced Software.
Immunohistochemistry and in situ hybridization. Immunohistochemistry analysis for phosphorylated ERK (phospho-ERK) was performed as previously described using the Perkin Elmer TSA biotin system kit. 29 The primary antibody directed against phospho-p44/42 (ERK1/2) (Cell Signaling, Danvers, MA, USA, catalog number:#43700) was diluted 1:300 and the secondary biotinylated anti-rabbit antibody (Vector, Burlingame, CA, USA, catalog number #BA1000 ) was diluted 1:300. Anti p-Akt (Cell Signaling, catalog number #2965) antibody was diluted 1:500. ISH for type 1 collagen and osteocalcin was performed according to published protocols. 30 For all immunostaining experiments, samples from three mice per group were analyzed.
Cell proliferation assay. For BrdU labeling 50 μg of BrdU per gram of body weight was intraperitoneally injected into mice 2 h before euthanasia. BrdU was detected using the BrdU in situ staining kit (invitrogen, Waltham, MA, USA). The BrdU labeling index was calculated as the ratio of BrdU-positive nuclei over total nuclei of stromal cells of the metaphyseal tibia.
TRAP staining. Slides were deparaffinized and rehydrated. TRAP reagent consisted of 6 ml 50 mM tatrate in acetate buffer (PH 5.0), 0.5 mg Naphthol As-Mx, 50 μl N,N dimethylamide and 3 mg fast red violet LB. TRAP reagent was added for 5-10 min and once satisfactory color was observed, slides were washed with water and then with PBS. At the end the slides were mounted with water-based medium.
Cell death assay (TUNEL assay). Cell death was evaluated on sections using an in situ cell death detection kit (Roche, Branford, CT, USA) according to the manufacturer's instructions.
MicroCT analysis. A high-resolution desktop micro-tomographic imaging system (μCT40, Scanco Medical AG, Basserdorf, Switzerland) was used to assess trabecular and cortical in the proximal metaphysis and diaphysis of the tibia, respectively. Scans were acquired and analyzed as previously described. 31 Image acquisition and analysis were performed according to the JBMR guidelines for the use of μCT in rodents. 32 To assess the trabecular architecture, transverse CT slices were evaluated in a 1500 μm (150 slices) region beginning 750 μm below the proximal growth plate and extending distally. The trabecular bone region was identified by semi-manually tracing with the assistance of an auto-thresholding software algorithm. A mineral density threshold of 225 mgHA/cm 3 was used for all images to segment bone from soft tissue.
Rescue experiments-inhibitors. The MEK1 inhibitor (U0126) and the PI3K inhibitor (LY294002) were purchased from Selleckchem (Houston, TX, USA). Inhibitors were first dissolved in DMSO according to the manufacturer's instructions, then diluted into PBS, and injected daily into pregnant as well as nursing mothers intraperitoneally from E18.5 through P9.5. Subsequently, the inhibitors were injected to pups. MEK inhibitor was injected at a dose of 5 mg/kg per day. PI3K inhibitor was injected at a dose of 100 mg/kg four times a week. | 4,208.4 | 2016-10-01T00:00:00.000 | [
"Biology"
] |
Logarithmic norms and regular perturbations of differential equations
In this note we explore the concept of the logarithmic norm of a matrix and illustrate its applicability by using it to find conditions under which the convergence of solutions of regularly perturbed systems of ordinary differential equations is uniform globally in time.
Introduction
The concept of the logarithmic norm of a matrix, also known as a logarithmic derivative, or the logarithmic Lipschitz constant for nonlinear operators, was introduced independently by Dahlquist [3] and Lozinski [6], whose aim was to estimate the error of discretization in numerical analysis of differential equations, see e.g. [5,Section I.10]. This "norm" (which is not really a norm in the sense of functional analysis as it can take negative values) is a measure of the dissipativity of an operator. It has, nevertheless, many norm-like properties that allow to use the dissipative terms in the original problem to generate negative terms in the error estimates. In this way the error estimates are reduced to linear differential inequalities that reflect the structure of the original problem in a much better way than the Gronwall inequality. In particular, in many cases it yields estimates uniform in time, remedying thus one of the main drawbacks of the Gronwall inequality, namely that the constants grow exponentially in time.
It turns out that this feature of the logarithmic norm can be used to provide uniform globally in time estimates for solutions to perturbed systems of differential equations. To explain the problem, let us recall a classical regular perturbation result.
The α-neighbourhood (α > 0) of graph of x 0 (definition: the set of all points (t, x) with t ∈ J, |x−x 0 (t)| ≤ α) will be denoted by S α . Suppose there exists α > 0 such that f (t, x) is continuous and Lipschitz in x uniformly in t in S α . Then the solution x 0 (t) depends continuously on the initial values and on the right-hand side f . In other words: For every > 0, there is δ > 0 such that if g is continuous in S α and the inequalities are satisfied, then every solution z(t) of the perturbed initial value problem exists in all of J and satisfies the inequality This result does not give, however, a satisfactory answer as far as the long term dynamics is concerned. In fact, even if solutions to (1) converge as t → ∞ to, say, a stationary point, the solutions to (3) can diverge as t → ∞, or even blow-up at finite time for any δ > 0.
Example 1.2. Consider the family of Cauchy problems
Then x 0 (t) = 1, t ≥ 0, and It is clear that for > 0, x (t) blows up as t → 1 − . On the other hand, for any compact interval On the other hand, if we consider then x 0 (t) = e −t and Since We observe that, contrary to the first case, in the second case x * = 0 is the hyperbolic equilibrium of the limit problem. To simplify the discussion, we slightly modify (1) to assume that f is differentiable with respect to all variables and f (x * , 0) = 0. Then, if the Jacobian J f (x * , 0) is not singular, then the Implicit Function Theorem implies that for some 0 > 0 there is a differentiable family x * ( ), ∈ (− 0 , 0 ), of solutions to f (x * ( ), ) = 0. If, in addition, x * is a hyperbolic equilibrium, then the theorem on continuous dependence of the roots of a polynomial on its coefficients, see e.g. [8,15], shows that for sufficiently small the equilibria x * ( ) are of the same type as x * . In other words, for regularly perturbed problems (7) we have the convergence of its solutions on any finite time interval to the solution of the limit problem (with = 0). Moreover, provided the equilibria of the limit problem are hyperbolic, (7) has the same structure and the type of the equilibria, and these equilibria converge to the equilibria of the limit problem. However, this does not prove that the interval of convergence of the solutions can be extended to [t 0 , ∞). To prove this fact, some uniform estimates of x for large times would be required. The aim of this note is to show how the logarithmic norm can be used to prove such estimates.
Basic mathematical tools
As the main idea of using the logarithmic norm to error estimates consists in deriving an appropriate differential inequality for the norm of the error, we must specify in what sense that norm can be differentiated. In this section we discuss this issue as well as the solvability of relevant differential inequalities, mostly following [2, Chapter I]. Let X = R n and let · be a norm on X.
Definition 2.1. Let f : (a, b) → R be any function. The upper and lower right Dini derivatives of f at t ∈ (a, b) are defined, respectively, as Similarly, the upper and lower left Dini derivatives of f are defined, respectively, as at some t, then we say that f has right (resp. left) hand side derivative at t and denote it by f . Due to the properties of the upper and lower limits we have (10) D ± ± (f + g) = D ± ± f + g as long as g is differentiable. Clearly, the formula remains correct if g only has one side derivatives and D is the corresponding one sided Dini's derivative. We shall be concerned with the system of differential equations (11) x where t 0 ∈ (a, b).
Definition 2.2. A vector function
, then the same is true for D − z (resp. D + z) so also in these two cases we obtain the monotonicity of z, see also [17,Appendix B.I].
Remark 2.6. Following Remark 2.5, in the statement of Theorem 2.3 the inequality . Indeed, consider Then, by (10), ) and the statement of the first part of Theorem 2.3 follows. Similarly, in the second part of Theorem 2.3, the inequality D − y ≥ f (t, y) can be replaced by D + y ≥ f (t, y). Indeed, consider Then, again by (10), Thus we see that D + y(t) ≥ f (t, y) implies D − y(t) ≥ f (t, y) and the statement of the second part of Theorem 2.3 follows.
The following theorem is a consequence of the convexity of the norm.
In particular, if u is differentiable at t = t 0 , then
Logarithmic, or Lozinski's, norm
Let A be an n × n matrix. Usually we shall use real matrices but most considerations are valid also in the complex case. Let · be a norm on R n (or C n ). For a given norm · , we define the logarithmic norm of A by The existence of µ(A) is ensured by Theorem 2.7. As mentioned in Introduction, µ(A) has most properties of the norm. These properties, as well as other ones relevant to this paper, are listed for instance in [2, Section 1 of Chapter 2], or in [6,13,14]. Some of them are proved in [6], while the proofs of others are scattered among sources that are not easily accessible and thus we decided to provide them here.
Proof. a) We can write b) Similarly, by the triangle inequality for · , To prove the converse, we have
c) We have
and, letting h → 0 + , Since e tA ≤ 1 = e 0A , from the definition of the right hand derivative and its existence, we infer d dt + e tA | t=0 ≤ 0, which proves the thesis. We shall need the following lemma.
Lemma 3.4.
(i) The function A → µ(A) is Lipschitz continuous; that is, for any matrices A and B, we have (ii) For any z ∈ C, we have (17) and (16), we have and the statement follows.
One of the drawbacks of the logarithmic norm is that it strongly depends on the underlying norm, see e.g. [2, Section 1 of Chapter 2], and thus it is not directly related to the dynamical properties of (e tA ) t≥0 . More precisely, if µ(A) < 0, then (e tA ) t≥0 is an exponentially stable contractive semigroup. On the other hand, if (e tA ) t≥0 is only exponentially stable; that is, for some M ≥ 1, ω < 0 (24) e tA ≤ M e ωt for all t ≥ 0, then nothing can be said about µ(A) for a given norm · . We observe that in finite dimensional spaces the stability (24) is determined by where σ(A) is the spectrum of A, which is independent of the norm. We have, however, Theorem 3.6. For any > 0 there is a norm · (equivalent to · ) such that the logarithmic norm µ defined by · satisfies Remark 3.7. Theorem 3.6 goes back possibly to [9,10] but the proof above seems to be more elementary. On the other hand, the construction of [10] gives an inner product norm (x, P x), where P is the hermitian solution of the Lyapunov equation
Regularly perturbed systems
As mentioned in Introduction, we consider a family of Cauchy problems in D × [0, 0 ), where D ∈ R n is a open domain and 0 > 0, We denote the semiflow generated by (28) by x (t,x) and use the simplified notation x(t,x) := x 0 (t,x).
Theorem 4.1.
Assume that x * ∈ D is a stationary solution of the limit equation and the spectral bound of the Jacobian J of f (x * , 0), s(J f (x * , 0)), satisfies s(J f (x * , 0)) < 0. Further, let lim →0 +x =x ∈ D withx belonging to the domain of attraction of x * . Then uniformly on [0, ∞).
Proof.
To fix notation, let R n be normed with the l 1 norm · 1 and let · be a fixed equivalent norm on R n such that the logarithmic norm of J f (x * , 0) with respect to · satisfies µ(J f (x * , 0)) < 0, see Theorem 3.6. Let us specify for some c, C > 0, . Using (22) and the regularity of f , we find that there are δ 1 > 0, 0 < Before we proceed, we need to combine the estimates for the logarithmic norm with some estimates of the second order remainder of the expansion of f . For arbitrary u, v ∈ D, we have uniformly in . Indeed, suppressing in the notation as not relevant for the discussion, we proceed as in the classical proof of the multivariate Taylor expansion and consider the function φ = (φ 1 , . . . , φ n ), where the scalar functions φ i , 1 ≤ i ≤ n, are defined as so that φ(0) = f (v) and φ(1) = f (u). Using the Taylor expansion with the integral remainder, in the original notation we get where and Hf i is the Hessian of f i . Let us now return to the (uniform) dependence on and write down the complete estimate in vector notation. To do this, we introduce H = {H ik } 1≤i,j≤n by Ln 2 , L = sup{|∂ 2 x j x k f i (x, )|; x ∈ D, ∈ [0, 0 ), i, j, k = 1, . . . , n} and C, c were defined in (31). We see that there is δ < δ 1 such that (37) µ * + M δ ≤μ < 0 for someμ. By assumption, there is T such that for all t ≥ T we have x(t,x) ∈ B x * , δ 4 . Then, by the regular perturbation theorem, Theorem 1.1, for any 0 < η < δ 4 there is η > 0 such that for all ∈ [0, η ) and t ∈ [0, T ] we have Thus, x (T,x ) ∈ B x * , δ 2 for < η . Next, following the ideas of [1,7], we introduce a C ∞ 0 (R n ) cut-off function 0 ≤ ψ ≤ 1 that satisfies Such a function exists by [16, Lemma 1, Chapter 2, §5] and the fact that · is equivalent to the Euclidean norm used in the proof in op. cit. so that there is an Euclidean neighbourhood separating B x * , δ 2 and the exterior of B(x * , δ). Shortening notation to x(t) := x(t,x) and x (t) := x (t,x ), we consider the following modification of (28), We observe that y (t) = x (t) as long as y (τ ) − x(τ ) ≤ δ 2 for T ≤ τ ≤ t. Now, as in [5, Section I.10], we derive a differential inequality for the norm of the error e (t) = y (t) − x(t), t ≥ T . For a fixed t ≥ T , we have . Now, subtracting e (t) from both sides, dividing by h and passing to the limit as h → 0 + , we obtain, by Corollary 2.7, for any fixed t ≥ T , Next, using the definition of ψ, we estimate: (22) and (37), for t ≥ T . Since 0 >μ > µ * , we obtain the following differential inequality for the norm of the error Since scalar equations automatically are of type K, from Remark 2.6 we obtain (42) Thus, defining 3 := −μδ 2K , (38) implies that y (t) − x(t) ≤ δ 2 for any ∈ [0, 3 ) and hence, for such , y (t) = x (t). Therefore, (42) can be written as Combining (38) and (43), we obtain that for any (sufficiently small) η there is 4 < min 3 , η , η −μ K such that for all 0 < < 4 and t ∈ [0, ∞) proving the uniform convergence of x (t) to x(t) on [0, ∞).
Example 4.2.
To illustrate the result, let us consider the Ross model of malaria, as derived in [11], where I h and I v are, respectively, the numbers of infected humans and mosquitoes, H and V are, respectively, the total populations of humans and mosquitoes, b 1 is the probability of a human becoming infectious after an infectious bite, a is the rate of bites of infectious mosquitoes, γ H is the human rate of recovery, µ H is the human death rate, b 2 is the probability that a mosquito becomes infectious after an infectious bite, while γ V and µ V are, respectively, the recovery and death rates of infected mosquitoes.
Since it is assumed that the human and mosquito populations are constant, we normalize them by setting x = I h /H and y = I v /V so that (44) becomes where m = V /H. Furthermore, it is observed that human mortality is negligible on the time scale of the recovery rate. Also, in epidemiological literature it is assumed that mosquitoes remain infected practically for the whole life after becoming infectious. Thus, using µ H = γ V ≈ 0, (45) can be written as Can we say that that the dynamics described by (45) does not change, when we simplify it to (46)? To illustrate the application of Theorem 4.1, let us focus on the disease free equilibrium (0, 0). The Jacobian at this point is given by with the characteristic equation We mention that while in the epidemiological context this result is not unexpected as we dropped negative terms on the right hand side of (45) so that the solutions to (46) decay to zero faster than those of (46) mathematically, however, the result does not depend on the sign of µ H and γ V . | 3,780 | 2020-01-16T00:00:00.000 | [
"Mathematics"
] |
The Vibration Isolation Design of a Re-Entrant Negative Poisson’s Ratio Metamaterial
: An improved re-entrant negative Poisson’s ratio metamaterial based on a combination of 3D printing and machining is proposed. The improved metamaterial exhibits a superior load-carrying and vibration isolation capacity compared to its traditional counterpart. The bandgap of the proposed metamaterial can be easily tailored through various assemblies. Additionally, particle damping is introduced to enhance the diversity of bandgap design, improve structural damping performance, and achieve better vibration isolation at low and medium frequencies. An experiment and simulation were conducted to assess the static and vibration performances of the metamaterial
In the mechanical application of metamaterials, the deformation behavior, bearing capacity, and the ability to resist vibration and impact have always been the research focuses. Zhang et al. [24] investigated the influence of hierarchical structures on bandgap distribution and energy absorption efficiency, revealing significant potential in widening bandgaps and enhancing energy absorption efficiency. Li et al. [25] proposed novel facecentered cubic plate and truss micro-lattices as new types of metamaterials and found that the absorption coefficient's characteristics are fundamentally shaped by the geometric morphology of voids and cavities. The exceptional mechanical performance stems from the near-membrane stress state of the plate structures and the superior ductility and strength of the base material. Chen et al. [26] theoretically and numerically studied the dynamic behavior of triangular and hexagonal lattice cylindrical structures under constant-velocity impact. The results showed that for lattice cylindrical shells, introducing a positive density gradient can enhance early-stage energy absorption at high velocities. For lattice sandwich and the proposed metamaterial design accomplished the miniaturization concept by arranging unit cells in a multi-layer structure and possesses unique properties, such as a highly effective medium ratio and left-handed characteristics.
It is evident that metamaterials possess a higher degree of designability compared to traditional materials, and incorporating assembly techniques into metamaterial design can enhance their versatility and designability. As a class of artificially designed materials, metamaterials offer significant advantages in structural lightweight while simultaneously addressing various other performance requirements. In the aerospace applications of metamaterials, there are three main requirements that need to be met simultaneously: structural lightweight requirements, adequate strength and stiffness, and good vibration properties. Extensive research has been conducted in this area.
This work presents an assembly-based approach to design a re-entrant negative Poisson's ratio metamaterial by introducing circular rings as connecting nodes to conventional NPR metamaterials and a 300% increase in the bearing capacity of the novel structure compared to traditional structural metamaterials. The introduction of the metal pins and metal particles increases the density of the metamaterial structure, so the resonance frequencies of the overall structure will move in the low-frequency direction, and the corresponding resonant vibration amplitude may indeed be larger than that of the original structure, which can be suppressed by damping. Meanwhile, the vibration suppression bands will also move, and the vibration propagation can be suppressed by making the suppression band contain the frequency of the vibration source. The resonance frequency of the overall structure of the metamaterials can be adjusted by the mass of the particle damping, the amplitude of the resonance peak can be suppressed by the particle damping, and the damping energy consumption effect can also suppress the vibration of other frequencies.
On the other hand, in the medium-and high-frequency bands, the bandgap properties of the metamaterial can be adjusted by regulating the mode of the metamaterial cells through an increase in the particle mass or metal pins. In summary, by introducing metal pins and particle damping, the structural bandgap and the overall mode frequency can be adjusted, and vibration control can be realized. The improvement of the carrying capacity and vibration suppression capacity is conducive to the application of negative Poisson's ratio metamaterials in automotive, aerospace, and other engineering fields. The design scheme presented in this paper is expected to be applied in the design of space equipment.
In this paper, Section 2 introduces the structural characteristics and design principles of the re-entrant negative Poisson's ratio metamaterial. Section 3 presents the static mechanical performance under different assembly conditions. Section 4 investigates the bandgap characteristics of the metamaterial under different assembly conditions, along with methods for bandgap control. Additionally, particle damping is introduced to suppress low-frequency vibration, and the effect of particle damping on the bandgap characteristics is examined. Section 5 validates the vibration isolation performance of the metamaterial by using simulation and experimental methods, with a focus on the increased suppression of low-frequency vibration due to particle damping.
Geometrical Configuration of the Novel Re-Entrant Metamaterials
As shown in Figure 1, a novel NPR metamaterial (N-NPRM) is constructed by introducing a ring structure into the traditional NPR metamaterial (T-NPRM); the joint of the thin walls is replaced by the ring structure. The geometric parameters of the N-NPRM are listed in Table 1. L 1 and L 2 are the width and length of the unit cell, T is the thickness of the thin wall, θ is the angle between the thin walls, and R is the radius of the hole. The N-NPRM and T-NPRM have the same width and length of the unit cell. the thin wall, θ is the angle between the thin walls, and R is the radius of the hole. The N-NPRM and T-NPRM have the same width and length of the unit cell.
Mechanical Properties of the Proposed NPRM
The proposed NPRM is manufactured by 3D-printing technology, and made of a polymer plastic material named WEILAI 8000, which is from a company named WeNext (Shenzhen, China). The pieces at both ends are made of aluminum, the assembly pins are made of metal, and the particle damping comprises tungsten particles. The properties of the material are listed in Table 2.
A simulation and experiment were conducted to study the mechanical properties of the NPRM. The testing method is shown in Figure 2. Specifically, for the equivalent setup of particle damping in the simulation, the loose particles were considered to have no impact on the structural stiffness and to only affect the mass distribution at the locations of the connecting circular rings. Therefore, in the finite element analysis, the circular rings were separately segmented, and their material properties, except for density, were the same as that of the plastic (WL8000). The equivalent density eq ρ can be obtained using the following formula: By solving Equation (1), we obtained the following result:
Mechanical Properties of the Proposed NPRM
The proposed NPRM is manufactured by 3D-printing technology, and made of a polymer plastic material named WEILAI 8000, which is from a company named WeNext (Shenzhen, China). The pieces at both ends are made of aluminum, the assembly pins are made of metal, and the particle damping comprises tungsten particles. The properties of the material are listed in Table 2. A simulation and experiment were conducted to study the mechanical properties of the NPRM. The testing method is shown in Figure 2. Specifically, for the equivalent setup of particle damping in the simulation, the loose particles were considered to have no impact on the structural stiffness and to only affect the mass distribution at the locations of the connecting circular rings. Therefore, in the finite element analysis, the circular rings were separately segmented, and their material properties, except for density, were the same as that of the plastic (WL8000). The equivalent density ρ eq can be obtained using the following formula: where R represents the radius of the pin, T denotes the wall thickness of the NPRM, 1 ρ is the density of WL8000, 2 ρ is the density of the pin material, and h represents the thickness of the NPRM plate. The simulation of the static properties was carried out using the software ABAQUS 2018. For improving the computational efficiency, a 2D model was established, as shown in Figure 2. The element type was CPS4R, and as the thickness of the thin wall was 1.2 mm, in order to ensure the accuracy of the simulation, the maximum size of the element was 0.2 mm. The properties of the materials were set according to Table 2. The bottom aluminum block was fixed, and the force F was loaded on the middle point of the top surface of the top aluminum block.
The compressive testing of the metamaterial structure was performed using a universal testing machine in the configuration shown in Figure 2. The same loading conditions were applied in finite element simulations. The length of the simulated compression curve was set to 20 mm, starting at 0 and gradually increasing in the testing machine. The loading was stopped when the specimen exhibited failure. During the experiments, it was observed that the specimen did not reach the full compression of 20 mm before failure occurred. This behavior can be attributed to the material properties of the metamaterial and the quality of the 3D printing. By solving Equation (1), we obtained the following result: where R represents the radius of the pin, T denotes the wall thickness of the NPRM, ρ 1 is the density of WL8000, ρ 2 is the density of the pin material, and h represents the thickness of the NPRM plate. The simulation of the static properties was carried out using the software ABAQUS 2018. For improving the computational efficiency, a 2D model was established, as shown in Figure 2. The element type was CPS4R, and as the thickness of the thin wall was 1.2 mm, in order to ensure the accuracy of the simulation, the maximum size of the element was 0.2 mm. The properties of the materials were set according to Table 2. The bottom aluminum block was fixed, and the force F was loaded on the middle point of the top surface of the top aluminum block.
The compressive testing of the metamaterial structure was performed using a universal testing machine in the configuration shown in Figure 2. The same loading conditions were applied in finite element simulations. The length of the simulated compression curve was set to 20 mm, starting at 0 and gradually increasing in the testing machine. The loading was stopped when the specimen exhibited failure. During the experiments, it was observed that the specimen did not reach the full compression of 20 mm before failure occurred. This behavior can be attributed to the material properties of the metamaterial and the quality of the 3D printing.
A comparison was made between the stress-strain curve obtained from the experiment, where failure did not occur, and the simulated curve, as shown in Figure 3a. The stressstrain curve corresponds to the conventional T-NPRM structure. In Figure 3a, it can be observed that there is good agreement between the experimental and simulated data, confirming the reliability of the simulation method. And in Figure 3a, the figures A~D are the deformation shapes of the metamaterial by simulation and experiment at different strain points. Figure 3b displays the stress-strain curves for the traditional T-NPRM, N-NPRM, N-NPRM with aluminum pins, and N-NPRM with particle damping. In the graphs, it can be observed that the addition of circular rings significantly enhanced the stiffness of the NPRM structure, thereby improving the structural load-carrying capacity of the metamaterial.
The presence of metal pins increased the local stiffness at the circular ring, but since the compression deformation of the metamaterial structure was primarily governed by the deformation of the connecting walls, there was minimal change in the stress-strain curve.
Bandgap Properties of N-NPRM
The bandgap is a distinctive property of metamaterials in the field of vibration control. Therefore, in this section, the bandgap performance of T-NPRM and N-NPRM is analyzed to reveal the influence of the design parameters on the bandgap behavior. This work aims to provide a foundation for the bandgap design of the proposed metamaterials.
According to the basic equation of elastic dynamics, without the damping and body force, the propagation of elastic waves in two-dimensional periodic structures can be written as [43] In the case of N-NPRM with particle damping, a cover was added at the circular ring, with the material of the cover being the same as that of the metamaterial. This slightly increased the stiffness at the circular ring. However, the particles did not have a significant impact on the static mechanical performance of the metamaterial structure, resulting in a minimal difference between the stress-strain curves of the N-NPRM and the N-NPRM with particle damping.
Bandgap Properties of N-NPRM
The bandgap is a distinctive property of metamaterials in the field of vibration control. Therefore, in this section, the bandgap performance of T-NPRM and N-NPRM is analyzed to reveal the influence of the design parameters on the bandgap behavior. This work aims to provide a foundation for the bandgap design of the proposed metamaterials.
According to the basic equation of elastic dynamics, without the damping and body force, the propagation of elastic waves in two-dimensional periodic structures can be written as [43] ρ(r) where u is the displacement vector, which is related to the position vector r = (x, y). ..
u is a second derivative of the displacement with respect to time. ∇ = ( ∂ ∂x , ∂ ∂y ) denotes the differential operator, and ρ is the mass density. The symbols λ and µ are the Lamé constants, which can represent Young's modulus E and Poisson's ratio ν as According to the Bloch theorem, the displacement vector can be expanded as where ω and t mean the angular frequency and time, respectively. L equals √ −1, and k is the wave vector of the 2D lattice. The displacement vector u is a periodic function with the same periodicity as the periodic structure, which follows the relation u(r) = u(r + R) (6) in which R is the lattice vector. Combined with Equation (6), and considering the relationship between the node displacement vectors on the cell boundary in the space domain, Equation (5) can be rewritten as By substituting Equation (7) into Equation (3), the wave−governing equation can be transformed into the eigenvalue equation where K and M are the stiffness and mass matrices, respectively. U is the displacement column vector of all nodes.
Bandgap Analysis of the NPRM
In this section, the bandgap performance of the metamaterials is calculated using the multi-physics software COMSOL 5.6. To ensure computational accuracy, the minimum wavelength is generally required to contain 10 elements, and thus, the maximum element size was set as 0.2 mm. Three periodic boundaries were set; the unit cell can be seen in Figure 4a. The properties of the materials were set according to Table 2.
The bandgap performances of both T-NPRM and N-NPRM were analyzed to find the factors influencing the distribution and the width of the bandgap. This work will further help in establishing methods for bandgap tuning.
As shown in Figure 4a, the unit cell of the NPRM was used for the bandgap calculations. The Brillouin zone of the periodic lattices, which represents the reciprocal space of the unit cell, is shown in Figure 4b size was set as 0.2 mm. Three periodic boundaries were set; the unit cell can be seen in Figure 4a. The properties of the materials were set according to Table 2.
The bandgap performances of both T-NPRM and N-NPRM were analyzed to find the factors influencing the distribution and the width of the bandgap. This work will further help in establishing methods for bandgap tuning.
As shown in Figure 4a, the unit cell of the NPRM was used for the bandgap calculations. The Brillouin zone of the periodic lattices, which represents the reciprocal space of the unit cell, is shown in Figure 4b, and the four intersection points are marked by letters O, A, B and C, respectively. The scanning direction follows the path of O-A-B-C-O, corresponding to the scanning parameters 0-1-2-3-4 in COMSOL 5.6. As shown in Figure 5, the dispersion curves of the traditional T-NPRM, N-NPRM, and N-NPRM with aluminum pins are depicted. Figure 6 illustrates the corresponding As shown in Figure 5, the dispersion curves of the traditional T-NPRM, N-NPRM, and N-NPRM with aluminum pins are depicted. Figure 6 illustrates the corresponding mode shapes at specific points. Combining Figures 5 and 6, it can be observed that the T-NPRM structure exhibited a higher bandgap frequency. The dominant mode determining the bandgap width was the deformation of the connecting walls, resulting in a higher starting frequency, such as A1~A4 in Figure 6. Such vibration modes make it challenging to adjust the bandgap width, as changes in the material properties will cause the upper and lower mode frequencies to shift in the same direction. And B1~E4 are the modes corresponding to the marks in Figure 5c. It can be seen that the mode shapes are changed, as the stiffness and mass distribution of the unit cell is changed by the introduction of the rings and pins. The darker the color of the mode shape indicates that the greater the deformation of the corresponding position, and this is not the true deformation amplitude and is only used to represent the deformation shape. Figure 5. Figure 6. The vibration modes of the metamaterial corresponding to the points in Figure 5.
For the newly proposed N-NPRM structure, as shown in Figure 5b, the circular rings increased the local stiffness of the unit structure, leading to more coupled modes between the walls and rings. Within the frequency range of the first 20 modes, no bandgap was formed. Introducing the ring at the node mainly increased the stiffness of the node, and the mass change also increased. For the initial cell, the stiffness of the node was larger than that of the thin wall, and as the introduction of the ring resulted in a larger rigid and mass, a slight increase in the mode frequencies was generated. This small and universal change of the dispersion curves did not easily enable them to separate from each other and form bandgaps. As can be seen in Figure 5b, compared to the initial cell, the number of bandgaps reduced from 1 to 0. Therefore, in the design of cell structure, the factors that can bring significant changes to the cell mode must be considered to form the bandgap.
When metal pins were installed in the circular rings, the mass distribution of the N-NPRM cell had a noticeable change. Figure 5c shows that two bandgaps were formed, located near 7000 Hz and 14,000 Hz, respectively. By examining Figure 6, it can be observed that the mode frequencies of D1 and E1 determined the width of the first bandgap. However, both modes are the coupled motion between the walls and pins, and altering the mass of the pins will have an impact on both modes. Therefore, adjusting the material of the assembly pins may not effectively broaden the bandgap width. For the second bandgap, its upper and lower limits were determined by modes B1 and C1, as depicted in Figure 6. It can be noticed that mode B1 represents the localized vibrations of the connecting walls, while mode C1 is the coupled motion between the walls and pins. Thus, by changing the material of the pins, it is possible to conveniently adjust the frequency of mode C1 and consequently control the width of the second bandgap.
Based on the above analysis, it is evident that the bandgap is influenced by different mode shapes. In the vibration design of metamaterials, introducing factors that can alter the mode shapes and frequencies of the unit cell has the potential to control the bandgap of the metamaterial.
Effects of Design Parameters
Introducing circular rings into the traditional T-NPRM structure can adjust the mode shapes and frequencies of the unit cell, thereby enabling bandgap control of the metamaterial. In this section, we present our research on the influence of the following design factors on the bandgap.
(1) The effects of the materials of assembly pins Based on the above analysis, it can be observed that to adjust the bandgap of the metamaterial structure, effective control can be achieved by varying the density of the core pins, which requires the use of different materials for the pins. This approach enables the manipulation of the dispersion curves, which are primarily governed by the wall-pin coupled vibration mode, thereby achieving bandgap tuning of the metamaterial. Figure 7 demonstrates the bandgap characteristics of the NPRM using different assembly pin materials, namely WL8000, aluminum, steel, and copper. The bandgaps of the N-NPRM with different pins are marked by blue areas.
demonstrates the bandgap characteristics of the NPRM using different assembly pin materials, namely WL8000, aluminum, steel, and copper. The bandgaps of the N-NPRM with different pins are marked by blue areas.
In the figure, it can be observed that the presence of the pins has an impact on the mode frequencies associated with the deformation of the connecting walls. In Figure 7a, where WL8000 is used as the core material, which is the same as the metamaterial, the corresponding mode frequencies of the wall deformation are slightly increased. In the case of Figure 7b-d, the modulus of the metal materials, being significantly higher than that of WL8000, allows the pins to behave as rigid bodies in the deformation mode of the connecting walls (mode B1 in Figure 6). Consequently, the upper frequency of the bandgap (mode B1) remains around 14,700 Hz and does not vary with changes in the pin material. On the other hand, the lower mode shape of the bandgap primarily involves a wall-pin coupled motion. As the density of the pins increases, the corresponding frequency decreases, resulting in an increased width of the bandgap.
As the density difference between steel and copper is not significant, Figure 7c,d shows a minor increase in the width of the frequency band. However, the copper pins induce a decrease in frequency for the other modes, opening up a new bandgap with a frequency range of 8200 Hz to 8600 Hz. It is evident that by utilizing pins of different materials, the width of the bandgap can be effectively adjusted, potentially leading to the formation of new bandgaps. By using pins made of different materials, the width of the bandgap can be effectively controlled. This provides valuable insights for the bandgap design and optimization of metamaterials. These methods can be used in various applications, such as vibration control, wave manipulation, and energy harvesting, where precise control over bandgaps is desired. In the figure, it can be observed that the presence of the pins has an impact on the mode frequencies associated with the deformation of the connecting walls. In Figure 7a, where WL8000 is used as the core material, which is the same as the metamaterial, the corresponding mode frequencies of the wall deformation are slightly increased. In the case of Figure 7b-d, the modulus of the metal materials, being significantly higher than that of WL8000, allows the pins to behave as rigid bodies in the deformation mode of the connecting walls (mode B1 in Figure 6). Consequently, the upper frequency of the bandgap (mode B1) remains around 14,700 Hz and does not vary with changes in the pin material. On the other hand, the lower mode shape of the bandgap primarily involves a wall-pin coupled motion. As the density of the pins increases, the corresponding frequency decreases, resulting in an increased width of the bandgap.
As the density difference between steel and copper is not significant, Figure 7c,d shows a minor increase in the width of the frequency band. However, the copper pins induce a decrease in frequency for the other modes, opening up a new bandgap with a frequency range of 8200 Hz to 8600 Hz. It is evident that by utilizing pins of different materials, the width of the bandgap can be effectively adjusted, potentially leading to the formation of new bandgaps. By using pins made of different materials, the width of the bandgap can be effectively controlled. This provides valuable insights for the bandgap design and optimization of metamaterials. These methods can be used in various applications, such as vibration control, wave manipulation, and energy harvesting, where precise control over bandgaps is desired.
(2) The effect of the size of the pin From the analysis of the vibration modes above, it can be determined that increasing the size of the pins, without altering the dimensions of the metamaterial unit, will have two main effects. Firstly, reducing the length of the connecting walls will increase the mode frequencies primarily associated with the vibration deformation of the connecting walls. Secondly, increasing the size of the pins will significantly increase the local mass, leading to a decrease in the mode frequencies dominated by the wall-pin coupled motion. The effect of the pin size on the bandgap is illustrated in Figure 8, using steel as the pin material. The bandgaps of N-NPRM with pins radii of 3 mm, 3.5 mm and 4 mm are marked by blue area, red area and yellow area, respectively. (2) The effect of the size of the pin From the analysis of the vibration modes above, it can be determined that increasing the size of the pins, without altering the dimensions of the metamaterial unit, will have two main effects. Firstly, reducing the length of the connecting walls will increase the mode frequencies primarily associated with the vibration deformation of the connecting walls. Secondly, increasing the size of the pins will significantly increase the local mass, leading to a decrease in the mode frequencies dominated by the wall-pin coupled motion. The effect of the pin size on the bandgap is illustrated in Figure 8, using steel as the pin material. The bandgaps of N-NPRM with pins radii of 3 mm, 3.5 mm and 4 mm are marked by blue area, red area and yellow area, respectively.
As the pin size increases, the upper limit frequency of the bandgap increases, while the lower limit frequency decreases, resulting in a significantly widened bandgap. Moreover, when the pin size reaches 4 mm, a new bandgap is opened up in the frequency range of 3800 Hz to 4000 Hz. It can be observed that increasing the pin size is advantageous for expanding the bandgap.
This shows that by adjusting the size of the pins, it is possible to modify the mode frequencies and broaden the bandgap without altering the dimensions of the metamaterial unit. This work provides guidance for the design and optimization of metamaterials with desired bandgap properties, enabling enhanced vibration control and wave manipulation capabilities. (3) The effect of particle damping As the pin size increases, the upper limit frequency of the bandgap increases, while the lower limit frequency decreases, resulting in a significantly widened bandgap. Moreover, when the pin size reaches 4 mm, a new bandgap is opened up in the frequency range of 3800 Hz to 4000 Hz. It can be observed that increasing the pin size is advantageous for expanding the bandgap.
This shows that by adjusting the size of the pins, it is possible to modify the mode frequencies and broaden the bandgap without altering the dimensions of the metamaterial unit. This work provides guidance for the design and optimization of metamaterials with desired bandgap properties, enabling enhanced vibration control and wave manipulation capabilities.
(3) The effect of particle damping In engineering applications, low-frequency vibration sources often are common. Therefore, low-frequency and wide-band vibration control methods have been a significant research focus. For instance, in traditional industries, like the automotive sector, vibrations below 2000 Hz are of utmost concern. In the context of vibration control in metamaterial structures, bandgap manipulation is an important design approach. In the proposed N-NPRM structure, the addition of circular rings shifts the dispersion curves of the metamaterial towards lower frequencies. However, it remains challenging to form effective bandgaps below 2000 Hz. To expand the application range of metamaterials, new methods must be introduced to suppress vibrations in the low-frequency range.
For the traditional T-NPRM structure, its mode shapes are combinations of the deformations of the walls that make up the structure. In the case of N-NPRM, the addition of circular rings leads to significant changes in the stiffness and mass distribution within the unit cell. The structural stiffness is noticeably increased, which is beneficial for enhancing its load-bearing capacity, as shown in Figure 3. At the same time, the mode shapes of N-NPRM exhibit specific characteristics as the frequency increases, as depicted in Figure 9. The darker the color of the mode shape indicates that the greater the deformation of the corresponding position. For the circular rings, as the frequency increases, they exhibit translational, rotational, and deformation motions, represented by M1 to M3 in Figure 9. At very high frequencies, the mode shapes resemble localized deformations of the walls, as shown by M4 in Figure 9. In the above analysis, it was found that increasing the weight at the location of the circular rings can effectively lower the frequencies of modes, such as M1 to M3. In engineering applications, low-frequency vibration sources often are common. Therefore, low-frequency and wide-band vibration control methods have been a significant research focus. For instance, in traditional industries, like the automotive sector, vibrations below 2000 Hz are of utmost concern. In the context of vibration control in metamaterial structures, bandgap manipulation is an important design approach. In the proposed N-NPRM structure, the addition of circular rings shifts the dispersion curves of the metamaterial towards lower frequencies. However, it remains challenging to form effective bandgaps below 2000 Hz. To expand the application range of metamaterials, new methods must be introduced to suppress vibrations in the low-frequency range.
For the traditional T-NPRM structure, its mode shapes are combinations of the deformations of the walls that make up the structure. In the case of N-NPRM, the addition of circular rings leads to significant changes in the stiffness and mass distribution within the unit cell. The structural stiffness is noticeably increased, which is beneficial for enhancing its load-bearing capacity, as shown in Figure 3. At the same time, the mode shapes of N-NPRM exhibit specific characteristics as the frequency increases, as depicted in Figure 9. The darker the color of the mode shape indicates that the greater the deformation of the corresponding position. For the circular rings, as the frequency increases, they exhibit translational, rotational, and deformation motions, represented by M1 to M3 in Figure 9. At very high frequencies, the mode shapes resemble localized deformations of the walls, as shown by M4 in Figure 9. In the above analysis, it was found that increasing the weight at the location of the circular rings can effectively lower the frequencies of modes, such as M1 to M3. Based on the analysis of the mode shapes of the metamaterial structure shown in Figure 9, it was observed that in the low-frequency range, the circular rings undergo significant motion. Therefore, by combining traditional damping vibration control methods, the introduction of particle damping within the circular rings becomes a possibility for the broad-spectrum suppression of low-frequency vibrations.
In the simulation, the circular rings and particle damping were treated as an integrated system. The increase in weight due to particle damping can be achieved by adjusting the density of the circular rings. To prevent particle leakage, covers were added at both ends of the circular rings, which enhanced the stiffness at the location of the circular rings. The effect on the stiffness can be adjusted by modifying the elastic modulus of the circular rings, disregarding the impact when it is negligible and ensuring equal weight. Figure 10c shows the dispersion diagram of the metamaterial when the weight of the circular rings was equal to the weight of the steel pins. It can be observed in the figure that when particle damping was added within the circular rings, the mode frequencies were generally lower compared to the metamaterial with inserted steel pins since the increase Based on the analysis of the mode shapes of the metamaterial structure shown in Figure 9, it was observed that in the low-frequency range, the circular rings undergo significant motion. Therefore, by combining traditional damping vibration control methods, the introduction of particle damping within the circular rings becomes a possibility for the broad-spectrum suppression of low-frequency vibrations.
In the simulation, the circular rings and particle damping were treated as an integrated system. The increase in weight due to particle damping can be achieved by adjusting the density of the circular rings. To prevent particle leakage, covers were added at both ends of the circular rings, which enhanced the stiffness at the location of the circular rings. The effect on the stiffness can be adjusted by modifying the elastic modulus of the circular rings, disregarding the impact when it is negligible and ensuring equal weight. Figure 10c shows the dispersion diagram of the metamaterial when the weight of the circular rings was equal to the weight of the steel pins. It can be observed in the figure that when particle damping was added within the circular rings, the mode frequencies were generally lower compared to the metamaterial with inserted steel pins since the increase in stiffness due to particle damping was not significant. As shown in Figure 10b,c, the first 20 mode shapes occurred within the frequency ranges of 0-16,000 Hz and 0-9000 Hz, respectively. Although the addition of particles created a bandgap at 6500 Hz, it was still ineffective for controlling the vibrations at even lower frequencies. However, increasing the particle damping caused more dispersion curves to concentrate in the low-frequency range, facilitating the mode of wall-ring-coupled vibrations. This phenomenon allows particles to collide and generate friction, thereby providing damping effects and suppressing vibrations in the low-frequency range. 20 mode shapes occurred within the frequency ranges of 0-16,000 Hz and 0-9000 Hz, respectively. Although the addition of particles created a bandgap at 6500 Hz, it was still ineffective for controlling the vibrations at even lower frequencies. However, increasing the particle damping caused more dispersion curves to concentrate in the low-frequency range, facilitating the mode of wall-ring-coupled vibrations. This phenomenon allows particles to collide and generate friction, thereby providing damping effects and suppressing vibrations in the low-frequency range. The vibration suppression ability of the samples was evaluated by the vibration transmission loss (VTL), which can be written as: where a and a are the acceleration amplitudes of the sensors shown in Figure 11. The vibration transmission loss of the NPRMs were calculated by the software ABAQUS, and the results can be seen in Figure 10d. It can be seen that the introduction of steel pins can generate a broad bandgap from 9100 Hz to 14,500 Hz, and the vibration in The vibration suppression ability of the samples was evaluated by the vibration transmission loss (VTL), which can be written as: where a input and a output are the acceleration amplitudes of the sensors shown in Figure 11.
vibration suppression ability in low frequency (400 Hz~4500 Hz) is better than the that of the NPRM with steel pins. The steel pin can increase both the mass and stiffness, and thus, the vibration deformation amplitude is weaker than that of the NPRM with an equivalent mass.
In the simulation, for computational efficiency, the particle damping of the equivalent mass was ignored. In the following text, we investigate the vibration suppression ability of particle damping by experiments. Figure 11. The testing of vibration transmission loss. (a) The testing system of vibration transmission loss, (b) The metamaterial samples with metal pins and particle damping.
Simulation of Transfer Performance and Experimental Verification
In this section, we use simulation and experimental methods to validate the vibrational suppression capability of the proposed N-NPRM and compare the simulations with the experimental results to verify the accuracy of the simulation method. The results show that the simulation agrees well and can effectively guide the design of N-NPRM.
An experimental test of VTL was carried out, as shown in Figure 11a. The sampling frequency of the experiment was 10,000 Hz, and the sampling time was 10 s. A vibration shaker was used to excite the sample. The white noise generated by a sweep signal generator was used as an excitation signal to control the vibration shaker, and the sweeping frequency range was from 1 Hz to 5000 Hz. Two acceleration sensors were used to collect the vibration signal, and the sensitivities were 1.075 mv/(m • s ) and 1.067 mv/(m • s ), respectively. The ultimate testing range of the acceleration sensor was 10,000 Hz.
The results of the simulations and experiments are shown in Figure 12. As can be seen in Figure 12a,b, the frequency consistency corresponding to the structural mode peaks obtained by the simulation and experiment is good (peaks in yellow box), which indicates that the simulation method was effective. Figure 12c shows that the simplified method for N-NPRM with particle damping is feasible, because the frequency consistency corresponding to the simulation and experimental structural mode peaks is good (yellow The vibration transmission loss of the NPRMs were calculated by the software ABAQUS, and the results can be seen in Figure 10d. It can be seen that the introduction of steel pins can generate a broad bandgap from 9100 Hz to 14,500 Hz, and the vibration in this frequency band is suppressed obviously. However, compared to the other two NPRMs, the vibration in low frequency (200~4500 Hz) is not suppressed obviously.
The NPRM with equivalent mass can generate a bandgap near 6500 Hz, and the narrow bandgap cannot generate broadband vibration suppression. The equivalent mass cannot obviously increase the stiffness of the NPRM, but it can increase the vibration deformation amplitude, which can enhance the effect of the structure damping. Therefore, the vibration suppression ability in low frequency (400~4500 Hz) is better than the that of the NPRM with steel pins. The steel pin can increase both the mass and stiffness, and thus, the vibration deformation amplitude is weaker than that of the NPRM with an equivalent mass.
In the simulation, for computational efficiency, the particle damping of the equivalent mass was ignored. In the following text, we investigate the vibration suppression ability of particle damping by experiments.
Simulation of Transfer Performance and Experimental Verification
In this section, we use simulation and experimental methods to validate the vibrational suppression capability of the proposed N-NPRM and compare the simulations with the experimental results to verify the accuracy of the simulation method. The results show that the simulation agrees well and can effectively guide the design of N-NPRM.
An experimental test of VTL was carried out, as shown in Figure 11a. The sampling frequency of the experiment was 10,000 Hz, and the sampling time was 10 s. A vibration shaker was used to excite the sample. The white noise generated by a sweep signal generator was used as an excitation signal to control the vibration shaker, and the sweeping frequency range was from 1 Hz to 5000 Hz. Two acceleration sensors were used to collect the vibration signal, and the sensitivities were 1.075 mv/(m·s 2 ) and 1.067 mv/(m·s 2 ), respectively. The ultimate testing range of the acceleration sensor was 10,000 Hz.
The results of the simulations and experiments are shown in Figure 12. As can be seen in Figure 12a,b, the frequency consistency corresponding to the structural mode peaks obtained by the simulation and experiment is good (peaks in yellow box), which indicates that the simulation method was effective. Figure 12c shows that the simplified method for N-NPRM with particle damping is feasible, because the frequency consistency corresponding to the simulation and experimental structural mode peaks is good (yellow box), indicating that it was feasible for the stiffness and quality simplification of the particle damping. However, because the action mode of the particle damping was different from the structural damping, the suppression effect of the structural vibration was quite different. Therefore, Figure 12d is an experimental comparison of the vibration suppression effect of N-NPRM with steel pins and N-NPRM with particle damping, and the results show that the particle damping can achieve a very good vibration suppression effect in the low-and middle-frequency bands (peaks in yellow boxes). It is worth noting that particle damping has advantages in the application of the vibration suppression of space equipment due to its good environmental adaptability and high reliability. box), indicating that it was feasible for the stiffness and quality simplification of the particle damping. However, because the action mode of the particle damping was different from the structural damping, the suppression effect of the structural vibration was quite different. Therefore, Figure 12d is an experimental comparison of the vibration suppression effect of N-NPRM with steel pins and N-NPRM with particle damping, and the results show that the particle damping can achieve a very good vibration suppression effect in the low-and middle-frequency bands (peaks in yellow boxes). It is worth noting that particle damping has advantages in the application of the vibration suppression of space equipment due to its good environmental adaptability and high reliability.
Conclusions
In this work, a novel re-entrant NPR metamaterial was designed. Some assembly parts and particle damping were introduced to the proposed metamaterials. The static mechanical properties and vibration suppression capacities were investigated. Some conclusions can be obtained as follows: 1. The stiffness of the new NPRM structure is much higher than that of the traditional NPRM structure, which can greatly improve the carrying capacity of the structure to 300%. 2. The installation of different metal accessories in N-NPRM can easily adjust the bandgap of metamaterials. The larger the re-entrant ring, the wider the bandgap. 3. Mounting particle damping in N-NPRM enables very good vibration inhibition in the medium-and low-frequency bands.
Conclusions
In this work, a novel re-entrant NPR metamaterial was designed. Some assembly parts and particle damping were introduced to the proposed metamaterials. The static mechanical properties and vibration suppression capacities were investigated. Some conclusions can be obtained as follows: 1.
The stiffness of the new NPRM structure is much higher than that of the traditional NPRM structure, which can greatly improve the carrying capacity of the structure to 300%.
2.
The installation of different metal accessories in N-NPRM can easily adjust the bandgap of metamaterials. The larger the re-entrant ring, the wider the bandgap.
3.
Mounting particle damping in N-NPRM enables very good vibration inhibition in the medium-and low-frequency bands.
The re-entrant metamaterial proposed in this paper can easily change its bandgap characteristics by replacing the assembly pin. Particle damping has good environmental adaptability and high reliability, and its introduction is conducive to extending the vibration suppression application of metamaterials in space equipment. | 9,896.6 | 2023-08-21T00:00:00.000 | [
"Engineering",
"Materials Science",
"Physics"
] |
Genetic Simulation Resources: a website for the registration and discovery of genetic data simulators
Summary: Many simulation methods and programs have been developed to simulate genetic data of the human genome. These data have been widely used, for example, to predict properties of populations retrospectively or prospectively according to mathematically intractable genetic models, and to assist the validation, statistical inference and power analysis of a variety of statistical models. However, owing to the differences in type of genetic data of interest, simulation methods, evolutionary features, input and output formats, terminologies and assumptions for different applications, choosing the right tool for a particular study can be a resource-intensive process that usually involves searching, downloading and testing many different simulation programs. Genetic Simulation Resources (GSR) is a website provided by the National Cancer Institute (NCI) that aims to help researchers compare and choose the appropriate simulation tools for their studies. This website allows authors of simulation software to register their applications and describe them with well-defined attributes, thus allowing site users to search and compare simulators according to specified features. Availability: http://popmodels.cancercontrol.cancer.gov/gsr. Contact<EMAIL_ADDRESS>
INTRODUCTION
Owing to the cost and availability of genetic samples, lack of knowledge of causal variants that contribute to observed phenotypes and mathematical intractability of complex evolutionary models, computer simulations have been widely used, among many applications, to predict outcomes under realistic genetic scenarios (e.g. Peng and Kimmel, 2007), to compare and verify analytical methods or tools (e.g. Spencer et al., 2009) and to estimate parameters of evolutionary models (e.g. Peter et al., 2010). With increasing power of personal computers and the availability of computer clusters, novel simulation methods and sophisticated simulation programs have been and continue to be developed to simulate genetic data for new application areas such as large-scale genomic studies (Dalquen et al. 2012).
Despite the availability of a large number of simulation programs, choosing appropriate simulation programs for a particular research topic can be a time-consuming process that usually involves studying, downloading and testing many different tools with varying quality. Adding to the difficulties is the fact that many software applications lack comprehensive documentation, and use implicit assumptions and terminologies that are familiar only to researchers in particular research areas. As a result, at an NCI-sponsored conference, meeting participants recommended creating a web resource that summarizes available genetic simulation programs (Mechanic et al., 2012).
Genetic Simulation Resources (GSR) is a website provided by NCI that aims to help researchers compare and choose the right simulation tools for their studies. This website allows authors of simulation software to register their applications and describe them with standardized attributes that are understandable to researchers in diverse research areas. Visitors of this website can browse a catalogue of genetic data simulators, review simulators of interest and search and compare simulators according to specified features. This pre-sorting allows researchers to focus on the most applicable simulators before starting the time-consuming process of downloading and testing the packages themselves.
METHODS
We searched published articles for software applications that simulate genetic data for the human genome in scientific journals such as Bioinformatics, BMC Bioinformatics, Genetics and Molecular Biology and Evolution. We selected simulators that can simulate genetic markers, haploid and diploid DNA sequences and RNA and protein sequences of the human genome. We excluded simulators without an accessible web page or download link and those that are designed for teaching purposes and are limited in their ability to simulate usable genetic data. We also excluded packages that have been replaced by newer or updated packages from the same authors.
We collected basic information of selected simulators, including short and long descriptions, URL to package web page, project start date and version and release date of the most recent release. We went through publications and documentation of these simulators and summarized *To whom correspondence should be addressed. their features with 167 attributes in 8 categories and 25 subcategories. These attributes range from key features such as type of genetic variations that can be simulated (e.g. single nucleotide polymorphism, insertion and deletion and microsatellite) and simulation methods (e.g. coalescent, forward time, resampling based and phylogenetic), to development features such as programming language, supported platform and license information. Because not all aspects of packages will be captured using these standard attributes, we allow package owners to annotate existing attributes with package-specific comments and define package-specific attributes.
We entered attributes of selected simulators and characterized them to the best of our knowledge. To ensure the accuracy of data, we sent a questionnaire to all package authors and received responses from approximately half of the authors, which may suggest that some packages have been left unmaintained for various reasons. We revised attributes of packages according to feedback from authors.
The GSR website currently provides an interface to a catalogue of 80 registered packages (Fig. 1), with a global search box, a list view of all software resources and interfaces to rank packages according to selected attributes and compare attributes of selected packages. Packages in this catalogue are continuously being added and updated by authors and users of simulation programs. GSR does not host or maintain individual packages and is not responsible for the accuracy and timely update of information related to these packages. We plan to evaluate the activity of packages regularly, based on factors including, but not limited to, availability of website and download links, number of updates and web visitors to package pages on GSR, number of applications (citations) and feedback from users of GSR. Packages that are no longer used by the research community will be phased out and eventually removed from GSR.
DISCUSSION
GSR provides a catalogue of genetic data simulators with detailed descriptions and list of features of each package, which make it easier for users of GSR to search and compare simulators and identify the most appropriate simulators for particular research topics. Package authors will also benefit from this service because a centralized catalogue would increase visibility of their software, and a clear list of features would help with documentation of their packages. GSR compliments existing review articles (e.g. Hoban et al., 2012;Liu et al., 2008) on genetic simulation programs by providing a comprehensive up-to-date list of programs, with links to web pages and searchable attributes, in a user-friendly format.
GSR is still under active development. Features that will be provided in the near future include an automated revision proposal and approval process, a citation management interface to track the applications of packages and a user-feedback system. We encourage all authors of genetic data simulators to register their packages in GSR and place a link to GSR on their websites, which would turn individually hosted packages to a web of simulators that could greatly facilitate the application, development and dissemination of genetic simulators. | 1,570.8 | 2013-02-23T00:00:00.000 | [
"Biology",
"Computer Science"
] |
The ultra-long GRB 220627A at z = 3.08
Context. GRB 220627A is a rare burst with two distinct γ -ray emission episodes separated by almost 1000s that triggered the Fermi Gamma-ray Burst Monitor twice. High-energy GeV emission was detected by the Fermi Large Area Telescope coincident with the first emission episode but not the second. The discovery of the optical afterglow with MeerLICHT led to MUSE observations which secured the burst redshift to z = 3 . 08, making this the most distant ultra-long gamma-ray burst (GRB) detected to date. Aims. The progenitors of some ultra-long GRBs have been suggested in the literature to be di ff erent to those of normal long GRBs. Our aim is to determine whether the afterglow and host properties of GRB 220627A agree with this interpretation. Methods. We performed empirical and theoretical modelling of the afterglow data within the external forward shock framework, and determined the metallicity of the GRB environment through modelling the absorption lines in the MUSE spectrum. Results. Our optical data show evidence for a jet break in the light curve at ∼ 1 . 2days, while our theoretical modelling shows a preference for a homogeneous circumburst medium. Our forward shock parameters are typical for the wider GRB population, and we find that the environment of the burst is characterised by a sub-solar metallicity. Conclusions. Our observations and modelling of GRB 220627A do not suggest that a di ff erent progenitor compared to the progenitor of normal long GRBs is required. We find that more observations of ultra-long GRBs are needed to determine if they form a separate population with distinct prompt and afterglow features, and possibly distinct progenitors.
Introduction
Gamma-ray bursts (GRBs) are flashes of γ-rays lasting from milliseconds to hours typically with isotropic γ-ray luminosities of ∼10 51 −10 53 erg s −1 , making them the most luminous explosions observed in the Universe (Zhang 2018).GRBs have traditionally been separated into long and short bursts based on an observed bimodality in their duration distribution, with 2 s taken as the dividing line (Kouveliotou et al. 1993).Short bursts are thought to be caused by the coalescence of two compact objects involving a neutron star, while long bursts are thought to result from the collapse of a massive Wolf-Rayet star, though recent observations have shown there is an overlap between these two classes (e.g., GRB 211211A; Rastinejad et al. 2022;Yang et al. 2022).
A very small number of bursts have been detected with extremely long durations greater than 1000 s (e.g., GRBs 091024A, 101225A, 111209A, 130925A; Gruber et al. 2011;Thöne et al. 2011;Gendre et al. 2013;Stratta et al. 2013;Virgili et al. 2013;Evans et al. 2014;Levan et al. 2014;Piro et al. 2014).Some authors have suggested that these GRBs form a distinct class of so-called ultra-long GRBs whose progenitors may be different with respect to the collapsar model (Gendre et al. 2013;Levan et al. 2014).Levan et al. (2014) studied three ultralong GRBs -GRB 101225A, GRB 111209A, and GRB 121027A -and found that they had very similar long-lasting X-ray emission with flares and were situated close to the cores of highly star-forming dwarf galaxies.The extremely long duration of these bursts led them to conclude that their central engines were active for much longer than normal long GRBs, and therefore their progenitors may be blue supergiant stars (Mészáros & Rees 2001;Nakauchi et al. 2013) which have much larger radii than the compact Wolf-Rayet stars that are commonly regarded as the progenitors of long GRBs (Woosley & Bloom 2006).This was the preferred explanation by Gendre et al. (2013) for the extremely long duration of ∼25 000 s for GRB 111209A, where the additional mass from the outer layers of such a star can power the central engine for much longer, leading to longer-duration γ-ray emission.Zhang et al. (2014), however, pointed out that not all bursts that had been claimed as ultra-long were actually ultra-long in γ-rays (e.g., GRB 121027A).Instead, the long duration of highly variable X-ray light curves had been used to infer the ultralong duration (Levan et al. 2014).Swift observations of X-ray flares and internal plateaus have shown that the central engine duration is much longer than T 90 values suggest.Zhang et al. (2014) therefore used X-ray data in addition to γ-ray data to derive central engine durations for 343 GRBs, and found that 21.9% of GRBs have durations t burst 10 3 s, and 11.5% have t burst 10 4 s.The inference is that ultra-long GRBs may be the tail of a single long GRB population and do not require a separate, blue supergiant progenitor even though the data do not exclude it.Additionally, observations suggest that the afterglow properties of ultra-long GRBs are not different to those of other, classical, long GRBs (Virgili et al. 2013).In order to assess the claim that ultra-long GRBs form a distinct population compared to other long GRBs, further multi-wavelength observational evidence encompassing afterglow and host galaxy properties is needed.
On 2022 June 27, the Fermi Gamma-ray Burst Monitor (GBM; Meegan et al. 2009) was triggered by two events separated by 956 s, leading to the speculation that GRB 220627A was a gravitationally lensed or ultra-long GRB with a duration of ∼1000 s (Roberts et al. 2022).The Large Area Telescope (LAT; Atwood et al. 2009) aboard Fermi detected high-energy photons coincident with the first GBM trigger and localised the first burst to a 0.2 degree-radius error circle (di Lalla et al. 2022), which led to the eventual identification of the optical and X-ray afterglows at ∼0.8 days post-trigger.Here we report the results of our observational follow-up campaign and place GRB 220627A in the context of the ultra-long GRB population.
We note that there is no universally agreed-upon definition for ultra-long GRBs, so we defer to adopting the convention that ultra-long bursts satisfy T 90 1000 s, as used by Lien et al. (2016).We report all uncertainties at the 1σ level unless stated otherwise, and all magnitudes in the AB system.We follow the conventions with F ν ∝ ν β t α and N E (E) ∝ E −Γ , and adopt a Lambda cold dark matter (ΛCDM) cosmology with Ω m = 0.31, Ω Λ = 0.69, and H 0 = 68 km s −1 Mpc −1 (Planck Collaboration XIII 2016).The first Fermi/GBM trigger occurred at 21:21:00.09UT.We take this time as T 0 for GRB 220627A, and reference all other observations with respect to this time.
MeerLICHT optical afterglow discovery
MeerLICHT is a 65-cm aperture fully-robotic optical telescope located at the South African Astronomical Observatory (SAAO) site in Sutherland, South Africa (Bloemen et al. 2016).The primary science goal behind MeerLICHT is to provide simultaneous optical coverage of the radio sky as observed by the 64-antennae MeerKAT radio array, which is also located within the arid Karoo region of the South African interior.Meer-LICHT's wide field-of-view of 2.7 deg 2 (98.6 × 98.6 ) and robotic operation make it suitable for the discovery of new transients and follow-up of events with large error boxes on the plane of the sky, such as gravitational wave (GW) events and poorlylocalised GRBs, while its six filters (SDSS ugriz plus a wide q filter spanning 440-720 nm, roughly equivalent to g + r) make it suitable for multi-colour monitoring of transients.
MeerLICHT began an observing programme in June 2021 to follow-up GRBs detected by the Swift and Fermi missions.For Swift bursts the aim is to start observing Burst Alert Telescope (BAT) error boxes as soon as possible after a trigger, regardless of whether an X-ray or optical counterpart is discovered by Swift.For Fermi bursts the aim is to observe a cumulative probability of at least 70% of the GBM HEALPix skymaps with 80 or fewer telescope pointings, an observing criterion which naturally targets brighter bursts since they are better-localised.Observations are automatically triggered for bursts if they can begin within five hours of a trigger, with manual scheduling available for specific cases such as LAT-detected bursts or bursts with a high scientific interest.
GRB 220627A triggered automatic observations with Meer-LICHT starting 21 min after the trigger at 21:42:23 UT, when the fields became visible given the telescope's observing constraints.The first GBM trigger had a 90% (50%) error area of 216.5 (52.7) deg 2 , while the second trigger had a 90% (50%) error area of 213.8 (32.5) deg 2 .A total of 52 fields encompassing a cumulative probability of 71% of the first trigger GBM skymap (see Fig. 1) were observed during the 1.6 h that MeerLICHT was observing.All observations consisted of 60 s q-band exposures, since the q band is our most sensitive band and also has the most complete set of archival reference images.Our automatic scheduling aims to target the highest probability fields first, but due to the western fields setting first only the most eastern fields were scheduled.All 52 fields were observed at least once in the q band, while ten of the most eastern fields were observed twice encompassing a cumulative probability of 7.5%.Two of these ten fields were observed three times.The MeerLICHT transient detection pipeline was used to identify two afterglow candidates which were reported via the GCN within six hours of the first trigger (Groot et al. 2022).
The next morning at 07:00:40 UT, a Fermi/LAT GCN circular indicated that high-energy γ-rays had been detected along with a 0.2 degree radius localisation -a much smaller error box than the GBM error box (di Lalla et al. 2022).The LAT error box straddled two MeerLICHT fields which had not been observed on the previous night, ruling out our two initial afterglow candidates.We scheduled 2 × 300 s observations in the q band for these fields in order to search for an optical afterglow within the LAT error box.Observations began just after the evening twilight under new moon conditions at 17:12:15 UT, at approximately 0.83 days post-trigger.Swift/XRT target of opportunity (ToO) observations identified 15 X-ray sources 1 within the LAT error box that may have been associated with GRB 220627A (Evans & Swift Team 2022), most having error regions with radii smaller than 8 .Among the three most promising2 candidates (green in Fig. 1), only one source was uncatalogued.Our two MeerLICHT images at 0.84 and 0.87 days showed a new optical transient within the error box of this source at coordinates α = 13 h 25 m 28.49 s , δ = −32 d 25 m 33.31 s (ICRS).The brightness of q = 21.25 ± 0.09 mag in our first exposure, and the lack of any source at the same position down to q > 21.71 in an archival image from two months earlier made it likely that this source was indeed the optical afterglow to GRB 220627A (de Wet et al. 2022).The source was confirmed as the afterglow through spectroscopic observations with MUSE mounted on the VLT (see Sect. 2.5 below, and Izzo et al. 2022).
Prompt emission
The duration of the burst associated with the first GBM trigger was T 90 = 136.71± 1.28 s, while that of the burst associated with the second trigger was T 90 = 126.98± 8.84 s, as taken from the online Fermi GBM Burst Catalog3 (von Kienlin et al. 2020).The 10−1000 keV fluence for the first and second triggers (from the Burst Catalog) are (4.54 ± 0.01) × 10 −5 erg cm −2 and (1.08 ± 0.02) × 10 −5 erg cm −2 , resulting in a total fluence of (5.62 ± 0.02) × 10 −5 erg cm −2 across both episodes.At the burst redshift of z = 3.08 (Sect.2.5) this results in a high isotropic γ-ray energy of E γ,iso = (4.81± 0.02) × 10 54 erg.Among the ∼130 GRBs with known redshift listed in the 10-yr Fermi-GBM Gamma-Ray Burst Spectral Catalog (Poolakkil et al. 2021), only two bursts have a larger isotropic γ-ray energy: GRBs 090323 and 160625B.Both emission episodes were also detected by Konus-Wind (Aptekar et al. 1995).The Konus-Wind light curve had a similar structure to the GBM light curve, though it was reported that a weak emission tail may have been present in the soft energy bands (20−100 keV) lasting up until T 0 + 3700 s (Frederiks et al. 2022).
GeV photons were detected by Fermi/LAT coincident with the first GBM trigger but not with the second one (di Lalla et al. 2022).The detection of GeV photons makes GRB 220627A the first ultra-long (with duration >1000 s) GRB detected at these energies.The prompt emission from GBM and LAT was studied in detail by Huang et al. (2022).They found that the time-integrated spectrum for the first emission episode is best described by a cutoff power law plus a power law component, where the power law component (with Γ = 1.92 ± 0.05) is necessary to account for the detected LAT photons.The second emission episode is best described by a cutoff power law alone.The cutoff energy for the first and second episodes are E c = 286.96± 38.00 keV and E c = 248.64± 66.58 keV, while their low-energy photon indices are Γ = 0.73 ± 0.10 and Γ = 1.06 ± 0.11, respectively.Huang et al. (2022) argue that the gravitational-lensing scenario to explain the two triggers can be ruled out at the 5.1σ level based on the non-detection of any LAT photons coincident with the second trigger.Furthermore, they place a lower limit on the bulk Lorentz factor of Γ ≥ 300 by using the optical depth to pair production method along with the highest energy LAT photon with an energy of 15.3 GeV.
In order to quantify the duration of GRB 220627A across both emission episodes, we obtained the CSPEC data from the NASA HEASARC data archive for the NaI detectors where the burst position was within 50 • of the detector normal -these were naturally the detectors with the strongest detected signal.For trigger 1 these were detectors n0, n1, n3 and n6, while for trigger 2 these were n3, n4, n6, n7, and n8.We considered photons with energies between 8 keV and 1 MeV and rebinned the count-rate light curve for each detector in 4.096 s time bins, fitting the background with polynomials of varying order in three time intervals for each detector: before the first trigger, between both triggers, and after the second trigger.These time intervals correspond to [−250.0,−60.0], [300.0,900.0] and [1200.0,1500.0]s with respect to T 0 .The summed count rate light curve for all seven detectors is shown in Fig. 2. We determine a burst duration of T 90 ≈ 1092 s as the time difference between the times when the cumulative background-subtracted count rate was between 5% and 95% of its total value.We note that this duration depends on the time binning used and the detectors included in the summed light curve, and hence should be regarded as approximate.
The spectral hardness vs. duration diagram has long been used as a means of categorising bursts into long and soft or short and hard classes (Kouveliotou et al. 1993), notwithstanding the fact that the burst duration is energy and detector-dependent (Qin et al. 2013;Bromberg et al. 2013).For both emission episodes we calculated the hardness ratio as the ratio of the integrated flux in the 50-300 keV to 10-50 keV energy ranges, making use of the best-fit parameters from the cutoff power law fits performed by Huang et al. (2022).Figure 3 compares the position of both emission episodes in the hardness-duration diagram with the sample of triggers from the Fourth Fermi/GBM Gamma-Ray Burst Catalog (von Kienlin et al. 2020).We see that both emission episodes sit in the long and soft portion of the diagram, providing support for a collapsar origin.
X-rays
The Swift X-Ray Telescope (XRT; Burrows et al. 2005) conducted ToO observations of the LAT error box in order to search for X-ray afterglow candidates (Evans & Swift Team 2022).The MeerLICHT identification of an optical source coincident with one of the potential X-ray afterglow candidates (see Sect. 2.1) confirmed this source as the X-ray afterglow, along with evidence of X-ray fading.A total of three orbits of Photon Counting mode (PC) observations of the afterglow were acquired at mid-times of 0.52, 1.59 and 4.62 days post-trigger.We obtained the X-ray count-rate light curve and spectrum from the online Swift/XRT GRB Catalogue hosted on the UK Swift Science Data Centre (UKSSDC) website (Evans et al. 2007(Evans et al. , 2009)).We fitted the photon spectrum with a photoelectrically absorbed power law model (tbabs*ztbabs*pow) in Xspec version 12.12.1,fixing the Galactic hydrogen column density at N Gal with a C-statistic of 14.7 for 19 degrees of freedom.The unabsorbed 0.3−10 keV flux was 1.05 +0.28 −0.24 × 10 −12 erg cm −2 s −1 , from which we derive an unabsorbed counts-to-flux conversion factor of 3.60 × 10 −11 erg cm −2 count −1 .Using this value along with a spectral index of β X ≡ 1 − Γ X ≈ −0.73 we created a 1 keV X-ray light curve.The light curve consisted of two detections at 0.52 and 1.59 days, and a 3σ upper limit at 4.62 days (see Fig. 4).
Optical/near-infrared photometry
Following confirmation of the afterglow detection, we obtained 600 s exposures in each of the q, g, r, and i bands with MeerLICHT at ∼1.84 days post-trigger.We used the MeerLICHT pipeline (Vreeswijk et al., in prep.) to perform standard CCD reduction tasks including calibration, astrometry and point-spread function (PSF) photometry.Due to the faintness of the afterglow in some of our images, we employed a forced photometry routine (developed as part of the MeerLICHT pipeline) to accurately measure the flux and significance of the detections.The afterglow was detected with a high significance (>15σ) in the first two q-band images at 0.84 and 0.87 days.The afterglow was detected at more than 5σ significance in the q and r bands at 1.84 days, and at 4.7σ significance in the g band.The i-band observation yielded a lowsignificance measurement of 2.7σ which we do not include as a detection.
We obtained 6 × 600 s exposures at approximately 0.93 days post-trigger in the g, r, and i bands with the 1-m SAAO Lesedi optical telescope (Worters et al. 2016) located in Sutherland and equipped with the Mookodi spectrograph and imager (Erasmus et al., in prep.).We employed an adapted version of the Meer-LICHT pipeline to perform astrometry and photometry on each image since both telescopes make use of the SDSS ugriz filter set.The pipeline produced a catalogue file containing all 5σ source detections.We detected the afterglow in each image.MeerLICHT is abbreviated to ML in the legend.The vertical grey region denotes the time of the MUSE spectroscopic observations.We show the broken power law fits to each of the g, q, r and i bands, where the break time and temporal indices were constrained to be the same across each fit.Residuals are shown in magnitudes in the lower panel.We show the two X-ray detections as crosses and the single upper limit as an upside-down triangle.The dotted line is the optical light curve fit shifted vertically to the X-ray band.
We acquired three epochs of imaging in the Bessel R filter at 1.13, 5.09, and 360.2 days post-trigger with the European Southern Observatory Very Large Telescope (ESO VLT) UT1 (Antu) equipped with FORS2.We obtained the last epoch approximately one year after the GRB in order to constrain any host galaxy emission long after the afterglow had faded.Each epoch consisted of 6 × 200 s, 3 × 200 s and 3 × 300 s exposures, respectively.We performed photometric calibration in the R band using ri DELVE DR2 photometry (Drlica-Wagner et al. 2022) of a large number of stars in the field along with the Lupton (2005)4 transformation equation R = r − 0.2936 * (r − i) − 0.1439.We employed the Aperture Photometry Tool (APT; Laher et al. 2012) with a three-pixel radius aperture in an automated mode to extract instrumental magnitudes of all 3σ point sources within the FORS2 images, and derived image zero-points of 33.18 ± 0.02, 33.37±0.01,and 33.42±0.03mag in the images from 1.13, 5.09, and 360.2 days, respectively.We detected the afterglow with a brightness of R = 21.25 ± 0.02 and R = 24.61± 0.10 mag during the first two epochs, and derived a 3σ upper limit of R > 25.92 mag during the third epoch.
We further obtained two epochs of follow-up observations of GRB 220627A in the g r i z JHK bands with the Gamma-ray Burst Optical Near-Infrared Detector (GROND; Greiner et al. 2008) mounted at the 2.2-m MPG telescope at the ESO La Silla observatory in Chile.The afterglow was detected in all the optical bands (g r i z ) but not in the near-infrared bands (JHK) during the first epoch of observations at 2.18 days post-trigger (Nicuesa Guelbenzu et al. 2022).The afterglow was detected in only the g and r bands during the second epoch at 3.21 days.The GROND data were reduced using standard PSF photometry through DAOPHOT (Stetson 1987) and IRAF (Tody 1993).The optical data were calibrated to the Pan-STARRS catalogue (Chambers et al. 2016) while the NIR data were calibrated to the 2MASS catalogue (Skrutskie et al. 2006).We present all optical detections of GRB 220627A in Fig. 4.
Optical spectroscopy
Following the detection of the optical afterglow by MeerLICHT, we observed the GRB afterglow region with the Multi-Unit Spectroscopic Explorer (MUSE; Bacon et al. 2010) mounted on UT4 at the ESO VLT.A set of four exposures of 600 s were obtained at 1.17 days post-trigger covering the wavelength range 4800-9300 Å with the corresponding spectral resolution ranging from R ∼ 1800-3500.Data from each exposure was reduced and stacked using standard esorex recipes.Finally, we subtracted the sky background in the reduced data cube using zap (Soto et al. 2016).We extracted a spectrum from the MUSE data cube using a circular aperture of 0.6 .The spectrum is characterised by the presence of a broad damped Lyα absorption feature and the pres- (Izzo et al. 2022).An intervening absorber at z = 2.665 was also identified by the presence of S iv, Si ii, C iv, Fe ii, Al ii lines (Izzo et al. 2022).The white light image, obtained by integrating over the entire wavelength region covered by MUSE, is shown in Fig. 5 along with the resulting spectrum.
Radio
Radio observations with the ATCA and MeerKAT arrays were obtained at 8 and 44 days post-trigger, respectively (Leung et al. 2022;Giarratana et al. 2022).The radio afterglow of GRB 220627A was detected by ATCA with a flux of ∼0.4 mJy at a frequency of 17 GHz at 7.3 days, while no source was detected by MeerKAT in the L band at 8.9 and 35.7 days where the image RMS noise was 9 and 14 µJy for each epoch, respectively.We assume a conservative 33% error on the ATCA flux measurement, and the upper limits as three times the RMS noise (3σ).
All flux measurements and upper limits used in this work are presented in Table 1, where we have converted AB magnitudes to flux densities in µJy.The frequency of each optical filter corresponds to the effective wavelength of that filter, which we obtained from the SVO Filter Profile Service5 for the VLT and GROND filters, while for MeerLICHT and Lesedi we obtained them internally.
External forward shock framework
We interpret our afterglow observations in the framework of the synchrotron external forward shock model (Mészáros & Rees 1997;Sari et al. 1998;Chevalier & Li 2000).In this model, the GRB central engine -usually assumed to be a black hole or neutron star -powers an extremely relativistic, collimated outflow that sweeps up mass in the surrounding circumburst medium, Right: telluric-corrected spectrum (black) and error spectrum (grey) of GRB 220627A extracted from the MUSE data cube using an aperture with a radius of 0.6 .We show identified absorption lines at the GRB redshift (z = 3.084) and the intervening system (z = 2.665) in grey and red, respectively.The vertical shaded region is heavily affected by telluric lines.forming a shock front behind which electrons are accelerated to a power law distribution in energies with N(γ e ) ∝ γ −p e for γ e > γ m , where γ m is the minimum Lorentz factor of the electrons in the distribution and p is the electron spectral index.The electrons produce synchrotron radiation whose emission spectrum is a multi-segment broken power law characterised by three break frequencies: the frequency associated with the peak of the spectrum, ν m , corresponding to electrons with the Lorentz factor γ m in the instantaneous electron distribution; the cooling frequency ν c corresponding to the Lorentz factor beyond which electrons are cooling efficiently by synchrotron radiation over the lifetime of the system; and the self-absorption frequency ν a corresponding to the frequency below which the synchrotron emission is self-absorbed.The ordering and evolution of the spectral breaks with time is dictated by the dynamics of the blast wave.After reverse shock crossing, the decelerating blast wave enters a self-similar regime described by the Blandford-McKee (BM;Blandford & McKee 1976) solution for a spherical, relativistic blast wave expanding into a medium with a density profile n(r) ∝ r −k .From this solution, the spectral flux density is given as a power law of both time and frequency, from which so-called closure relations can be derived relating the temporal and spectral indices within a given spectral regime (Zhang & Mészáros 2004;Zhang et al. 2006;Gao et al. 2013).We consider both a constant density ISM-like medium (k = 0) or a stellar wind medium (k = 2) in the relativistic (BM) regime, as in Granot & Sari (2002).
Evidence for a jet break
Optical detections of GRB 220627A are presented in Fig. 4, separated by observing band.To account for the slight differences in observing filters, we shifted the r-and R-band data to a common frequency of 4.820×10 14 Hz (the GROND r -band effective frequency) using a spectral index of β ≈ −1.This is the approximate spectral index derived from the GROND r , i and z bands at 2.18 days, uncorrected for Galactic extinction.We excluded the g -band detection from the spectral fit as there is a clear dip in the spectral energy distribution (SED) in this band compared to the redder bands, due to rest-frame Lyα absorption (see Fig. 5).
We fitted the light curves in each of the g, q, r, and i bands with two analytic functions: a simple power law (PL), and a smoothly broken power law6 (BPL), constraining the temporal indices and break times (for the BPL) to be the same across each fit.We employed a break smoothness parameter of ω = 9 since smoother breaks result in fits with higher reduced χ 2 values.The BPL fit had a reduced χ 2 value substantially closer to one compared to the simple PL fit (1.30 vs. 1.87).Furthermore, the Bayesian information criterion (BIC) for the two fits gives preference to the BPL model (16.09 vs. 19.86).Figure 4 shows the best-fit BPL model in each optical band.The pre-and post-break temporal indices are α 1 = −1.24± 0.44 and α 2 = −2.17± 0.14, with a break time of t b = 1.23 ± 0.28 days.Our late-time constraint on any host galaxy emission of R > 25.92 mag allows us to place an upper limit to any possible host galaxy contribution to the final R-band detection at 5.09 days of <30%, providing additional support to the steepening observed in the light curve.The BPL model is also compatible with the X-rays, as the data can accommodate the optical light curve fit shifted to the X-ray band (Fig. 4).
in which F 0 is the normalising flux level, α 1 and α 2 are the pre-and post-break temporal indices, t b is the break time, and ω is a smoothness parameter.
At X-ray and optical frequencies, an achromatic steepening of the afterglow light curves from a 'normal' temporal index of α ≈ −1 to a post-break index of α ≈ −2 has often been attributed to the jet break effect.Observationally, jet breaks have been studied extensively (see the sample in Wang et al. 2018).As the blast wave decelerates, a deficit in flux will be observed once 1/Γ > θ j , resulting in a steepening of the light curves.If the jet break is purely due to sharp edges of the jet (e.g., a top-hat jet) coming into view rather than due to lateral spreading or a combination of both, the light curves at all frequencies will steepen by t −3/4 or t −1/2 in an ISM or stellar wind environment, respectively.Rhoads (1999) and Sari et al. (1999) considered sideways expansion of a conical jet and found that the bulk Lorentz factor of the jet decreases exponentially after 1/Γ > θ j , producing a steeper post-jet break decay.For the spectral break ordering with ν a < ν m < ν c (usually relevant when a jet break occurs), Sari et al. (1999) found that the light curves decay as t −p for ν > ν m , t −1/3 for ν a < ν < ν m , and t 0 for ν < ν a .Numerical simulations, however, have shown that sideways expansion should not contribute before Γ has decreased considerably, though post-jet break decay is predicted to be steeper than with the edge effect only so that t −p may be a reasonable approximation (Zhang & MacFadyen 2009;van Eerten & MacFadyen 2012b;Granot & Piran 2012).
The passage of the cooling frequency through the optical bands can in principle lead to a temporal break in optical light curves.For both an ISM and wind medium undergoing slow cooling the difference in spectral index between the spectral segments either side of the cooling break is ∆β = 0.5.Interpolating and extrapolating the R-band light curve fit to the same time as the two X-ray detections, we find that the optical to Xray spectral index either side of the break in the light curve is β O,X ≈ −0.9, indicative of negligible spectral evolution between the optical and X-ray bands during this time.This spectral slope is also consistent with the optical in-band spectral index of β O = −0.91 at 2.18 days, indicating that both bands may lie on the same spectral segment.The difference in decay rate between the regimes either side of the cooling break is |∆α| = 0.25, so that the passage of ν c should not lead to a steepening of more than ∆α = −0.25.We also expect the temporal break to be chromatic, that is it occurs at different times in different observing bands.Our light curves steepen by ∆α = −0.93 ± 0.46, which is too large for the passage of the cooling break but is consistent with a jet break due to the edge effect (∆α = −0.75 in an ISM medium) or lateral spreading (t −p ).Furthermore, the post-break decay index of α ≈ −2.2 is difficult to reconcile within the standard closure relations.The steepest decay rate is expected in the regime with ν m < ν < ν c within a stellar wind scenario, where α = (1 − 3p)/4.An extreme electron power law index of p = 3 would result in α = −2, which is still shallower than our measured value of α ≈ −2.2.It is therefore likely that the break in our light curve is a jet break.We investigate the jet-break scenario further via theoretical modelling in Sect. 4.
Broadband temporal and spectral considerations
The GROND optical spectral energy distribution (SED) at 2.18 days has a spectral slope of β O = −0.91 ± 0.16 as derived from the r , i and z bands (The JHK near-infrared bands did not constrain the spectral slope) corrected for Galactic extinction using the Milky Way extinction curve from Fitzpatrick (1999) with R V = 3.1 and A V = 0.13 mag for the GRB line of sight (Schlafly & Finkbeiner 2011).We note that these observing bands correspond to rest-frame ultraviolet (UV) wavelengths A32, page 7 of 17 de Wet, S., et al.: A&A 677, A32 (2023) at the redshift of GRB 220627A (z = 3.08), so that the intrinsic spectral slope may be shallower than this value if there is significant host-galaxy extinction.The X-ray spectral index from our fit in Sect. 2 was β X = −0.73+0.57−0.77 .We calculate an optical to X-ray spectral index at the time of the second X-ray detection at 1.59 days by interpolating our r-band fit to this time.We take the mean relative error in our r-band flux measurements as the error on the interpolated r-band flux, approximately 10%.We measure a spectral index of β O,X = −0.93 ± 0.08, which is consistent with the GROND spectral index of β O = −0.91±0.16.With even moderate host-galaxy extinction, we would expect this to set an upper limit on the optical to X-ray spectral index, such that a value β ≈ −1 is likely from optical to X-ray frequencies.
Due to a paucity of data, we are not able to estimate the location or evolution of the cooling break, ν c .It is therefore difficult to perform an accurate closure relation analysis to determine the circumburst medium density profile and electron energy spectral index p.Nevertheless, if we start with the assumption that p ≈ 2.2 based on a post-jet break decay of α 2 = −2.17± 0.14, we can draw some broad conclusions.In the slow cooling regime (ν m < ν c ) we have spectral slopes of β = (1 − p)/2 and β = −p/2 below and above ν c , respectively.Assuming p ≈ 2.2, we would have β ≈ −0.6 and β ≈ −1.1 below and above ν c .Our optical to X-ray spectral index of β ≈ −1 therefore appears more consistent with being in the spectral regime above ν c .With p = 2.2, the expected light curve decay rate in this spectral regime is α = (2 − 3p)/4 = −1.15,which is fully consistent with the pre-break temporal index of α = −1.24± 0.44 from our optical light curve fit.In an ISM environment, ν c moves to lower frequencies as t −1/2 , while in a stellar wind environment ν c is expected to rise as t 1/2 (Granot & Sari 2002).The most plausible 7 scenario is that we are in an ISM environment where ν c has already moved below the optical observing bands at the time of our measurement of β O,X at 1.59 days.
The radio data consists of a single detection at 7.3 days at 17 GHz, and two non-detections in the L band (1.4 GHz) at 8.9 and 35.7 days.If we assume that the MeerKAT upper limit at 8.9 days also holds at 7.3 days, we can constrain the spectral slope between the L band and 17 GHz (Ku band) to β L−Ku 1.07 at 7.3 days.This implies that the spectrum is likely synchrotron self-absorbed at GHz frequencies.
Since we cannot precisely constrain the location of ν m , ν c , or ν a , there are likely to be extensive model degeneracies when performing theoretical modelling, as shown in Sect. 4.
MUSE spectroscopy
The huge photon flux emitted by early GRB afterglows allows us to investigate the composition of the immediate environment surrounding the GRB progenitor star (Savaglio et al. 2003;Jakobsson et al. 2004;Fynbo et al. 2006;Prochaska et al. 2007;Heintz et al. 2018;Bolmer et al. 2019;Saccardi et al. 2023).This is one of the main motivations to get an optical/near-IR GRB spectrum as soon as an optical counterpart has been identified.Early GRB afterglow spectra have shown the presence of neutral and singly-ionised low-excitation metal absorption lines, such as O i, C ii, Si ii, S ii, Fe ii, Ni ii, Zn ii, Al ii, and Al iii (Vreeswijk et al. 2007).In several cases, fine structure and meta-stable levels of Si ii and Fe ii have also been detected 7 We cannot conclusively rule out a wind environment with ν c below the optical since the optical light curve spans less than a single decade in time which corresponds to a change in ν c by a factor of ∼3 given a t 1/2 evolution.( D'Elia et al. 2007).The study of these absorption features can provide us with information on the metallicity of the immediate GRB region, while from the estimate of the column densities N X , with X being the element under consideration, one can also obtain a rough estimate of the extinction A V along our line of sight (De Cia et al. 2016).Due to their large redshifts, GRB afterglows are therefore one of the most important tools for investigating the evolution of the properties of the ISM in long GRB host galaxies, and consequently, in star-forming galaxies over a large redshift range.
The HI column density in GRB 220627A is derived by modelling the broad Lyα absorption trough with a Voigt profile using VoigtFit (Krogager 2018).This code convolves the intrinsic model with the spectral resolution and determines the redshift z, broadening parameter b, and column density N, of the input lines.Due to the substantial column density of HI, the Lorentzian wings dominate the line profile allowing for accurate estimates of the column density.We derive a best-fit log(N HI /cm −2 ) = 21.15 ± 0.05 (see Fig. 6).
We also attempt to measure the column densities of the main elements identified in the MUSE spectrum (Fig. 7).To this aim, and given the spectral resolution of MUSE, we have used the curve of growth (CoG) methodology, which provides a relation between the equivalent width (EW) of ISM lines and the corresponding column densities (Spitzer 1998).For low EW values (<0.1 Å), the EW is directly proportional to the column density, while for larger values the situation is complicated by saturation effects.The dependence of the EW from the column density is also related to the Doppler parameter b, which could not be very well constrained with the spectral resolution provided by MUSE.However, if we identify at least two absorption lines originating from the same electronic transition of the same ion (such as Si ii 1260, 1808 Å), we can roughly estimate the b value from their EWs, given that these lines have the same column density.Then, under the assumption that the curve of growth of ions with similar excitation potential is described by the same Doppler parameter, we can estimate their column density from their rest-frame EW. Figure 8 shows the results of our methodology.The majority of the lines used for the analysis are consistent with the CoG determined using Si ii lines, with the interesting exception of S ii.We also note that we have not applied any correction for dust depletion, which can considerably affect ions such as Fe ii.2012), we estimate metal abundances assuming that ions with ionisation potentials just above the ionisation energy of hydrogen constitute the dominant ionisation level, and finally give an estimate for the element abundance.We also do not include any ionisation correction given that this is negligible in Damped Lyman α (DLA) systems (Jenkins 2009), and especially when log(N HI /cm −2 ) > 10 20.5 (Péroux et al. 2007), as with GRB 220627A.To determine the metallicity, we derive the relative metal to hydrogen abundances in the GRB afterglow spectrum assuming Solar values provided by Asplund et al. (2009).The metallicity is then determined as [X/H] = log(N X /N H ) GRB − log(N X /N H ) for each element identified in the GRB spectrum.In Table 2 we report our final estimates of [X/H] for each ion identified in the GRB spectrum.In Fig. 9 we compare our results with the distribution of absorption-derived GRB and QSO-DLA metallicities (Rafelski et al. 2012;Thöne et al. 2013;Bolmer et al. 2019;Saccardi et al. 2023), where [X/H] is mainly derived from the S ii and Si ii ions, which are also the faintest detected lines in the GRB 220627A spectrum, see also Fig. 7.We further notice that for the estimate of the metallicity from S ii lines, we have used the S ii 1253 Å transition, given that the other line visible in the spectrum, S ii 1250 Å, is strongly blended with Si iv 1394 Å from the intervening absorber.The environment of GRB 220627A is characterised by a typical sub-solar GRB afterglow metallicity.Prochaska (2006) discussed this methodology comprehensively and concluded that column densities obtained using low-resolution spectra are likely to be underestimated due to instrumental line broadening and consequent blending of more intrinsically narrow absorption components.This is particularly true when metal absorption lines display heavily saturated profiles.In the case of GRB 220627A, we are also limited by the low spectral resolution provided by MUSE, which is not suitable to study ISM lines with smaller Doppler parameters.With these prescriptions, the metallicity values determined above must be considered as lower limits, especially for oxygen and carbon that can be heavily saturated.However, we also note that in the very few cases where GRB afterglows have been studied with both high-and low-resolution data, the results obtained using analysis based with Voigt-line profile fits and with the CoG method were fully in agreement (D'Elia et al. 2011).
Theoretical afterglow modelling
We perform theoretical afterglow modelling to determine the physical blast wave parameters of the forward shock, with the A32, page 9 of 17 de Wet, S., et al.: A&A 677, A32 (2023) aim of establishing whether the afterglow properties of this ultralong GRB are unusual compared to the wider GRB population.
Model
We make use of the ScaleFit software package to perform theoretical modelling of our broadband afterglow dataset (Ryan et al. 2015;Aksulu et al. 2020Aksulu et al. , 2022)).ScaleFit is based on the BoxFit set of high-resolution hydrodynamic simulations of GRB explosions (van Eerten et al. 2012).Boxfit interpolates between a series of compressed data sets of hydrodynamical jet simulations and employs scale invariance between the blast wave energies and circumburst medium densities to cover the space of afterglow parameters, rapidly computing light curves and spectra using a linear radiative transfer module.Scalefit builds on this by making use of simple scaling laws between a set of scale-invariant characteristic quantities to derive the full set of spectral parameters that determine the observed emission (van Eerten & MacFadyen 2012a).The characteristic quantities are computed and tabulated directly from the BoxFit simulations, allowing for nearly instantaneous calculation of afterglow light curves and spectra given an arbitrary set of blast wave parameters.The initial conditions for the BoxFit simulations are the Blandford-McKee radial profile truncated to the opening angle of the jet θ j .ScaleFit is therefore only suitable for the deceleration phase after reverse shock crossing and so cannot be used to model energy injection, plateaus or flares.
The jet break and non-relativistic (Sedov-Taylor) transitions are both well-handled by ScaleFit (van Eerten & MacFadyen 2012a).ScaleFit can be used to model both an ISM or stellar wind medium, and accepts ten free parameters: explosionrelated parameters including the isotropic-equivalent blast wave energy E K,iso , circumburst medium density n 0 , and opening angle of the jet θ j ; shock microphysics parameters including the electron energy distribution spectral index p, the fraction of accelerated electrons within the shock ξ N , and the fractions of shock internal energy partitioned to electrons and magnetic fields, e and B , respectively; and observer-related parameters including the burst redshift z, luminosity distance d L , and observer angle with respect to the jet axis θ obs .
We use the emcee Python package (Foreman-Mackey et al. 2013) to implement a Markov chain Monte Carlo (MCMC) exploration of our ScaleFit model parameter space.An MCMC analysis allows for correlations (and degeneracies) between parameters to be readily identified.Furthermore, the uncertainty on each parameter can be determined through marginalisation of the posterior distribution.emcee offers advantages over traditional MCMC samplers because its multiple 'walkers' moving through the parameter space make it affineinvariant, with the result that it is unaffected by covariances between parameters.For GRB afterglow modelling, if a large majority of the measured data points are in a single spectral regime (e.g., at optical and X-ray frequencies) the location of the spectral breaks will not be well constrained, and so there are likely to be strong correlations between the E K,iso , n 0 , e and B parameters.
In order to reduce the number of free parameters when fitting, we fix the burst redshift at the MUSE value of z = 3.08 (Sect.2.5) and the luminosity distance at 8.25 × 10 28 cm, computed using our adopted cosmology (Sect.1).The fraction of shock-accelerated electrons ξ N is degenerate with respect to the parameters {E K,iso , n 0 , e , B } (Eichler & Waxman 2005), so we make the common assumption that ξ N = 1.We further assume that the observer is looking directly down the axis of the jet (θ obs = 0).We account for Galactic extinction using the Milky Way extinction curve from Fitzpatrick (1999) with R V = 3.1 and A V = 0.13 mag for the GRB line of sight (Schlafly & Finkbeiner 2011).The host galaxy extinction is a free parameter in our modelling, where we employ the Small Magellanic Cloud (SMC) extinction curve from Pei (1992) at the burst redshift since the vast majority of GRB host galaxies are consistent with an SMC extinction law (Schady et al. 2010;Zafar et al. 2011).We assume that the flux blueward of the rest-frame Lyman limit (912 Å) is totally absorbed.For both Galactic and host extinction we employ the astropy-affiliated dust_extinction8 Python package to redden our model SEDs.
In total we have seven free parameters denoted by the vector Θ: (1) Given a data set D of flux measurements at frequencies ν i and times t i , the posterior probability p(Θ|D) is proportional to the product of the likelihood p(D|Θ) and the prior p(Θ) via Bayes' Theorem To account for both detections and non-detections in our data, we employ the likelihood function for Gaussian errors used by Laskar et al. ( 2014) where δ i is equal to one for a detection and zero for an upper limit, e i are the residuals p(e i ) is the probability density function of the residuals, and F(e i ) is the cumulative distribution function of the residuals.The two functions p(e i ) and F(e i ) take the form and respectively, where σ i are the errors on the flux measurements or upper limits.As in Laskar et al. (2014), we also enforce a floor of 5% on the measured flux errors so as not to give undue weight to very high S/N measurements (usually those at optical wavelengths).
ScaleFit requires certain parameters to be transformed into dimensionless values in log space in order to improve performance when fitting.The energy E K,iso is transformed into dimensionless units of log 10 53 erg, and the quantity log ¯ e is used by ScaleFit rather than log e .The two quantities are related via The circumburst medium density n 0 is defined as the number of particles per cm 3 at the reference distance of 10 17 cm from the GRB central engine.In a stellar wind medium the circumburst medium has a density profile following ρ(r) = Ar −2 .
Chevalier & Li (2000) define a dimensionless A parameter according to A = A/(5 × 10 11 g cm −1 ).The n 0 parameter is therefore related to A via We employ wide, uninformative log-uniform priors on all parameters except for p and A V,host , for which we use uniform priors (see Table 3).The jet opening angle is restricted to a range varying from a very narrow jet (θ j = 0.6 • ) to a spherical jet (θ j = 90 • ).Our priors are equivalent to those used by Aksulu et al. (2022).During our emcee run we utilise 1000 walkers performing 2000 steps through the parameter space.The initial state of the walkers are clustered around the values from a Maximum-Likelihood fit performed using the scipy package.We discard the initial 200 steps as burn-in.We performed the MCMC analysis in both an ISM and stellar wind circumburst medium and calculated log likelihoods of ln P(Θ ISM |D) = 124.9+1.6 −2.2 and ln P(Θ Wind |D) = 120.0+2.5 −3.8 for each medium, respectively.Assuming both an ISM and stellar wind medium have equal prior probabilities of fitting our data, the Bayes factor is simply the likelihood ratio between the two models.We therefore derive a Bayes factor of 134.29 in favour of an ISM environment.According to Kass & Raftery (1995) a Bayes factor >100 provides decisive evidence in favour of one model over another, so we only show the results of our ISM modelling henceforth.For completeness we present the results of the wind modelling in Appendix A.
Results
Figure 10 shows the marginalised distributions and correlations between pairs of parameters, and Table 4 presents the median values along with their 1σ uncertainties derived from the marginalised distributions.For the electron spectral index
Parameter
Prior Distribution we derive a value of p = 2.00 +0.08 −0.06 .This value is consistent within uncertainties with the value for p derived from the postjet break decay index of p = α 2 = 2.17 ± 0.14 in Sect.3.2.Furthermore, the model associated with the median values for each parameter (bold lines in Fig. 11) has ν c below the optical and X-ray regimes during our observations, consistent with the argument in Sect.3.3 based on the optical spectral index.This model has ν a ≈ 10 12 Hz until ν m crosses ν a at 0.13 days, whereafter the afterglow spectral breaks are ordered ν m < ν a < ν c .The single radio detection at 17 GHz and MeerKAT nondetections at 1.4 GHz are unable to constrain the location of ν m and ν a precisely, and as a result there are strong degeneracies between E K,iso , n 0 , ¯ e and B , as expected.In contrast, the jet-opening angle is well-constrained to 4.5 +1.2 −0.3 deg and is driven by the clear break in the optical light curves as discussed in Sect.3.2.The corresponding beaming correction of f b = (1 − cos θ j ) = 3.1 +1.8 −0.3 × 10 −3 results in a beaming-corrected prompt γ-ray energy of E γ = 1.5 +0.9 −0.2 ×10 52 erg and kinetic energy of E K = 3.1 +20.3 −2.5 × 10 51 erg.The radiative efficiency of a GRB is defined as (Lloyd-Ronning & Zhang 2004) from which we derive a high radiative efficiency of η γ ≈ 84%.As mentioned in Sect.4.1, assuming ξ N = 1 means that our derived kinetic energy is actually a lower limit on the true energy, and therefore this calculated radiative efficiency is actually an upper limit.We note also that the uncertainty on E K is rather large due to degeneracies in our theoretical modelling.Taking into account the uncertainties in E K and E γ , we derive a 1σ range of 39−97% for η γ .Wang et al. (2015) find that radiative efficiencies peak at ∼6% with the 1σ range extending up to ∼40%, though they still have a very wide distribution extending to almost 90%, fully consistent with our derived value.
Discussion
The defining feature of GRB 220627A is its two distinct prompt γ-ray emission episodes separated by ∼600 s, resulting in a total burst duration of ∼1090 s.At a redshift of z = 3.08, GRB 220627A is the most distant ultra-long GRB detected to date.We now discuss whether the prompt and afterglow emission are typical for normal long GRBs.
Prompt emission properties
Based on the sample of long GRBs fitted with cutoff power laws in the Fermi-GBM Gamma-Ray Burst Spectral Catalog, indices of Γ = 1.01 +0.39 0.35 and peak energies of E p = 205 +374 −109 keV.The prompt emission spectral parameters of GRB 220627A (see Sect. 2.2) are fully consistent with these distributions.For the first emission episode, an additional power law spectral component extending up to higher energies (>100 MeV) is needed to explain the LAT emission.Such a feature has been observed in several other long GRBs (e.g., GRBs 090902B, 090926A; Abdo et al. 2009;Ackermann et al. 2011).The spectral properties of GRB 220627A are therefore not unusual compared to the long GRB population.The temporal features, however, are rare though not unprecedented, and we discuss these further in Sect.5.3 below.
Afterglow properties
Most of our model parameters derived from our theoretical modelling (Sect.4.2) are typical values within the literature.Our value of p is within the 1σ range found by Wang et al. (2015) of p = 2.33 ± 0.48.Wang et al. (2015) also find that the typical isotropic kinetic energy for GRBs without energy injection is log(E K,iso /erg) = 54.66 ± 1.18.Our inferred kinetic energy of E K,iso = 9.0 × 10 53 erg is well within their sample range.Our circumburst medium density of 19 cm −3 agrees within the range of 0.06−26 cm −3 found by Aksulu et al. (2022) almost five orders of magnitude from 10 −5 −10 −1 .Our value of B ≈ 5 × 10 −3 is close to their median value of 1.0 × 10 −2 .We are unable to determine a physical value for e using Eq. ( 7) since p = 2 results in ¯ e = 0. Values of p less than two have been suggested in the literature (Panaitescu & Kumar 2002;Dai & Cheng 2001) and have been found through modelling of actual GRB datasets (Aksulu et al. 2022).As discussed in Granot & Sari (2002), using ¯ e is still valid when p < 2 as long as γ m is proportional to the shock Lorentz factor; a high-energy cutoff in the electron energy distribution is then needed so that the total energy in electrons is bounded.Wang et al. (2015) found that the jet opening angle takes values of θ j = 2.5 ± 1.5 deg.Our value of 4.5 +1.2 −0.3 deg is just outside their 1σ range, but well within the range of the sample considered by Laskar et al. (2014) having θ j = 7.4 +11 −6.6 deg.The afterglow properties derived from our theoretical modelling are fully consistent with long GRBs, and do not suggest a different or unusual progenitor.The large distance to GRB 220627A means that we are also unable to shed light on the progenitor through observations of a possible supernova (e.g., SN 2011kl accompanying the ultra-long GRB 111209A; Greiner et al. 2015) or another thermal transient.The findings presented here cannot exclude that GRB 220627A has a different progenitor compared to normal long GRBs.
GRBs with widely-spaced emission episodes
Among ultra-long GRBs, GRB 220627A is one of an even smaller subset of GRBs with distinct γ-ray emission episodes separated by long quiescent periods.Virgili et al. (2013) compared the ultra-long GRB 091024A with a sample of 11 other bursts having durations >1000 s and divided ultra-long GRBs into those with continuous prompt γ-ray emission, and those with distinct emission episodes separated by long quiescent periods (so-called interrupted bursts).They pointed out that the total duration of interrupted bursts holds less significance than for continuous bursts, since long quiescent intervals between sub-bursts may not accurately reflect the duration of central engine activity.They identified four bursts with interrupted emission: GRBs 020410A, 080407A, 091024A, and 110709B.Since then, three GRBs have triggered Fermi/GBM twice as listed in the Fourth Fermi/GBM Gamma-Ray Burst Catalog (von Kienlin et al. 2020): GRB 130925A, GRB 150201A, and GRB 160625B.Although GRBs 110709B and 160625B are not strictly ultra-long due to having durations <1000 s, we still include them in this sample since they are close to 1000 s and have widely-spaced emission episodes.Some properties of these bursts including GRB 220627A are presented in Table 5, similar to Table 6 in Virgili et al. (2013).We now discuss the prompt and afterglow properties of these bursts in order to determine if they share any unifying characteristics.
GRB
Duration (a) z Fluence (b) Energy range (c) E γ,iso Episodes (e) GeV ( f ) Afterglow Notes. (a) Approximate duration of γ-ray activity across all emission episodes. (b) Fluence as measured across all emission episodes. (c) Energy range over which reported fluence was measured. (d) We assume z = 1 to calculate E γ,iso for bursts without measured redshifts.The prompt emission light curves for all eight bursts are diverse in their morphology.Some bursts have weak precursorlike episodes preceding the main episode which contains the majority of the total fluence (GRBs 091024A, 130925A, 160625B), while others have brighter initial episodes (020410A, 080407A, 150201A, 220627A).GRB 110709B has two emission episodes of similar brightness.All bursts appear to show hard to soft evolution across the whole duration of γ-ray activity, a common trait for the wider GRB population.GRB 220627A is the most distant of all these bursts, and has the highest isotropic γ-ray energy.The bursts in Table 5 span almost two orders of magnitude in E γ,iso , comparable to the range of energies of the normal long GRB population (see Fig. 19 in Poolakkil et al. 2021).GRB 220627A is also one of only two bursts that has been detected at GeV γ-ray energies by Fermi/LAT.
The prompt emission light curve of GRB 220627A is most similar to that of GRB 110709B, a so-called double burst which triggered Swift/BAT twice separated by an interval of 11 min.Zhang et al. (2012) studied the prompt and X-ray emission in detail and ruled out a gravitational lensing and a giant X-ray flare origin for the second sub-burst.Their preferred physical explanation for the two sub-bursts with a long quiescent period in between was a magnetar to black hole (BH) scenario, where the first sub-burst is produced by a newly-formed magnetar releasing rotational energy via a magnetised jet, and the second, softer sub-burst is produced by a slower jet once the magnetar has collapsed to a BH.GRB 160625B was an extremely bright burst with three distinct emission episodes which were studied in great detail by Zhang et al. (2018).The first, short precursor episode was thermal-dominated, while the latter two episodes were consistent with synchrotron emission.This spectral transition was interpreted as direct evidence of the GRB jet changing its composition, with the first thermal component associated with the initial core collapse and break out of the ejecta from the surface of the Wolf-Rayet progenitor.For a black hole central engine the quiescent phase prior to the main emission was suggested to be a result of a magnetic barrier delaying accretion until enough material has built up (Proga & Zhang 2006), while for the magnetar engine the delay may be a result of the hot proto-magnetar taking time to dissipate energy before launching an outflow (Komissarov & Barkov 2007;Metzger et al. 2011).
Thereafter, a Poynting-flux dominated outflow characterised by synchrotron emission would be launched.Due to the weakness and short duration (T 90 ∼ 0.84 s) of the thermal precursor emission, the authors noted that such a feature would not have been observable had GRB 160625B been more distant.Such a feature may have been observed in GRB 220627A had it been closer.Based on 3D simulations, Gottlieb et al. (2022) proposed that the observed quiescent periods of ∼1−100 s in prompt emission light curves are naturally explained by a time-varying tilt of the central engine, such that quiescent periods correspond to times when the jet axis is pointed away from the observer.The much longer quiescent period of ∼600 s for GRB 220627A, however, may exclude this scenario.
In terms of afterglow emission, almost all of the bursts in Table 5 were detected in X-rays, and their X-ray luminosities are comparable to the majority of the GRB population (see Fig. 12).Levan et al. (2014) regarded the presence of X-ray flares as a defining feature of ultra-long GRBs.GRBs 110709B and 130925A show evidence for X-ray flares, though in the cases of GRBs 091024A and 160625B Swift/XRT was unable to observe at early times, so any flares may simply have been undetected (Fig. 12).GRB 150201A does not show any X-ray flares, despite there being early-time data.GRB 220627A was not localised until 0.84 days, so no search for flaring could be conducted.GRB 130925A is the nearest of the ultra-long GRBs in the sample and also has the longest duration measured in γ-rays.Its X-ray afterglow showed many large flares, similar to those of the ultra-long GRBs studied by Levan et al. (2014).Evidence for a thermal emission component was found in the X-ray spectra and was interpreted as photospheric emission from the GRB fireball (Piro et al. 2014).Such thermal emission has been observed in a number of other X-ray flares (Peng et al. 2014).Evans et al. (2014) suggested that the lack of external shock X-ray emission implied a low circumburst density, which could explain the ultra-long γ-ray duration since the deceleration time and radius would be larger, allowing more ejected shells to interact and produce prompt emission before reaching the external shock.The radio emission from GRB 130925A proved challenging to explain in a normal forward shock afterglow model (Horesh et al. 2015).GRBs 091024A, 130925A, and 160625B were all detected and localised by Swift/BAT A32, page 14 of 17 de Wet, S., et al.: A&A 677, A32 (2023) and were therefore monitored from very early times at optical frequencies.
In summary, GRBs with widely-spaced emission episodes show a wide variety of prompt and afterglow features.More observations of such bursts are needed in order to determine if there are unifying characteristics that distinguish them from single-emission episode bursts.
Conclusion
GRB 220627A is an ultra-long GRB that triggered Fermi/GBM twice separated by a 956 s time interval.High-energy GeV γ-rays were detected by Fermi/LAT in coincidence with the first emission episode which led to the discovery of the optical afterglow with MeerLICHT at 0.84 days.Optical spectroscopic observations with MUSE were used to deduce the burst redshift of z = 3.08, making GRB 220627A the most distant ultra-long GRB observed to date.From our optical follow-up observations we identified a temporal break in the light curve at ∼1.2 days which we interpret as a jet break.From our spectroscopic measurements we found that the environment of the burst is consistent with a sub-solar metallicity typical of DLA systems and other GRB afterglows.Combined with publicly-available X-ray and radio data, we performed broad-band theoretical modelling of the afterglow data and found preference for a homogeneous circumburst medium.Our most well-constrained parameter is the jet opening angle, which we constrain to θ j = 4.5 +1.2 −0.3 deg.All our parameters are typical for long GRB afterglows.Our observations of this ultra-long GRB do not require a different progenitor compared to normal long GRBs as suggested by some authors, though we cannot exclude this possibility.More observations of bursts with widely-spaced emission episodes are needed to determine if they form a separate population with distinct prompt and afterglow features.
Fig. 1.Localisation of GRB 220627A.Left: 50% and 90% uncertainty regions for both GBM triggers associated with GRB 220627A are outlined in purple.A total of 52 MeerLICHT fields (grey boxes) were automatically scheduled for observations immediately following the first trigger.Following the announcement of the Fermi/LAT localisation region (red circle), two MeerLICHT fields (orange boxes) were scheduled for observations the following night.Top right: Swift/XRT ToO observations identified 15 X-ray sources within the LAT error box.MeerLICHT identified a new optical transient within the error box of the third 'good' XRT source (yellow diamond).Bottom right: first MeerLICHT detection of the new transient (left), and an archival image taken two months previously on 2022 April 26 (right).Both thumbnails are 1 × 1 in dimension.
H = 4
.90 × 10 20 cm −2(Willingale et al. 2013) and fixing the source redshift to z = 3.08.From our fit we derive a host column density of N host H = 3.75+7.83−3.74 ×10 22 cm −2 and a photon index of Γ = 1.73 +0.78 −0.51 Fig.4.X-ray and optical light curves associated with GRB 220627A, organised by observing band and instrument.MeerLICHT is abbreviated to ML in the legend.The vertical grey region denotes the time of the MUSE spectroscopic observations.We show the broken power law fits to each of the g, q, r and i bands, where the break time and temporal indices were constrained to be the same across each fit.Residuals are shown in magnitudes in the lower panel.We show the two X-ray detections as crosses and the single upper limit as an upside-down triangle.The dotted line is the optical light curve fit shifted vertically to the X-ray band.
Fig. 5 .
Fig. 5. MUSE spectroscopy of GRB 220627A.Left: white light image resulting from the final MUSE data cube.The GRB afterglow is clearly visible at the centre of the image.Right: telluric-corrected spectrum (black) and error spectrum (grey) of GRB 220627A extracted from the MUSE data cube using an aperture with a radius of 0.6 .We show identified absorption lines at the GRB redshift (z = 3.084) and the intervening system (z = 2.665) in grey and red, respectively.The vertical shaded region is heavily affected by telluric lines.
Fig. 7 .Fig. 8 .
Fig. 7. Absorption lines of S ii and Si ii used in the CoG analysis.We show in grey the Si iv lines from the intervening absorber at z = 2.665.The Si iv 1394 line from the absorber is blended with the Si ii 1250 line.The purple horizontal line denotes the telluric correction applied to the spectrum, shifted vertically up by 1.4 flux units.
Fig. 9 .
Fig.9.Metallicities obtained from the analysis of S ii and Si ii absorption lines in GRB afterglows (orange points;Thöne et al. 2013;Bolmer et al. 2019;Saccardi et al. 2023) compared with the corresponding [X/H] values obtained from the same elements in GRB 220627A (green and red data), as a function of redshift.We also show the absorption-derived metallicity values for a large sample of QSO-DLA systems (grey points;Rafelski et al. 2012;De Cia et al. 2016;Saccardi et al. 2023).
Fig. 10 .
Fig. 10.Corner plot from our MCMC implementation showing the 2D marginalised distributions between pairs of model parameters along with the marginalised distributions for each individual model parameter.Contours denote the 1σ, 2σ and 3σ levels while the red lines denote the median values from the marginalised distributions for each model parameter.Uncertainties on each parameter are at the 16th and 84th (1σ) percentile.
for long GRBs in ISM environments.Santana et al. (2014) found that B spans A32, page 12 of 17 de Wet, S., et al.: A&A 677, A32 (2023) Table4.Parameter values derived from our theoretical modelling.We report the median values and 68% confidence intervals derived from our marginalised distributions in Fig.10.
Fig. 11 .
Fig. 11.All afterglow flux measurements presented in Table1along with 100 random models drawn from our MCMC exploration of the parameter space.The bold lines represent the model associated with the median values from the marginalised posterior distributions in Fig.10.Upper limits are shown as upside-down triangles.
Fig
Fig.12.X-ray luminosities as a function of rest-frame time for all Swift/XRT-detected bursts in Table5.For GRBs without redshifts (110709B and 150201A) we assume z = 1.The grey colour bar denotes the fraction of Swift/XRT-detected afterglows with known redshifts crossing each luminosity-time bin.
Table 1 .
X-ray, optical and radio observations of GRB 220627A used in this work.
Table 2 .
Metallicity computed from the MUSE spectrum and using the CoG method for metal lines.
Table 3 .
Priors on parameters in Θ used in our MCMC analysis. | 15,611.4 | 2023-07-17T00:00:00.000 | [
"Physics"
] |
New geNera for two poorly-kNowN millipeds from Bahia (polydesmida: Chelodesmidae)
Two chelodesmid millipeds described by Brölemann (1903) from the interior of Bahia have not been reported for over 100 years despite their large size and bright coloration. Originally described as Leptodesmus gounellei and Leptodesmus carminatus, neither species is referable to Leptodesmus as currently defined nor any other established genus. Both have been studied from the type specimens, and are here designated the type species of two new genera, Plectrogonodesmus for gounellei and Baianassa for carminatus. Diagnostic characters are illustrated for both taxa. Intergeneric relationships are at present not evident, and are not suggested pending better understanding of the chelodesmid fauna of eastern Brazil. Key-Words: Diplopoda; Polydesmida; Chelodesmidae; New genera; Brazil: Bahia.
IntroductIon
Prior to about 1934, when Otto Schubart emigrated to Brazil from Germany and began to study the diverse fauna of Neotropical millipeds, the great majority of species now referred to the family Chelodesmidae had been described in a genus Leptodesmus, an ensemble of appalling heterogeneity.As he studied numerous collections from many parts of Brazil, Schubart quickly appreciated the great variety of the endemic chelodesmid fauna, and proposed no fewer than 23 new generic names to reflect the structural variability of these animals.
During this period of taxonomic refinements, Schubart was generally concerned with the placement of new species that came to his attention, and less involved with clarification of species described in Leptodesmus by European authors as far back as 1859 (nor was it always easy to borrow type specimens from European museums).As a result, a substantial number of enigmatic taxa were by default more or less bypassed and continued to infest the literature.
One major fundamental problem unresolved during Schubart's investigations concerned the characteristics and status of Leptodesmus itself.The name was originally proposed (DeSaussure, 1859) as a subgenus of Polydesmus, and contained five species only two of which were chelodesmids.One of them, P. (L.) carneus DeSaussure, 1859, was designated type of Leptodesmus by Pocock in 1909, but how the genus was to be defined in the light of future information was not addressed until Hoffman (1971) on the identity of Leptodesmus.At that time my provisional diagnosis admitted 21 species sharing several traits in gonopod structure.
The consequence of that exclusive delimitation was to leave the great majority of names proposed in Leptodesmus (ante Schubart) "homeless" in the sense of not being referable to any established generic taxon.
Having had the opportunity to study type material of many such orphans in the Brazilian fauna, I have on several occasions been able to clarify their identify and status, and now wish to call attention to two species described by Brölemann (1903) from Bahia, and to my knowledge not reported, aside from inclusion in lists, for 108 years.Since the abundance of unstudied material now available is offset by the paucity of qualified taxonomists, progress can only be piecemeal and opportunistic.While such an approach is certainly not the optimal way to an adequate comprehension of any taxon or faunal unit, the two species involved are not relevant to any generic or tribal revisions currently in progress and, being large and conspicuous elements in the Bahian fauna, deserve to be entered in the mainstream of ongoing knowledge.
Name: A neologism composed of the Greek elements plektron (a spur) + gonos (denoting the male reproductive appendage) + -desmus (a combining suffix widely employed throughout the order, from the original Polydesmus).Masculine.
Diagnosis: Body size large, length to near 70 mm.Among the known genera with enlarged gonopod aperture and prominent sclerotized median gonosternal sclerite, this new genus is characterized by the elongated paramedian processes of the 4 th segment in males, by small paramedian sternal lobes on segments 13-17 in males, by the greatly extended lateral prolongation of the gonopod coxa, and especially by the unusually long and etiolated elements of the telopodite.The efferent groove, visible for its entire length in mesal aspect, terminates on a long, slender subterminal solenomere.
Species: Only the type species is known.
Distribution:
The genus is known only from the type locality of the single included species, in the interior of the state of Bahia.
Comment:
The large black and yellow milliped named Leptodesmus gounelli by Brölemann in 1903 from a single male collected in the "Sertão" of Bahia, has apparently not been subsequently documented nor represented in museum collections normally holding these arthropods.The species was described in great detail and amply illustrated, with sufficient information to preclude its accommodation in Leptodesmus as currently defined, nonetheless it has remained an enigmatic, unplaced waif in the Brazilian fauna.Study of the holotype has disclosed additional structures not specified by Brölemann that confirm separate generic status for this striking species.
The unusually large gonopod aperture and sclerotized, bilobed, median sternal element suggest the form characteristic of the genera Eucampesmella Schubart, 1955, Leiodesmus Silvestri, 1987, and Euthydesmus Silvestri,1902, and it is perhaps to this last genus that we may look for a near relative despite the disparity in their ranges (E.acicarina Silvestri occurs in Mato Grosso do Sul).Structure of the undescribed female genitalia in all these chelodesmids may be decisive in developing a classification.
Material: The holotype has been examined.
Diagnosis: With the characters of the genus, further specific characters may be distinguished in the configuration of the gonopods when additional species are discovered.
Description (abstracted from original text): Body large, length 68 mm, width of 3 rd tergum, 10.8 mm, of 9 th tergum, 10.8 mm (prozonal diameter 6.8 mm) sides of body parallel, abruptly narrowed posteriad.Very dark reddish brown, almost black, with the peritreme and adjacent surface of the paranotum yellow.
Head somewhat shiny, divided by a well-defined suture extending between the antennae, and bearing up to their level a weak subtriangular depression.Antennae very long (12 mm) and slender, exceeding the posterior border of the 3 rd paranotum, not reflexed distally, antennomeres long and slender.
Collum much wider than the head, almost as broad as the following tergum, anterior border weakly arcuate medially, lateral ends narrowed to acute angle.Surface of metaterga dull, without transverse sulcus or seriate tubercles.Paranota well developed, placed at midheight of segments, a little declivous, continuing convexity of metaterga.Anterior corners broadly rounded, posterior obtusely rounded on anterior segments, becoming right-angled at midbody and increasingly acutely produced in going posteriad.Ozopores located in the posterior third of marginal peritremata, which form the posterior paranotal corner on all segments, and virtually the entire paranotum on segment 19 (Fig. 1).
Sterna broad, slightly elevated, with two paramedian projections between the posterior legpair of each postgonopodal segment (Fig. 2), anterior surface sparsely setose.Legs long and slender, the tibiae without apical subtarsal pads; pregonopodal legs without modifications.Sternum of segment 4 with two contiguous long processes (Fig. 3), sternum of segment 6 deeply concave for accommodation of the gonopodal apices.Gonopod aperture (Fig. 4) large, transversely oval, extending nearly to anterior edge of segment 7, and caudad between the 8 th pair of legs, posterior edge of aperture extended shelf-like into the cavity, this surface with several ridges in front of each coxa.
Gonopods notably large, coxae extended outside aperture rims, a large heavily sclerotized mesosternum; coxosternal apodeme elements nearly straight, elongated, apically a little enlarged.Coxa strongly prolonged on the lateral side (Fig. 7); a dorsal field of setae; no paracannular setae.Base of telopodite (prefemur) continuing main coxal axis, thence curved anteriad into a long very slender acropodite region, with small triangular apical lobe; efferent duct visible for its entire length in mesal aspect, carried by a slender acuminate solenomere.Acropodite region paralleled by a long slender prefemoral process, slightly broadened distally, with serrate edges.Neither acropodite nor prefemoral process with cingulum.
Comments: When visited by Gounelle in 1889, Santo Antonio da Barra was the name used for the city now called Condeúba in southwestern Bahia (14.53.35S, 41.59W).
Diagnosis: Distinguished from all known chelodesmid genera by the following combination of characters: size large (L to 70 mm), paranota well-developed, stricture costulate, prefemoral knobs and tibial pads absent, femora of legs 4 th -6 th pairs somewhat more incrassate than the others, those of 2 nd and 3 rd pairs with small but prominent ventrobasal lobe; anterior sternal processes of 5 th segment originating at coxal condyles long, acuminate, directed mesad with the apices in contact.
No sclerotized gonosternal sclerite present; coxa large and robust, with elongated coxosternal apodeme, dorsal coxal apophysis enlarged, with a field of setae on its lateral side, no paracannular setae present.Telopodite slightly smaller than coxa, lacking torsion, efferent groove conducted on a small laminate solenomere terminating the acropodite; prefemoral process large, calyciform, enveloping the acropodite.Neither element of telopodite with cingulum.
Species: Only the type species is known.
Comment: Like the foregoing species, the following has apparently never been recollected (or recorded) in over 100 years, and apparently mentioned only once, in 1938.In his 1903 paper, Brölemann sorted the various new species of Leptodesmus into several species groups, placing carminatus in the "Groupe du Leptodesmus plataleus" which corresponded to the taxon currently recognized as Chondrodesmus.Attems (1938) formally made the new combination Chondrodesmus carminatus although with considerable reservation, writing "Die Stellung dieser Art in der Gattung Chondrodesmus ist sehr zweifelhaft, die Gonopoden, die bei den anderen Arten sehr einheitlich sind, weichen bei dieser Art stark vom Typus ab, jedoch ist es schwer, sie zwanglos in einer Gattung unterzubringen."Lacking personal experience with the situation, Schubart accepted this assignation and did not include carminatus in his 1946 list of Brazilian species of Leptodesmus.Although Brölemann's perception was reasonable for its time, our better knowledge of chelodesmids associates Chondrodesmus and some closely related taxa in a discrete tribe Chondrodesmini endemic to the northern Andes and Middle America (Hoffman, 1978).The large gonosternum in Baianassa alone is sufficient reason to exclude it from that tribe.
Material examined: The holotype.
Diagnosis: With the characters of the genus, further specific characters may be identified in gonopod structure when additional species are discovered.
Description (partly from Brölemann): Length of holotype 63 mm., width of 9 th segment, 10.4 mm.Body robust, the anteriormost segment slightly the widest, parallel-sided except for the last three segments.Dorsum uniformly deep carmine, with a spot on each paranotum, a median spot on the caudal edge of the metaterga, antennae and legs yellow; ventral surfaces slightly paler red.Metaterga dorsally distinctly and densely coriaceous, from the 19 th segment with a vaguely defined sulcus, no transverse series of tubercles.Stricture finely costulate.Paranota large, set high on sides, mostly subquadrate, anterior corners broadly rounded; ozopores located on side of peritremata, which persist only as far as pore, not continued to posterior corner (Fig. 8-10).Sterna broad, flat, not as wide as length of femora, without subcoxal spines.Legs robust, 9.5 mm at midbody, tibiae without apical ventral pads; ventral surfaces with dense setation.Femora of 2 nd -4 th pairs of legs incrassate, with small ventral basal lobe (?adenostyle) (Fig. 11).Sternum of segment 5 with two paramdian pairs of slender, acuminate, mesially-directed processes (Fig. 12).
Gonopods (Figs. 13-15) relatively short and compact, without mesosternal sclerite; coxosternal apodeme slender and nearly straight in the coxal axis.Coxae not prolonged on the lateral side, but with a large, acute apophysis on the dorsal; a small field of setae on the dorsolateral surface; no paracannular setae.Telopodite set against coxa at nearly a right-angle; acropodite continues direction of prefemur.Telopodite dominated by the large, shield-like prefemoral process which encloses the short, simple acropodite.Efferent duct carried by the acropodite termination.No cingulum present on either component of the telopodite.
Comments: Although a number of tribal groups have been proposed in the Brazilian chelodesmid fauna in recent decades, none share the combination of characters that would accomodate Baianassa, which occupies a somewhat disjunct position.A disposition of this genus is probably contingent upon a much better knowledge of the (probably numerous) native chelodesmids of Bahia and adjacent states to the north.
The location of Santo Antonio da Barra is specified in the account of the preceding species.resumo Duas espécies de milípedes quelodesmídeos descritas por Brölemann (1903) | 2,767.8 | 2012-01-01T00:00:00.000 | [
"Biology"
] |
Higgs Couplings and Phenomenology in a Warped Extra Dimension
We present a comprehensive description of the Higgs-boson couplings to Standard Model fermions and bosons in Randall-Sundrum (RS) models with a Higgs sector localized on or near the infra-red brane. The analytic results for all relevant Higgs couplings including the loop-induced couplings to gluons and photons are summarized for both the minimal and the custodial RS model. The RS predictions for all relevant Higgs decays are compared with current LHC data, which already exclude significant portions of the parameter space. We show that the latest measurements are sensitive to KK gluon masses up to $20\, \rm{TeV} \times (y_*/3)$ at $95\%$ confidence level for anarchic 5D Yukawa couplings bounded from above by $|(Y_f)_{ij}|<y_*$. We also derive the sensitivity levels attainable in the high-luminosity run of the LHC and at a future linear collider.
Introduction
In July 2012 the Higgs boson, the last missing piece of the Standard Model (SM), was discovered at the Large Hadron Collider (LHC) at CERN [1,2]. Since then the hierarchy problem, i.e. the question about the mechanism that stabilizes the Higgs mass near the electroweak scale, is no longer a hypothetical issue. A promising possibility to solve the hierarchy problem is offered by Randall-Sundrum (RS) models [3], in which the SM is embedded in a slice of anti-de Sitter space while the Higgs sector is localized on the "infra-red (IR) brane", one of two sub-manifolds bounding the extra dimension. The smallness of the electroweak scale can then be explained by the fundamental UV cutoff given by the warped Planck scale, whose value near the IR brane lies in the TeV range. Moreover, by allowing the fermion fields to propagate in the bulk, these models provide a natural explanation for the hierarchies observed in the flavor sector [4][5][6] and the smallness of flavor-changing neutral currents [7][8][9][10][11][12][13].
The direct detection of Kaluza-Klein (KK) modes, massive copies of the SM particles with approximately equidistant mass gaps, would be a clear indication for a warped extra dimension. Unfortunately, none of these predicted particles have been observed yet, and electroweak precision measurements indicate that their masses could be too large for direct detection at the LHC. Thus, indirect searches like precision measurements of the Higgs-boson couplings to SM particles, which are accessible via studies of both the Higgs production cross sections and its various decay rates, become an attractive alternative. In the context of Higgs physics, new-physics deviations from the SM can be searched for by measuring the signal rates for the production of the Higgs boson in pp collisions at the LHC and its subsequent inclusive decay into an arbitrary final state X. Our work includes a detailed discussion of the signal rates R X for the most relevant decays into X = bb, τ + τ − , W W * , ZZ * , and γγ in different incarnations of RS models. From (1) we can read off that new physics can show up in three different ways. Firstly, it can lead to deviations in the Higgs production cross section σ(pp → h), which can be decomposed into the cross sections for Higgs production via gluon fusion, vector-boson fusion, Higgs-strahlung, and the associated production with a tt pair. The relative contributions read (for m h = 125 GeV) [14] σ(pp → h) = 0.872 σ ggh + 0.070 σ V V h + 0.033 σ W h + 0.020 σ Zh + 0.005 σ tth .
Secondly, new-physics effects can change the Higgs decay rates Γ(h → X), and thirdly they can modify the total Higgs width Γ h . Via the latter quantity the rates are sensitive to non-standard or invisible Higgs decays. In our analysis we take into account all three possibilities. While the gluon-fusion process has been discussed extensively in the literature [15][16][17][18][19][20][21][22][23][24], we analyze the effects of the exchange of virtual KK resonances in the Higgs-strahlung and vector-boson fusion production processes for the first time. Moreover, we take a closer look at the Higgs decays into pairs of W and Z bosons, including their subsequent decays into leptons. This allows for a thorough discussion of the implications of the latest LHC results on the RS parameter space.
In the context of various RS models, we summarize and discuss results for the various couplings of the Higgs boson to fermions and gauge bosons as well as the Higgs self-couplings. It has been reported in [25] that the LHC at √ s = 14 TeV and with an integrated luminosity of 300 fb −1 has the potential to probe, in a model-independent way, deviations of the Higgs couplings to fermions in the range of ∼ 30% and to gauge bosons in the range of ∼ 16%, both at 95% confidence level (CL). At future lepton colliders like the International Linear Collider (ILC) [26][27][28][29], the sensitivity to deviations can be improved by almost one order of magnitude (assuming √ s = 1 TeV and an integrated luminosity of 1000 fb −1 ). In order to explore to which extent it is possible to obtain evidence for models with warped extra dimensions by indirect measurements, we illustrate which regions of parameter space could be probed at these facilities. We focus on RS models where the electroweak symmetry-breaking sector is localized on or near the IR brane. The extra dimension is chosen to be an S 1 /Z 2 orbifold parametrized by a coordinate φ ∈ [−π, π], with two 3-branes localized on the orbifold fixed-points φ = 0 (UV brane) and |φ| = π (IR brane). The RS metric reads [3] where e −σ(φ) , with σ(φ) = kr|φ|, is referred to as the warp factor. The size r and curvature k of the extra dimension are assumed to be of Planck size, k ∼ 1/r ∼ M Pl . The quantity L = σ(π) = krπ measures the size of the extra dimension and is chosen to be L ≈ 33 − 34 in order to explain the hierarchy between the Planck scale M Pl and the TeV scale. We define the KK scale M KK = k , with = e −σ(π) , which sets the mass scale for the low-lying KK excitations of the SM particles. On the right-hand side of (3) we have introduced a new coordinate t = e σ(φ) , whose values on the UV and IR branes are and 1, respectively. 1 In our analysis, we consider both the minimal and the custodially protected RS model, adopting the conventions and notations of [10,19]. In the minimal RS model the gauge group is taken to be SU (3) c × SU (2) L × U (1) Y like in the SM, and it is broken to SU (3) c × U (1) em by the Higgs vacuum expectation model (vev). The RS model with custodial symmetry is based on the gauge group SU (3) c × SU (2) L × SU (2) R × U (1) X × P LR , which is broken both on the UV and IR branes as described in detail in [30][31][32]. The discrete P LR symmetry sets the gauge couplings of the two SU (2) symmetries equal to each other. We shall distinguish two scenarios of RS models, which differ in the localization of the Higgs sector. In models with a brane-localized Higgs field, the inverse characteristic width of the Higgs field along the extra dimension ∆ h is assumed to be much larger than the inherent UV cutoff near the IR brane, i.e. ∆ h Λ TeV ∼ several M KK [33]. In models in which the Higgs field lives in the bulk, the inverse width lies below the cutoff scale, and hence the structure of the Higgs profile can be resolved by the high-momentum modes of the theory. While the general bulk-Higgs case will be discussed in future work [34,35], we only discuss the special case of models featuring a narrow bulk-Higgs field, whose inverse width is such that M KK ∆ h Λ TeV [22]. Our paper is structured as follows: In Section 2 we calculate the cross sections for Higgs production via Higgs-strahlung and vector-boson fusion, as well as the decay rates of the Higgs boson into pairs of electroweak gauge bosons. In Section 3 we give a summary of the main Higgs couplings to fermions and gauge bosons in RS models, including the loop-induced couplings to two gluons and photons, and present expressions that are exact at first order in v 2 /M 2 KK . A numerical study of both the CP-even and CP-odd Higgs couplings in the custodial RS model is performed in Section 4. We comment on the possibility to detect deviations from the SM values of the Higgs couplings at the LHC operating at √ s = 14 TeV and with an integrated luminosity of 300 fb −1 , and an ILC operating at √ s = 1 TeV with an integrated luminosity of 1000 fb −1 . In Section 5 we then compare the predictions for pp → h → bb, τ + τ − , W W * , ZZ * , γγ obtained in the custodial RS scenario with the current data from the LHC, which can be used to deduce bounds on the relevant model parameters. Our main results are summarized in the conclusions.
Higgs production and decay via W and Z bosons
In this section we discuss in detail the structure of new-physics effects in the couplings of the Higgs boson to a pair of electroweak gauge bosons. These couplings are probed in the off-shell Higgs decays h → W W * and h → ZZ * with subsequent decays into four fermions, as well as in the production of the Higgs boson in vector-boson fusion or in the Higgs-strahlung process, see Figure 1. These tree-level processes have in common that they involve the exchange of virtual vector bosons, which implies that in addition to the SM W and Z bosons we must consider the effect of the infinite towers of KK resonances. It is often assumed in the literature that the main effect of new physics on these processes arises from a rescaling of the on-shell hV V couplings. We show that there are also several other effects that need to be accounted for, namely a possible rescaling of the Higgs vev, a modification of the couplings of the W and Z bosons to light fermions, and the exchange of new heavy particles in the off-shell propagators.
In RS models all of these effects are indeed present, and accounting for them correctly will be important for a general definition of the signal strength in terms of the Higgs couplings to fermions and vector bosons in Section 5. To good approximation, however, we will show that the main effects can be accounted for by a multiplicative rescaling of the SM decay rates and production cross sections. For simplicity of presentation, the derivations in this section will be performed for the case of the minimal RS model. The extension to the case of the custodial model is presented in the Appendix.
Higgs decay into vector bosons
We begin by studying the decay of the Higgs boson to a pair of electroweak gauge bosons, taking h → W W * as a concrete example. Since m h < 2m W , this decay is only allowed if at least one of the W bosons is produced off-shell. We thus consider the process h → W − W + * → W − f if j , where the off-shell boson decays into a pair of light fermions f i andf j with generation indices i, j. In the SM, the corresponding differential decay rate is given by [36] dΓ ds where s is the invariant mass squared of the fermion pair, and λ(x, y, z) = (x − y − z) 2 − 4yz. We have expressed the result in terms of the on-shell decay rate for the process W + → f if j , where g denotes the SU (2) L gauge coupling, the color factor N f c = 1 for leptons and 3 for quarks, and g ij,L = δ ij / √ 2 for leptons and V CKM ij / √ 2 for quarks. Performing the remaining integration over s in the interval 0 ≤ s ≤ (m h − m W ) 2 and neglecting fermion-mass effects, one obtains where the first factor is one half of the (would-be) on-shell h → W W width in the limit m h m W , the second factor accounts for the suppression due to the fact that one of the W bosons in the decay h → W W * is produced off-shell, and the phase-space function is given by The off-shell decay considered here arises if x > 1/4. In the literature, it is common practice to define the off-shell h → W W * decay rate as where the sum includes all fermion pairs with total mass lighter than m W . The factor 2 accounts for the charge-conjugated decays h → W −f i f j . In the SM the expression for Γ(h → W W * ) has the same form as in (6), but with the partial decay rate Γ(W + → f if j ) replaced by twice the total decay width Γ W of the W boson.
Analogous formulas hold for the decays based on h → ZZ * , where we must replace W → Z everywhere and use the corresponding expression for the partial decay rates of the Z boson in the SM, where g f,L = T f 3 −s 2 w Q f and g f,R = −s 2 w Q f are the left-handed and right-handed couplings of the various fermion species, and s w = sin θ w and c w = cos θ w are the sine and cosine of the weak mixing angle. In this case the total off-shell decay rate is defined as where the sum includes all fermions lighter than m Z /2. It follows from this definition that for the golden channel We now discuss in detail how the above results must be modified in the context of the minimal RS model. For the purposes of this discussion it is convenient to define the weak mixing angle s 2 w via the structure of the neutral current, which can be studied experimentally via the Z-pole polarization asymmetries observed at LEP. Alternative definitions are related to this one through the electroweak precision variables S, T and U ; see e.g. [34] for a detailed discussion. In the context of RS models one has s 2 w = g 2 5 /(g 2 5 + g 2 5 ) in terms of the 5D gauge couplings. If this ratio is extracted from experiment there are no new-physics corrections to the branching ratios Br(W → f if j ) and Br(Z → ff ). Modifications arise for the Higgs couplings to vector bosons, the electroweak gauge couplings entering the partial decay rates (5) and (9), and due to the contributions of heavy KK resonances, which change the momentum-dependent gauge-boson propagator. Let us for concreteness consider the decay h → W − W + * to study the impact of these corrections in the context of the minimal RS model. In the Feynman diagram in Figure 1(a) the off-shell gauge-boson propagator now contains the SM gauge boson and its infinite tower of KK excitations. The Feynman rule for the W h vertex is (with n = 0 for the zero mode and n > 0 for the KK excitations) where v denotes the Higgs vev in the RS model, which differs from the Higgs vev v SM ≡ √ 2G F −1/2 by terms of order v 2 /M 2 KK [22,24]. The quantitym 2 W = g 2 5 2πr v 2 4 is the leading contribution to the mass of the W boson in an expansion in powers of v 2 /M 2 KK , and χ W n (t) are the profiles of the W -boson KK modes along the extra dimension [10]. For the W -boson zero mode, one finds where here and below the ellipses denote terms of order v 4 /M 4 KK and higher. Note, in particular, that for the zero mode one encounters a correction factor [33] relative to the SM. The Feynman rule for the W A vertex, where A = L, R is a chirality label and i, j labels the flavors of the SM quarks, is to an excellent approximation given by [10] i √ 2 where P L = 1 2 (1 − γ 5 ) is a chiral projection operator. Corrections to this result, including the couplings to right-handed fermions, are strongly chirality suppressed. Note, in particular, that for the zero mode one encounters a correction factor relative to the SM, which will affect all decay amplitudes of the W boson into light fermions. It follows that, relative to the SM, we must make the following replacements in the SM decay amplitude for h → W − W + * → W − u idj : where the quantity denotes the 5D gauge-boson propagator of the RS model, which has been calculated in closed form in [33,37,38]. In the last equation we show the first two terms in an expansion in powers of v 2 /M 2 KK , valid under the assumption that p 2 < m 2 W , which is appropriate for our analysis. The numerator structures are given by with t < = min(t, t ). At subleading order, we can now rewrite the right-hand side of (17) in the form 1 This result has an intuitive form. The factor c 1/2 Γ W rescales the W -boson decay amplitudes of the SM in a uniform way, the factor c W rescales the Higgs-boson coupling to a W + W − pair, and the last term in brackets is the contribution of heavy KK resonances. Substituting the above expression for the gauge-boson propagator into (4) and performing the integration over s, we obtain with The analysis of new-physics effects on the h → ZZ * decay rate proceeds analogously. Instead of c W in (14) one finds the correction factor for the hZZ coupling. Moreover, in the RS model the Zff couplings entering the partial rates in (9) get replaced by If the weak mixing angle is defined via the structure of the couplings g f,A (s 2 w ), then the only difference with regard to the SM is a factor Note that, if m Z and s 2 w are taken as inputs, then the W -boson mass is a derived quantity, which obeys m 2 . As long as we choose M KK consistent with the bounds from electroweak precision tests (see Section 4), this value will be consistent within errors with the measured W mass.
The fact that the L-enhanced terms in the effective couplings c W in (14) and c Z in (23) are different is problematic from a phenomenological point of view, as this amounts to a breaking of custodial symmetry in the effective couplings of the Higgs to electroweak gauge bosons. Indeed, the difference (c W − c Z ) is related to the T parameter, which receives dangerously large corrections in the minimal RS model [38,39]. Taming these effects has been the main motivation for the construction of RS models with a custodial symmetry in the bulk [30][31][32]. The extension of the above analysis to the RS scenario with a custodial symmetry is discussed in the Appendix. Here we shall briefly collect the relevant formulas for the various correction factors. The expressions for the correction factors to the hV V vertices become Note that the custodial protection mechanism ensures that the leading, L-enhanced terms are now the same for both couplings [19,40], whereas the subleading terms are different. The correction factors c Γ W,Z to the W → ff and Z → ff decay rates remain unchanged.
Higgs-strahlung
We now move on to study the cross section for the Higgs-strahlung process, in which the Higgs boson is produced in pp collisions in association with a W or Z boson, see Figure 1(b). Since the Feynman diagram for Higgs-strahlung is identical to that for the Higgs-boson decay into a pair of electroweak gauge bosons, it follows that the amplitude at the quark level receives exactly the same corrections as the Higgs decay amplitude discussed in the previous section. If we denote the invariant mass squared of the hV pair in the final state by s, we immediately obtain from (20) Because the s dependence of the SM cross section is sensitive to the shapes of the parton distribution functions, it is not possible to derive a simple analytic formula for the corrections to the total Higgs-strahlung cross sections. However, the leading correction terms enhanced by L are universal and independent of s. When only these terms are kept, one obtains This approximation has been frequently used in the literature. In RS models it is accurate up to small corrections not enhanced by L.
Higgs production in vector-boson fusion
We finally consider the vector-boson fusion process shown in Figure 1(c). It involves two gauge-boson propagators, whose momenta we denote by p 1,2 . In analogy with the discussion in the previous sections, we find that in order to account for new-physics effects one must replace in the expression for the scattering amplitude. Once again the integrations over the virtual momenta flowing through the propagators cannot be performed in closed form, because they involve convolutions with parton distribution functions. However, the leading correction terms enhanced by L are universal. When only these terms are kept, one obtains which is an approximation often adopted in the literature.
Higgs couplings in RS models
In order to parameterize the RS contributions to the various Higgs couplings, we match them onto an effective Lagrangian defined at the electroweak scale µ ≈ v. For simplicity we neglect the effects of renormalization-group running from the new-physics scale µ ≈ M KK down to the electroweak scale, as their numerical impact is of minor importance. The phenomenologically most relevant Higgs couplings can be described using the following Lagrangian in the broken electroweak phase: We emphasize that it is not a complete list of operators. For instance, we have not included the operators hZ µf γ µ f and hZ µf γ µ γ 5 f contributing to the h → ZZ * → Zf f decay amplitude (and corresponding operators for h → W W * ), since as shown in Section 2.1 their contribution is subdominant. Furthermore, we do not consider the Higgs decay h → Zγ or any flavorviolating couplings in this work. Both the CP-even couplings c i and the CP-odd coefficients c i5 are real. In the SM c W = c Z = c f = c 3h = c 4h = 1 and c f 5 = c g = c g5 = c γ = c γ5 = 0.
Higgs couplings to fermions and electroweak gauge bosons
In the SM, the Higgs boson couples to fermions and electroweak gauge bosons at tree level, with coupling strengths proportional to the masses of these particles. The non-universality of these couplings is the most distinguished feature of the Higgs mechanism. In RS models, modifications of the couplings arise from two effects: genuine corrections to the hV V (with V = W, Z) and hf f vertices, and an overall rescaling of all couplings due to the shift of the Higgs vev, which appears because we use the SM vev v SM in the effective Lagrangian (31). We now present explicit expressions for the various c i parameters, working consistently to first order in v 2 /M 2 KK . Wherever possible, we will parameterize the differences between the minimal and the custodial RS model by means of a parameter ξ, which equals 1 in the minimal model and 2 in the custodial model.
The Higgs couplings to W and Z bosons in RS models have been derived in [10,19,33] and given in (14), (23), and (26). With L ≈ 33 − 34, the L-enhanced contributions in these expressions are by far dominant numerically. Future precise measurements of c W and c Z would thus provide a direct tool to determine the ratio M KK / √ L in the RS model. The couplings of the Higgs boson to the third-generation fermions have been studied in detail in [19], where it was found that flavor-changing couplings are strongly suppressed. For the CP-even and CP-odd flavor-diagonal couplings, it follows that (with f = t, b, τ on the left-hand side and f = u, d, e on the right-hand side) where Y f denote the dimensionless, anarchic 5D Yukawa matrices in the up, down and lepton sectors. Note that the CP-odd couplings in (32) are solely due to the "three-Yukawa terms". The real-valued quantities ε f arise from overlap integrals of the "wrong-chirality" fermion profiles. They are given by Explicit expressions for the matrices δ U,D,E and δ u,d,e can be found in eq. (5.13) of [10], while those for the matrices Φ U,D,E and Φ u,d,e are given in eqs. (6.19) and (6.20) of [19]. They depend in a complicated way on the bulk mass parameters of the various 5D fermion fields. All of the quantities ε f are of O(v 2 /M 2 KK ), but in addition some of them are strongly chirality suppressed. For all practical purposes, one can retain ε u = (δ U ) 33 + (δ u ) 33 but approximate ε d ≈ (δ D ) 33 , ε e ≈ 0, and similarly in the custodial model. Numerically, the ε f parameters turn out to play a numerically subleading role compared with the "three-Yukawa terms" in c f .
The Higgs couplings to the fermions do not only depend on the KK mass scale, but also on the dimensionless 5D Yukawa matrices. It is possible to simplify the Yukawa-dependent terms in the anarchic approach to flavor physics in RS models, in which the fundamental 5D Yukawa matrices are assumed to be structureless, and the observed hierarchies in the mass matrices of the SM fermions are explained in terms of their overlap integrals with the wave function of the Higgs scalar [4][5][6]. When scanning over the parameter space of an RS model, the various entries of the Yukawa matrices are taken to be complex random number subject to the condition that |(Y f ) ij | ≤ y , where the upper bound y = O(1) is a free parameter. For an ensemble of sufficiently many random matrices constructed in this manner, one can show that on average [22,33] Y where N g = 3 is the number of generations. It follows that the Higgs couplings to fermions are rather insensitive to the individual entries of the Yukawa matrices, but they do scale with y 2 . Hence, we encounter a similar situation as in the gauge-boson case, where the relevant parameter is now given by M KK /y . We should add at this point that in practice relation (34) is subject to some flavor-dependent corrections, which arise when the scan over random Yukawa matrices is performed subject to the constraint that one obtains acceptable values for the quark and lepton masses and for the CKM matrix in the quark sector. When this is done, one finds numerically that the expectation value (34) is slightly enhanced for the top quark and somewhat reduced for the bottom quark. 2 We close this subsection with a comment on a certain class of brane-Higgs models, in which one uses two different Yukawa matrices Y C f and Y S f in the Higgs couplings to the Z 2 -even and Z 2 -odd fermion fields. While in bulk-Higgs models the two matrices must be equal as a result of 5D Lorentz invariance, they can be different if the scalar sector is localized on the IR brane. We refer to models with Y C f = Y S f as type-II brane-Higgs models. In these scenarios, the Yukawa-dependent terms in (32) change according to [22] For the special case Y S f = 0, which was sometimes adopted in the literature, this term vanishes. There is then no contribution to the CP-odd couplings c f 5 .
Higgs self-couplings
One of the predictions of the SM is that the trilinear and quartic Higgs couplings can be expressed in terms of the Higgs-boson mass and the vev of the Higgs field, such that c 3h = c 4h = 1 in (31). In RS models these coefficients receive calculable corrections, which for the minimal and the custodial RS models are described by the same formula in terms of the correction to the Higgs vev. As long as the Higgs sector is localized on or near the IR brane, one obtains [22] For a KK mass scale of M KK = 1.5 TeV, one finds a 2.4% (4.8%) reduction of the trilinear coupling and a 4.8% (9.6%) reduction of the quartic coupling in the minimal (custodial) RS model. We mention that moving the Higgs field into the bulk would attenuate these deviations and move the couplings closer to their SM values [35]. Such small deviations will not be measurable by the LHC, and even for a future linear collider like the ILC this is probably out of reach. Therefore, we refrain from presenting a detailed numerical analysis of the Higgs self-couplings in the subsequent section.
Loop-induced Higgs couplings to two gluons
In the SM, the Higgs boson couples to massless gluons and photons only via loop diagrams containing heavy SM particles. Direct couplings, such as the ones contained in the effective Lagrangian (31), are absent in the SM. In the context of RS models such direct couplings are induced at one-loop order via the exchange of heavy KK resonances. We begin with a discussion of the loop-induced Higgs couplings to gluons, which are relevant for the calculation of the gluon-fusion cross section σ(gg → h), which is the main Higgs production channel at high-energy hadron colliders such as the LHC. In the present work we concentrate on the case matrices, while it is 2.7 in the up-quark sector and 2.2 in the down-quark sector. We do not consider neutrino masses or the PMNS matrix in our analysis, since this would require the specification of the neutrino sector, which is both model dependent and of little relevance to Higgs physics.
of the Higgs sector being localized near the IR brane, which has been discussed in several works [15][16][17][18][19][20][21][22][23][24]. As mentioned in the Introduction, the result for the contribution of the infinite tower of KK resonances exhibits a UV sensitivity in the sense that it is sensitive to the precise nature of the localization mechanism.
In the limit where we neglect O(v 2 /M 2 KK ) corrections which in addition are strongly chirality suppressed, the expressions for the induced Higgs couplings to two gluons read The quantities are entirely given by the dimensionless 5D Yukawa matrices of the RS model. Note that the Yukawa matrices are the same in both the minimal and the custodial RS model, but there is an additional √ 2 in the argument of the function g(X f ) in the latter case. For the two scenarios with a brane-localized and a narrow bulk-Higgs sector, one finds [22,23] g so that the effect from the KK tower is approximately equal but of opposite sign in the two scenarios. For a large ensemble of random matrices, one obtains on average [22,33] Tr Due to the additional factors √ 2 and 3 in the second case in (37), the quark KK tower contribution in the custodial RS model is roughly four times larger than in the minimal RS model. Note that with the hermitian matrices X f the traces over the matrix-valued functions g(X f ) are real, so that irrespective of the Higgs localization or the type of RS model (minimal or custodial). For the type-II brane-Higgs model, the function g(X f ) in the first line of (39) must be replaced by [22], and hence to leading order there is no difference with the result shown above. In this model the CP-odd coupling c g5 receives contributions starting at O(v 4 /M 4 KK ), which are however too small to be of any phenomenological significance. In the subsequent sections we will therefore restrict ourselves to a study of the two cases shown in (39).
When the top-quark is integrated out from the effective Lagrangian (31), additional contributions to the effective hgg couplings are induced at one-loop order. They can be accounted for by introducing the effective coefficients which we have normalized such that c eff g = 1 in the SM. Explicit expressions for the top-quark loop functions A q (τ t ) ≈ 1.03 and B q (τ t ) ≈ 1.05 (with τ t = 4m 2 t /m 2 h ) can be found, e.g., in [41,42]. Both approach 1 for τ t → ∞, and it is an excellent approximation to use the asymptotic values for the small new-physics corrections to the Wilson coefficients. It then follows that the terms proportional to ε u , which in c eff g combine to ε u 1 − A q (τ t ) , can be safely neglected. Note also that to a very good approximation c eff g5 ≈ c t5 .
Loop-induced Higgs couplings to two photons
We finally turn our attention to the couplings of the Higgs boson to two photons, which play a crucial role for the h → γγ decay channel, in which the Higgs boson has been discovered in 2012. Neglecting as before O(v 2 /M 2 KK ) corrections which in addition are strongly chirality suppressed, the expressions for the induced Higgs couplings to two photons in the minimal RS model read [33] while in the custodial model one obtains They receive KK contributions from the quark and lepton loops as well as from loops of W bosons and scalar Goldstone fields. Here Q u,d,e denote the electric charges of the SM fermions, and Q λ = 5 3 is the charge of a new exotic, heavy fermion species encountered in the custodial RS model. The precise embeddings of the SM quark fields into the extended gauge symmetry has been discussed in detail in [19,43]. For the lepton fields two types of embeddings have been studied in [33]. Here we adopt the simplest assignment, in which the left-handed neutrino and electron are put into an SU (2) L doublet (as in the SM) and the right-handed electron along with a new, exotic neutral particle N R into an SU (2) R doublet. The infinite tower of the KK excitations of the W bosons (including the Goldstone fields) contributes [19,24,33] Like in the case of the gluon-fusion channel gg → h, we defined effective coefficients obtained after the heavy particles t, W and Z of the SM have been integrated out. They are related to the above coefficients by where again we have chosen the normalization such that c eff γ = 1 in the SM. The explicit form , which approaches 1 for τ W → ∞, can be found in [41,42]. From the fact that the coefficient c γ5 in (43) and (44) vanishes, it follows that to a very good approximation
Numerical analysis of Higgs couplings
We now study the structure of new-physics effects to both tree-level and loop-induced Higgs couplings to fermions and gauge bosons in the context of the RS model with custodial symmetry, for which the bounds derived from electroweak precision tests allow for KK masses in the few TeV range. For example, a recent tree-level analysis of the S and T parameters yields M g (1) > 4.8 TeV (at 95% CL) for the mass of the lightest KK gluon and photon resonances [22], and somewhat lighter masses are possible for the KK fermion resonances [44][45][46]. We will see that these bounds still allow for sizable effects in the Higgs sector. On the other hand, the corresponding bound M g (1) > 12.3 TeV (at 95% CL) obtained in the minimal RS model is so high that the resulting corrections to the Higgs couplings are generally below the sensitivity level of present and planned collider experiments. In our analysis we take m h = 125.6 GeV for the Higgs mass and m t = 172.6 GeV for the pole mass of the top quark. The parameter L = ln(M Pl /Λ TeV ) is chosen to be L = 33.5.
Tree-level Higgs couplings
In the custodial RS model, the corrections to the tree-level Higgs couplings to W and Z bosons in (26) are identical up to very small corrections not enhanced by L. Introducing the mass M g (1) ≈ 2.45 M KK of the lightest KK gluon instead of the KK scale M KK , which is independent of the details of the localization of the scalar sector and the choice of the electroweak gauge group [47], we obtain Realistically, with KK masses not in conflict with electroweak precision tests, we might thus expect corrections of a few up to a maximum of 10%. The corrections to the Higgs selfcouplings in (36) are even smaller; the coefficients in front of the correction term are 0.026 for c 3h and 0.052 for c 4h . Next we study the corrections to the CP-even and CP-odd Higgs couplings c f and c f 5 to the third-generation fermions, as obtained from (32). In analogy to our previous analyses in [22,33], we generate three sets of 5000 random and anarchic 5D Yukawa matrices, whose entries satisfy |(Y q ) ij | ≤ y with y = 0.5, 1.5, and 3, and which correctly reproduce the Wolfenstein parametersρ andη of the unitarity triangle. Furthermore, we choose the bulk mass parameters c Q i < 1 and c q i < 1 such that we reproduce the correct values for the SM quark masses evaluated at the scale µ = 1 TeV. Figure 2 shows the Higgs couplings to top quarks as a function of the mass of the lightest KK gluon state and for three different values of y . In accordance with (32) and (34) we observe that c t is reduced compared to the SM value 1 for almost all parameter points, where the depletion increases with larger values of y . The corresponding plots for c b and c τ would look very similar, with the magnitude of the corrections somewhat reduced. The main difference is due to the different values of the ε f parameters in the three cases, but their numerical impact is subleading. The solid lines in the left plot in the figure show simple polynomial fits of the form c f = 1 − a f (5 TeV/M g (1) ) 2 to the scatter points, with coefficients a f = a f (y ) given in Table 1. We like to add a brief comment concerning the type-II brane Higgs model at this point, in which the three-Yukawa terms must (1) in the custodial RS model. The green, red, and blue scatter points correspond to model points obtained using y = 0.5, 1.5, and 3, respectively. The overlaid lines in the left plot show fits to the various distributions as explained in the text. The gray band in the right plot shows the experimental bound on |c t5 | derived from the electron EDM (at 90% CL). Table 1: Fit coefficients a f for different values of y .
be replaced according to (35) and have a vanishing expectation value. While the remaining terms in (32) still give rise to small negative corrections, the corresponding scatter plots would show points scattered more or less around the central value c i = 1, and which can become larger than 1 for not too small values for y due to the indefinite sign of the three-Yukawa terms. Although they are not as pronounced as in the conventional brane-Higgs scenarios, significant effects on the Higgs coupling to the top quark are still possible. For example, with y = 3 a modification of c t by 20% is possible for KK excitations as heavy as 7.5 TeV.
The CP-odd couplings of the Higgs to two fermions c f 5 in the RS model are given by the second expression in (32). For random complex Yukawa matrices with entries bounded by |(Y f ) ij | ≤ y , we find an approximately Gaussian distribution with zero mean and non-Gaussian tails, which can be reduced by imposing a lower bound on the magnitude of (Y f ) 33 . In the vicinity of the peak the distribution is approximately normal, with standard deviation 15 Figure 2: Predictions for the Higgs couplings to top quarks as a function of the KK gluon mass M g (1) in the custodial RS model. The green, red, and blue scatter points correspond to model points obtained using y = 0.5, 1.5, and 3, respectively. The overlaid lines in the left plot show fits to the various distributions as explained in the text. The gray band in the right plot shows the experimental bound on |c t5 | derived from the electron EDM (at 90% CL). Table 1: Fit coefficients a f for different values of y .
be replaced according to (35) and have a vanishing expectation value. While the remaining terms in (32) still give rise to small negative corrections, the corresponding scatter plots would show points scattered more or less around the central value c i = 1, and which can become larger than 1 for not too small values for y due to the indefinite sign of the three-Yukawa terms. Although they are not as pronounced as in the conventional brane-Higgs scenarios, significant effects on the Higgs coupling to the top quark are still possible. For example, with y = 3 a modification of c t by 20% is possible for KK excitations as heavy as 7.5 TeV.
The CP-odd couplings of the Higgs to two fermions c f 5 in the RS model are given by the second expression in (32). For random complex Yukawa matrices with entries bounded by |(Y f ) ij | ≤ y , we find an approximately Gaussian distribution with zero mean and non-Gaussian tails, which can be reduced by imposing a lower bound on the magnitude of (Y f ) 33 . In the vicinity of the peak the distribution is approximately normal, with standard deviation Due to the constraint that we must obtain realistic values of the quark masses and CKM mixing angles the actual results differ slightly from this result. It has been argued in [48] that present experimental bounds on electric dipole moments (EDMs) of the electron, neutron and mercury impose non-trivial bounds on the CP-odd Higgs couplings to the third-generation fermions. The strongest constraint exists for the magnitude on c t5 and comes from the EDM of the electron, which is sensitive to the htt couplings via two-loop Barr-Zee diagrams. Using the present 90% CL upper limit d e < 8.7 · 10 −29 e cm [49] and assuming that the Higgs coupling to electrons is not changed with respect to its SM value, one obtains |c t5 | < 0.01 [48]. In the RS models considered in this work this assumption is valid to high accuracy, since corrections to the he + e − coupling are strongly chirality suppressed. This resulting bound is shown by the gray band in the right plot in Figure 2. Interestingly, we find that for y 1 there are many points in RS parameters space for which c t5 takes values of the same order of magnitude as the experimental bound. Hence, in the context of RS models it is conceivable that first hints of a non-zero electron EDM might be seen in the next round of experiments.
Loop-induced Higgs couplings
We now move on to study the loop-induced hgg and hγγ couplings in the custodial RS model. They are of special interest, since they are very sensitive probes of the effects of virtual KK resonances. We concentrate on the CP-even couplings c eff g and c eff γ , since current measurements are not sufficiently precise to probe the CP-odd couplings. 3 Using the explicit expressions for c eff g and c eff γ in (42) and (46), it is straightforward to derive approximate expressions for these coefficients which help to understand the interplay of the various contributions. To this end, we expand the fermion KK tower contributions in (37) and (44) to first order in v 2 /M 2 KK and employ (34) and (40). We also approximate the top-quark loop function A q (τ t ) by its asymptotic value 1 and neglect subleading terms not enhanced by L in the bosonic contributions. This yields Here the upper sign holds for the brane-Higgs case, while the lower one corresponds to the narrow bulk-Higgs scenario. We have kept the dependence on the one-loop SM amplitude In each square bracket, the first term is due to the effects of KK fermion resonances, while the second term accounts for the vev shift and Figure 3: Predictions for the CP-even effective Higgs coupling to two photons as a function of the KK gluon mass M g (1) in the custodial RS model, for the scenarios with a brane-localized scalar sector (left) and a narrow bulk-Higgs field (right). The green, red, and blue scatter points correspond to model points obtained using y = 0.5, 1.5, and 3, respectively. The overlaid lines show the approximate results (50).
the contribution of bosonic KK states (for c eff γ ). The fermionic contributions enter the two coefficients with opposite signs and are larger in magnitude in the case of c eff g . Figure 3 shows our predictions for the coefficient c eff γ as a function of the mass of the lightest KK gluon resonance and for different values of y . We recall the well-known fact that the results exhibit a large sensitivity to the precise nature of the localization of the scalar sector on or near the IR brane. On average, the distributions of scatter points follow the approximate formulas shown in (50); however, in the brane-Higgs case higher-order corrections become important for small M g (1) values, and they are included in our phenomenological analysis below. The corresponding information on how c eff g depends on M g (1) and y can be deduced from the correlation between the two loop-induced couplings, to which we turn now.
Correlations between Higgs couplings
We have explained earlier that, to good approximation, the average results for the various Higgs couplings in RS models can be expressed in terms of only two parameters M KK and y , with some relatively narrow distribution of model points about these average predictions. As a result, in these models there are strong correlations between various Higgs couplings. This important fact is illustrated in Figure 4, where we display our predictions in the c t -c b and c eff γ -c eff g planes. In the right plot, scatter points below c eff g = 1 (lower right plane) correspond to the brane-localized Higgs scenario, while points above c eff g = 1 (upper left plane) refer to the narrow bulk-Higgs scenario. All points included in these plots obey the constraint M g (1) > 4.8 TeV implied by electroweak precision tests. In the case of the fermionic couplings c t and c b we observe a clear correlation in the sense that both couplings are smaller than 1 by approximately equal amounts. On the other hand, we see a clear anti-correlation between c eff γ Figure 3: Predictions for the CP-even effective Higgs coupling to two photons as a function of the KK gluon mass M g (1) in the custodial RS model, for the scenarios with a brane-localized scalar sector (left) and a narrow bulk-Higgs field (right). The green, red, and blue scatter points correspond to model points obtained using y = 0.5, 1.5, and 3, respectively. The overlaid lines show the approximate results (50).
the contribution of bosonic KK states (for c eff γ ). The fermionic contributions enter the two coefficients with opposite signs and are larger in magnitude in the case of c eff g . Figure 3 shows our predictions for the coefficient c eff γ as a function of the mass of the lightest KK gluon resonance and for different values of y . We recall the well-known fact that the results exhibit a large sensitivity to the precise nature of the localization of the scalar sector on or near the IR brane. On average, the distributions of scatter points follow the approximate formulas shown in (50); however, in the brane-Higgs case higher-order corrections become important for small M g (1) values, and they are included in our phenomenological analysis below. The corresponding information on how c eff g depends on M g (1) and y can be deduced from the correlation between the two loop-induced couplings, to which we turn now.
Correlations between Higgs couplings
We have explained earlier that, to good approximation, the average results for the various Higgs couplings in RS models can be expressed in terms of only two parameters M KK and y , with some relatively narrow distribution of model points about these average predictions. As a result, in these models there are strong correlations between various Higgs couplings. This important fact is illustrated in Figure 4, where we display our predictions in the c t -c b and c eff γ -c eff g planes. In the right plot, scatter points below c eff g = 1 (lower right plane) correspond to the brane-localized Higgs scenario, while points above c eff g = 1 (upper left plane) refer to the narrow bulk-Higgs scenario. All points included in these plots obey the constraint γ so as to obtain the best fit values to the experimental data assuming that the tree-level Higgs couplings take their SM values. It would be much preferable -and the clearest way to test any new-physics model -to compare the theoretical predictions with future results from model-independent analyses of the Higgs couplings.
Future sensitivities on Higgs couplings of LHC and ILC
In the last part of this section, we wish to illustrate the potential for constraining the relevant parameters of the RS models by future, model-independent analyses of Higgs couplings. It has been reported in [26] that the LHC with an integrated luminosity of 300 fb −1 has the potential to probe deviations of Higgs couplings to fermions in the range of 14% -46% and to gauge bosons in the range of 14% -30%, both at 95% CL. At future lepton colliders like the ILC [27][28][29][30] the sensitivity to deviations can be improved by almost one order of magnitude. In the following analysis we focus on the LHC operating at √ s = 14 TeV with 300 fb −1 of integrated luminosity and the ILC operating at √ s = 1 TeV with integrated luminosity of 1000 fb −1 . γ so as to obtain the best fit values to the experimental data assuming that the tree-level Higgs couplings take their SM values. It would be much preferable -and the clearest way to test any new-physics model -to compare the theoretical predictions with future results from model-independent analyses of the Higgs couplings.
Future sensitivities on Higgs couplings of LHC and ILC
In the last part of this section, we wish to illustrate the potential for constraining the relevant parameters of the RS models by future, model-independent analyses of Higgs couplings. It has been reported in [25] that the LHC with an integrated luminosity of 300 fb −1 has the potential to probe deviations of Higgs couplings to fermions in the range of 14% -46% and to gauge bosons in the range of 14% -30%, both at 95% CL. At future lepton colliders like the ILC [26][27][28][29] the sensitivity to deviations can be improved by almost one order of magnitude. In the following analysis we focus on the LHC operating at √ s = 14 TeV with 300 fb −1 of integrated luminosity and the ILC operating at √ s = 1 TeV with integrated luminosity of 1000 fb −1 .
LHC (14 TeV, 300 fb −1 ) ILC (1 TeV, 1000 fb −1 ) y = 3 y = 3 y = 1.5 y = 1.5 Figure 5: Summary of the exclusion limits (at 95% CL) on the mass of the first KK gluon resonance in the custodial RS model, which could be derived from SMlike measurements of Higgs couplings at the high-luminosity LHC (left) and the ILC (right), for two representative values of y . For the loop-induced couplings c eff g and c eff γ , we distinguish between the brane (green) and the narrow bulk-Higgs (blue) scenarios. The dashed vertical lines show the lower bounds on M g (1) obtained from electroweak precision measurements.
Our goal is to derive exclusion bounds for the mass of the first KK gluon resonance from each of the Higgs couplings. To obtain these bounds, we plot each coupling c i as in Figure 2, fit a Gaussian distribution to the model points for each pair of y and M g (1) , and determine the mean values c i with the standard deviations σ c i . For the experimental couplings we assume that they are SM-like, c exp i = 1, with the 1σ errors given in Table 2. These errors are asymmetric and correspond to the 1σ confidence intervals as they emerge from the combined fit (subject to certain assumptions) performed in [26]. We then consider the ratio c i /c exp i = c i , and calculate the corresponding standard deviation by combining the theoretical and experimental errors in quadrature. Finally, we test at which confidence level the coefficient c i is compatible with 1. The results are compiled in Figure 5 for two representative values of y . The colored regions are the 95% CL excluded regions for the mass of the lightest KK gluon resonance. To obtain exclusion bounds for arbitrary values of y , one can make use of the fact that the exclusion limits depend linearly on y to good approximation. We see that the strongest bounds emerge from the loop-induced Higgs couplings, for which we distinguish between the brane-Higgs (b.) and narrow bulk-Higgs (n.b.) scenarios. Our results imply that the high-luminosity run at the LHC can probe or exclude KK gluon masses in the range M g (1) < 21 TeV×(y /3) for the brane Higgs scenario, and M g (1) < 13 TeV×(y /3) in the narrow bulk-Higgs model. For the ILC, one expects to probe or rule out KK gluon masses in the range M g (1) < 43 TeV × (y /3) Our goal is to derive exclusion bounds for the mass of the first KK gluon resonance from each of the Higgs couplings. To obtain these bounds, we plot each coupling c i as in Figure 2, fit a Gaussian distribution to the model points for each pair of y and M g (1) , and determine the mean values c i with the standard deviations σ c i . For the experimental couplings we assume that they are SM-like, c exp i = 1, with the 1σ errors given in Table 2. These errors are asymmetric and correspond to the 1σ confidence intervals as they emerge from the combined fit (subject to certain assumptions) performed in [25]. We then consider the ratio c i /c exp i = c i , and calculate the corresponding standard deviation by combining the theoretical and experimental errors in quadrature. Finally, we test at which confidence level the coefficient c i is compatible with 1. The results are compiled in Figure 5 for two representative values of y . The colored regions are the 95% CL excluded regions for the mass of the lightest KK gluon resonance. To obtain exclusion bounds for arbitrary values of y , one can make use of the fact that the exclusion limits depend linearly on y to good approximation. We see that the strongest bounds emerge from the loop-induced Higgs couplings, for which we distinguish between the brane-Higgs (b.) and narrow bulk-Higgs (n.b.) scenarios. Our results imply that the high-luminosity run at the LHC can probe or exclude KK gluon masses in the range M g (1) < 21 TeV×(y /3) for the brane Higgs scenario, and M g (1) < 13 TeV×(y /3) in the narrow bulk-Higgs model. For the ILC, one expects to probe or rule out KK gluon masses in the range M g Table 2: Experimental capabilities for model-independent measurements of the Higgsboson couplings c i to gauge bosons (top) and third-generation fermions (bottom), expressed as 1σ confidence intervals derived in [25]. For the case of the hgg and hγγ couplings we show the effective coefficients c eff g,γ defined in (42) and (46).
in both scenarios. 4 Note also that, independently of the realization of the Yukawa sector (and hence the parameter y ), the analysis of the Higgs couplings to W bosons at the ILC is expected to be sensitive to KK gluon masses of up to 15 TeV. In all cases, these limits by far exceed the mass ranges allowing for a direct discovery of KK resonances.
Analysis of signal rates in the custodial RS model
We finally investigate in more detail the Higgs decay rates into pairs of electroweak gauge bosons and third-generation fermions. In order to directly compare our predictions with experimental measurements, we study the signal rates R X defined in (1), which can be expressed in terms of the effective couplings c i and c i5 derived in Section 3 via The correction to the total Higgs width relative to the SM total width Γ SM h = 4.14 MeV (for m h = 125.5 GeV) can be accounted for by the parameter [53] The corrections to the decay modes h → cc, Zγ, . . . have a numerically insignificant effect and can therefore be neglected; the combined branching fraction of these modes is 3% in the SM. In (51) we have taken into account the probabilities to produce a Higgs boson via gluon fusion (GF), or via vector-boson fusion and associated hV production (collectively referred to as VBF). Concerning the latter production processes, we have implemented the findings of Section 2. [55,56].
between c W and c Z as far as these terms are concerned, see (26). Other production channels such as pp → htt can be neglected to very good approximation. For inclusive Higgs production at the LHC the appropriate fractions are f GF ≈ 0.9 and f VBF ≈ 0.1. For the case of the final state X = bb, Higgs-strahlung is an experimentally more feasible Higgs production channel at the LHC than gluon fusion, since the latter suffers from an overwhelming QCD background [54]. For the case of the signal rate R bb we thus have to set f GF = 0 and f VBF = 1 in (51). A further comment concerns the Higgs decays into W W * and ZZ * , with subsequent decays of the off-shell vector boson into fermions. According to the discussion in Section 2.1, we use the expression for (21) instead of c 2 V in this case. In the following analysis we will focus first on the individual Higgs decay rates in the context of the custodial RS model. We will then present a summary of the bounds on the KK gluon mass M g (1) and the parameter y , which are derived by confronting our predictions with naive averages of the signal strengths reported by the ATLAS and CMS Collaborations and summarized in Table 3. A more thorough analysis properly accounting for correlations between the various measurements should be performed by the experimental collaborations.
Analysis of the signal rates R γγ , R ZZ , and R W W We start our analysis with a discussion of Higgs decays into two electroweak gauge bosons. The decay into two photons has been discussed extensively in our previous work [33], see in particular Figure 4 in this reference. We will not repeat the corresponding analysis here. Figure 6 shows the results for the ratio R ZZ as a function of the mass M g (1) of the lightest KK gluon state and for three different values for y . 5 To excellent approximation the scatter points also represent the results for the observable R W W , since at the level of the L-enhanced terms the Higgs decays into ZZ * and W W * are expressed by the same modification factor c 2 Z ≈ c 2 W , see (21) and (26). The blue band represents the 1σ error range corresponding to the latest experimental values for R ZZ given in Table 3, where the naively averaged value has been used. Model points falling outside this band are excluded at 68% CL. (Alternatively we could have used the average experimental value for the ratio R W W , in which case the excluded set of model points is a different one.) It is interesting to observe that for relatively large values Figure 6: Predictions for the ratio R ZZ as a function of the KK gluon mass M g (1) in the custodial RS model, for the cases of a brane-localized Higgs boson (left) and a narrow bulk-Higgs field (right). The scatter points with different color correspond to different values of y . The blue band represents the 1σ experimental error range for the observable R ZZ .
for y the data already disfavor KK gluon masses in the low TeV range. The tensions between the theoretical predictions for R ZZ (R W W ) and the experimental data are stronger for the brane-Higgs (narrow bulk-Higgs) model due to the mild tendency of an enhanced (suppressed) cross section seen in the data, which is in conflict with the suppression (enhancement) of the predicted cross section.
The shapes of the curves can be explained by the fact that, for not too small Yukawa couplings, the RS corrections to the gluon-fusion cross section by far dominate over the corrections to the Higgs decay rates. The results then closely resemble those shown in Figure 5 of [22], where only the corrections to the gluon-fusion cross section were taken into account. The dependance of this production channel on the details of the localization of the Higgs profile on or near the IR brane explains why the ratios R V V are suppressed (enhanced) in the brane-localized (narrow bulk-Higgs) scenario. For small values of M g (1) and y , however, the loop-induced couplings become subdominant, and the negative corrections to the h → ZZ * decay width give rise to a reduction of the signal rate even in the narrow bulk-Higgs scenario. The peculiar behavior seen for very small KK scales in the left plot in Figure 6 can be understood as follows. For y = 3, the gg → h production cross section vanishes for M g (1) ≈ 7.0 TeV, because the new-physics contribution cancels the SM amplitude. However, due to the vectorboson fusion production process a non-zero value of R ZZ remains. For even smaller values of M g (1) the new-physics amplitude dominates over the SM one and the cross section rises again.
The new-physics effects on the ratios R ZZ and R W W are stronger than those on R γγ , since in the latter case there is a partial compensation between the contributions of fermionic KK resonances to the Higgs production cross section via gluon fusion and to the h → γγ decay rate [34]. The strong correlation between R ZZ and R γγ resulting from these fermionic Figure 6: Predictions for the ratio R ZZ as a function of the KK gluon mass M g (1) in the custodial RS model, for the cases of a brane-localized Higgs boson (left) and a narrow bulk-Higgs field (right). The scatter points with different color correspond to different values of y . The blue band represents the 1σ experimental error range for the observable R ZZ .
for y the data already disfavor KK gluon masses in the low TeV range. The tensions between the theoretical predictions for R ZZ (R W W ) and the experimental data are stronger for the brane-Higgs (narrow bulk-Higgs) model due to the mild tendency of an enhanced (suppressed) cross section seen in the data, which is in conflict with the suppression (enhancement) of the predicted cross section.
The shapes of the curves can be explained by the fact that, for not too small Yukawa couplings, the RS corrections to the gluon-fusion cross section by far dominate over the corrections to the Higgs decay rates. The results then closely resemble those shown in Figure 5 of [22], where only the corrections to the gluon-fusion cross section were taken into account. The dependance of this production channel on the details of the localization of the Higgs profile on or near the IR brane explains why the ratios R V V are suppressed (enhanced) in the brane-localized (narrow bulk-Higgs) scenario. For small values of M g (1) and y , however, the loop-induced couplings become subdominant, and the negative corrections to the h → ZZ * decay width give rise to a reduction of the signal rate even in the narrow bulk-Higgs scenario. The peculiar behavior seen for very small KK scales in the left plot in Figure 6 can be understood as follows. For y = 3, the gg → h production cross section vanishes for M g (1) ≈ 7.0 TeV, because the new-physics contribution cancels the SM amplitude. However, due to the vectorboson fusion production process a non-zero value of R ZZ remains. For even smaller values of M g (1) the new-physics amplitude dominates over the SM one and the cross section rises again.
The new-physics effects on the ratios R ZZ and R W W are stronger than those on R γγ , since in the latter case there is a partial compensation between the contributions of fermionic KK resonances to the Higgs production cross section via gluon fusion and to the h → γγ decay rate [33]. The strong correlation between R ZZ and R γγ resulting from these fermionic corrections is examined in Figure 7. The SM predicts the values R SM ZZ,γγ = 1 denoted by the crossing position of the dashed lines. Scatter points below the horizontal dashed line belong to the brane-localized Higgs scenario, while the points above the line belong to the narrow bulk-Higgs scenario. 6 All scatter points fulfill the bound M g (1) > 4.8 GeV imposed by the measurements of the oblique parameters S and T . The cross shows the experimental values given in Table 3, while the green ellipses present the 68%, 95%, and 99% confidence regions of the combined measurements. We observe a strong correlation between the two ratios, where for reasons explained above the new-physics effects are larger for R ZZ than for R γγ . Notice that the naively averaged current experimental data slightly favor the narrow bulk-Higgs over the brane-localized Higgs scenario. It should be noted, however, that using only the measurements reported by CMS one would obtain the opposite conclusion.
Analysis of the signal rates R τ τ , R bb and the total Higgs width We now turn to the predictions for R τ τ and R bb in the custodial RS model. The upper plots in Figure 8 show the observable R τ τ as a function of M g (1) . As in the previous cases, the shapes of the curves are largely due to the behavior of the Higgs-boson production cross section, which is dominated by the gluon-fusion process. Particularly for small KK scales, these effects are quite large and have the potential to compensate and even exceed the SM contribution. For very small KK scales (M g (1) 3 TeV), on the other hand, the negative corrections to the c τ 6 We only show scatter points for y = 1.5 and 3. For y = 0.5, both R ZZ and R γγ are always reduced, see Figure 6 and Figure 4 in [34]. Figure 7: Correlation of the predictions for the signal rates R ZZ and R γγ in the custodial RS model under variations of M g (1) and y . All scatter points fulfill the constraints from electroweak precision tests. The cross shows the average experimental values with 1σ errors for the measured signal rates.
23
corrections is examined in Figure 7. The SM predicts the values R SM ZZ,γγ = 1 denoted by the crossing position of the dashed lines. Scatter points below the horizontal dashed line belong to the brane-localized Higgs scenario, while the points above the line belong to the narrow bulk-Higgs scenario. 6 All scatter points fulfill the bound M g (1) > 4.8 GeV imposed by the measurements of the oblique parameters S and T . The cross shows the experimental values given in Table 3, while the green ellipses present the 68%, 95%, and 99% confidence regions of the combined measurements. We observe a strong correlation between the two ratios, where for reasons explained above the new-physics effects are larger for R ZZ than for R γγ . Notice that the naively averaged current experimental data slightly favor the narrow bulk-Higgs over the brane-localized Higgs scenario. It should be noted, however, that using only the measurements reported by CMS one would obtain the opposite conclusion.
Analysis of the signal rates R τ τ , R bb and the total Higgs width We now turn to the predictions for R τ τ and R bb in the custodial RS model. The upper plots in Figure 8 show the observable R τ τ as a function of M g (1) . As in the previous cases, the shapes of the curves are largely due to the behavior of the Higgs-boson production cross section, which is dominated by the gluon-fusion process. Particularly for small KK scales, these effects are quite large and have the potential to compensate and even exceed the SM contribution. For very small KK scales (M g (1) 3 TeV), on the other hand, the negative corrections to the c τ Figure 8: Predictions for the ratios R τ τ (upper plots) and R bb (lower plots) as a function of the KK gluon mass M g (1) in the custodial RS model, for the cases of a brane-localized Higgs boson (left) and a narrow bulk-Higgs field (right). The meaning of the colors is the same as in Figure 2.
coupling can become so large that the h → τ + τ − decay rate almost vanishes (see Figure 2), and hence R τ τ can drop close to zero. The observable R bb shown in the lower plots receives more moderate corrections, since in this case the only production channel included is Higgsstrahlung. Although there is no need to distinguish between the brane-localized and narrow bulk-Higgs scenario in the Higgs production cross section and the h → bb decay rate, the two plots still differ due to the contribution of the h → gg decay rate to the total Higgs width. This partial rate is reduced in the brane-Higgs scenario and enhanced in bulk-Higgs models.
The present data on R bb only imply weak constraints on the RS parameter space, because the experimental accuracy is worse than for all other channels, see Table 3. Nevertheless, the Higgs coupling to bottom quarks c b is an important quantity, since it gives rise to one of the most significant corrections to the total Higgs width (52), which enters all of the signal rates in (1). Figure 9 shows the ratio c h = Γ RS h /Γ SM h in the custodial RS model. We see that in the 24 Figure 8: Predictions for the ratios R τ τ (upper plots) and R bb (lower plots) as a function of the KK gluon mass M g (1) in the custodial RS model, for the cases of a brane-localized Higgs boson (left) and a narrow bulk-Higgs field (right). The meaning of the colors is the same as in Figure 2.
coupling can become so large that the h → τ + τ − decay rate almost vanishes (see Figure 2), and hence R τ τ can drop close to zero. The observable R bb shown in the lower plots receives more moderate corrections, since in this case the only production channel included is Higgsstrahlung. Although there is no need to distinguish between the brane-localized and narrow bulk-Higgs scenario in the Higgs production cross section and the h → bb decay rate, the two plots still differ due to the contribution of the h → gg decay rate to the total Higgs width. This partial rate is reduced in the brane-Higgs scenario and enhanced in bulk-Higgs models. The present data on R bb only imply weak constraints on the RS parameter space, because the experimental accuracy is worse than for all other channels, see Table 3. Nevertheless, the Higgs coupling to bottom quarks c b is an important quantity, since it gives rise to one of the most significant corrections to the total Higgs width (52), which enters all of the signal rates in (1). Figure 9 shows the ratio c h = Γ RS h /Γ SM h in the custodial RS model. We see that in the (1) in the custodial RS model, for the cases of a brane-localized (left) and a narrow bulk-Higgs field (right).
brane-Higgs scenario the Higgs width can be reduced by about 25 -50% (10 -20%) for a KK gluon mass M g (1) ≈ 5 TeV (10 TeV) and maximal Yukawa value y = 3. The dominant effects come from the decays h → bb and h → gg, both of which receive negative corrections. The situation is different in the case of the narrow bulk-Higgs scenario, where the h → gg decay rate receives a large positive correction, which enhances the Higgs width and counteracts the suppression of the h → bb decay rate. This effect dominates for y 1.5, leading to a Higgs width larger than in the SM.
Summary of exclusion bounds for M g (1) and y Even at the present level of precision, the existing measurements of the signal rates for the various Higgs-boson decays provide strong constraints on the parameter space of the RS models under consideration. In Figure 10 we show the exclusion limits obtained at 95% CL on the mass of the first KK gluon resonance and the maximum value y of the elements of the anarchic 5D Yukawa matrices in the custodial RS model, derived by an analysis of the various decay rates using the latest experimental results shown in Table 3. To obtain these limits, we have fitted a Gaussian distribution to the model points for each pair of M g (1) and y , and determined the mean values R th X and the standard deviations σ R th X for these parameters, in analogy with our treatment of the effective Higgs couplings in Section 3. We have then calculated the ratios R X /R exp X , combined the theoretical and experimental errors in quadrature, and tested at which confidence levels these ratios are compatible with 1. The green (blue) bars in the figure refer to the brane-localized (narrow bulk-Higgs) RS scenario. The most stringent bounds emerge from the signal rates for pp → h → ZZ * , W W * . The former yields tighter constraints in the brane-localized Higgs scenario and the latter in the narrow bulk-Higgs scenario.
Taking the most stringent bounds from Figure 10, which are obtained for y = 3, we derive at 95% CL the lower bounds M g (1) custodial RS brane Higgs > 19.9 TeV and M g (1) custodial RS narrow bulk Higgs > 14.9 TeV (53) Figure 9: Predictions for c h = Γ RS h /Γ SM h as a function of M g (1) in the custodial RS model, for the cases of a brane-localized (left) and a narrow bulk-Higgs field (right).
brane-Higgs scenario the Higgs width can be reduced by about 25 -50% (10 -20%) for a KK gluon mass M g (1) ≈ 5 TeV (10 TeV) and maximal Yukawa value y = 3. The dominant effects come from the decays h → bb and h → gg, both of which receive negative corrections. The situation is different in the case of the narrow bulk-Higgs scenario, where the h → gg decay rate receives a large positive correction, which enhances the Higgs width and counteracts the suppression of the h → bb decay rate. This effect dominates for y 1.5, leading to a Higgs width larger than in the SM.
Summary of exclusion bounds for M g (1) and y Even at the present level of precision, the existing measurements of the signal rates for the various Higgs-boson decays provide strong constraints on the parameter space of the RS models under consideration. In Figure 10 we show the exclusion limits obtained at 95% CL on the mass of the first KK gluon resonance and the maximum value y of the elements of the anarchic 5D Yukawa matrices in the custodial RS model, derived by an analysis of the various decay rates using the latest experimental results shown in Table 3. To obtain these limits, we have fitted a Gaussian distribution to the model points for each pair of M g (1) and y , and determined the mean values R th X and the standard deviations σ R th X for these parameters, in analogy with our treatment of the effective Higgs couplings in Section 3. We have then calculated the ratios R X /R exp X , combined the theoretical and experimental errors in quadrature, and tested at which confidence levels these ratios are compatible with 1. The green (blue) bars in the figure refer to the brane-localized (narrow bulk-Higgs) RS scenario. The most stringent bounds emerge from the signal rates for pp → h → ZZ * , W W * . The former yields tighter constraints in the brane-localized Higgs scenario and the latter in the narrow bulk-Higgs scenario.
Taking the most stringent bounds from Figure 10, which are obtained for y = 3, we derive at 95% CL the lower bounds M g (1) custodial RS brane Higgs > 19.9 TeV and M g (1) custodial RS narrow bulk Higgs > 14.9 TeV (53) on the mass of the first KK gluon resonance. We stress that, since these bounds derived from Higgs physics are much stronger than those stemming from electroweak precision measurements, from a phenomenological point of view there is not much gained by implementing the custodial protection mechanism. While this mechanism can tame the large tree-level effects on the T parameter and the Zbb couplings in RS models, we still find very large contributions to loop-induced processes in the Higgs sector. A similar observation has been made in the context of loop-induced flavor-changing neutral current processes such as b → sγ [57]. However, the effects found here are far more pronounced. A possible way out (aside from gauge-Higgs unification models [58,59], where the Higgs is identified with the fifth component of a 5D gauge field) is to lower y . The right plot in Figure 10 summarizes the exclusion regions on y obtained for two different values of the lightest KK gluon mass. The analysis has been restricted to values for y below the perturbativity bound y ≤ y max ≈ 3 [9,22]. Again, the most stringent bounds come from the processes pp → h → ZZ * , W W * and can be combined to give the constraints (at 95% CL) valid for M g (1) = 4.8 TeV. We see that in particular in the brane-Higgs scenario small values are preferred. However, too small Yukawa couplings would give rise to enhanced corrections to K [9] and hence they would reinforce the RS flavor problem. Also, for y < 1 it becomes difficult to reproduce the physical value of the top-quark mass.
26 Figure 10: Summary of the bounds on the mass of the lightest KK gluon (left) and the parameter y (right) obtained from the exclusion plots in the custodial RS model for the brane-localized (green) and narrow bulk-Higgs scenario (blue). The shaded regions are excluded at 95% CL for each corresponding decay channel. The vertical dashed line shows the bound obtained from a tree-level analysis of electroweak precision observables.
on the mass of the first KK gluon resonance. We stress that, since these bounds derived from Higgs physics are much stronger than those stemming from electroweak precision measurements, from a phenomenological point of view there is not much gained by implementing the custodial protection mechanism. While this mechanism can tame the large tree-level effects on the T parameter and the Zbb couplings in RS models, we still find very large contributions to loop-induced processes in the Higgs sector. A similar observation has been made in the context of loop-induced flavor-changing neutral current processes such as b → sγ [57]. However, the effects found here are far more pronounced. A possible way out (aside from gauge-Higgs unification models [58,59], where the Higgs is identified with the fifth component of a 5D gauge field) is to lower y . The right plot in Figure 10 summarizes the exclusion regions on y obtained for two different values of the lightest KK gluon mass. The analysis has been restricted to values for y below the perturbativity bound y ≤ y max ≈ 3 [9,22]. Again, the most stringent bounds come from the processes pp → h → ZZ * , W W * and can be combined to give the constraints (at 95% CL) valid for M g (1) = 4.8 TeV. We see that in particular in the brane-Higgs scenario small values are preferred. However, too small Yukawa couplings would give rise to enhanced corrections to K [9] and hence they would reinforce the RS flavor problem. Also, for y < 1 it becomes difficult to reproduce the physical value of the top-quark mass.
Conclusions
The discovery of a Higgs boson at the LHC [1,2] has initiated a new era in elementary particle physics. The couplings of this new particle are found to be close to those predicted for the scalar boson of the SM. An explanation to the hierarchy problem is thus more urgently needed than ever. Precise measurements of the Higgs couplings to SM fermions and bosons provide an important tool for the discovery and the distinction of new-physics models addressing the hierarchy problem. In this paper, we have presented a comprehensive discussion of the effective Higgs couplings and all relevant signal rates for the production and decay of the Higgs boson at the LHC in the context of warped extra-dimension models with the scalar sector localized on or near the IR brane. For the first time, we have presented a thorough study of all new-physics effects in RS models on the decay rates for the processes h → V V * (with V = W, Z), with the subsequent decay of the off-shell gauge boson into a fermion pair. We have also studied the new-physics effects on the Higgs-strahlung and vector-boson fusion production processes and shown that to very good approximation they can be accounted for by the corrections to the on-shell hV V couplings c V . This analysis has included the effects of virtual KK gauge bosons, which have been shown to be subleading (in L) with respect to the contributions stemming from the modified hV V couplings.
We have then summarized the expressions for the effective Higgs couplings to pairs of gauge bosons and fermions obtained within the context of warped extra-dimension models with the Higgs sector localized on or near the IR brane. The distinction between brane-Higgs and narrow bulk-Higgs scenarios becomes relevant for the contribution of fermionic KK resonances to the loop-induced Higgs couplings to photons and gluons. The corrections to the hW W and hZZ couplings are universal and given by the very simple formula (48), which shows that corrections of more than a few percent can only be reached for KK masses close to the bound M g (1) > 4.8 TeV implied by electroweak precision tests. The corrections to the Higgs couplings to fermions scale like ∼ y 2 v 2 /M 2 KK and can be significant for M g (1) 10 TeV and not too small values of y . Even larger corrections can appear in the loop-induced Higgs couplings to gluons and photons, due to the high multiplicity of virtual KK particles propagating in the loop. The corresponding contributions to c eff g and c eff γ are strongly anti-correlated. For instance, for y = 3 and a KK gluon mass M g (1) = 10 TeV, the relevant couplings in the custodial RS model with a narrow bulk Higgs are c eff g ≈ 1.5 and c eff γ ≈ 0.7. Our analysis has included both the CPeven and CP-odd Higgs couplings. The CP-odd couplings to fermions can receive significant contributions from the 5D Yukawa couplings, while the CP-odd couplings to massive gauge bosons vanish. Concerning the loop-induced couplings to gluons and photons, the KK tower only contributes to the CP-even couplings, while the top-quark loop induces a contribution to the CP-odd couplings c eff g5 and c eff γ5 . This gives rise to a potentially important contribution to the electric dipole moment of the electron, which can naturally be at the present level of sensitivity.
In order elucidate the potential of future measurements at high-luminosity proton and lepton colliders to indirectly search for hints of a warped extra dimension, we have compared the predicted new-physics effects on the relevant couplings with the sensitivities that can be reached at the LHC with √ s = 14 TeV and an integrated luminosity of 300 fb −1 , and at the ILC with √ s = 1 TeV and an integrated luminosity of 1000 fb −1 . The exclusion bounds obtained in the RS model with custodial symmetry under the assumption of SM-like measurements are summarized in Figure 5. At the ILC in particular, one will be able to probe KK gluon masses in the range over several tens of TeV from an analysis of the loop-induced Higgs couplings to gluons and photons. The analysis of the Higgs coupling to W bosons at the ILC will have an expected sensitivity to KK gluon masses of M g (1) ≈ 15 TeV, which is independent of the realization of the Yukawa sector and hence the value of the parameter y .
In the last section of the paper we have compared our predictions for the various Higgs signal rates with the latest data from the LHC. The strongest exclusion bounds originate from the Higgs decay rates into pairs of electroweak gauge bosons. In the custodial RS model, KK gluon masses lighter than 19.9 TeV × (y /3) in the brane-Higgs case and 14.9 TeV × (y /3) in the narrow bulk-Higgs scenario are excluded at 95% CL. Our analysis shows that Higgs physics provides very sensitive probes of virtual effects from heavy KK excitations. Especially the signal rates for Higgs decays into pairs of electroweak gauge bosons, which primarily probe new-physics effects via the gluon-fusion production mechanism, could be used to either explain possible deviations in the corresponding cross sections or to derive strong bounds on the RS parameter space. These bounds are complementary to and often stronger than those from electroweak precision observables and rare flavor-changing processes. In the custodial RS model, the indirect effect of KK states on the Higgs-boson processes are strongly enhanced compared with the minimal model [22,33], and hence the current experimental results on various Higgs decays already provide strong constraints. Even under the pessimistic assumption that the direct detection of KK resonances is out of reach at the LHC, one may still see sizable modifications of the pp → h → X signal rates for X = γγ, ZZ * , W W * , τ + τ − , even with M g (1) as heavy as 10 or 15 TeV. It will be exciting to compare our predictions with future, more precise experimental results. Even if no KK particles are to be discovered at the LHC, such an analysis could still provide a hint of the existence of a warped extra dimension. at this orbifold fixed point. Explicitly, the zero-mode profiles read [19] √ 2π χ W 0 (t) = Note that the twisted component is proportional to t 2 and suppressed by the ratio m 2 W /M 2 KK . It follows that the corrections factors in (14) and (23) become in accordance with (26). The Feynman rules for the couplings of the W and Z bosons and their KK excitations to SM quarks, the W A vertices (with A = L, R), are given by with the chiral projectors P R,L = 1 2 (1±γ 5 ). Following [19], we collect all left-and right-handed quark fields in the up, down, and exotic sectors into the 15 Note that for the W -boson the leading contribution to the CKM matrix arises from the (11)component of Ω W . For vertices involving the light SM fermions, corrections coming from the t-dependent term in the gauge-boson profile as well as from the admixture of the U and D states are chirally suppressed and can be neglected [19]. This feature extends to the case of the KK excitations of the W boson. Effectively this means that we only need to keep the constant contributions of the W profiles, which survive near the UV brane and are given by χ W n ( ). In case of the Z-boson vertices in the second Feynman rule in (A.5), we have defined the couplings where T q3 L,R denote the eigenvalues under the third generator of SU (2) L,R , Y q is the hypercharge, and Q q denotes the electromagnetic charge of the quark. Once again we only need to keep the t-independent contributions in the gauge-boson profile functions. Thus, as in the minimal RS model we can approximate the Feynman rules in (A.5) by 2πrc w √ 2π 1 0 χ Z n ( ) γ µ g q,L (s 2 w ) P L + g q,R (s 2 w ) P R . (A.9) For the SM W and Z bosons (n = 0), the Feynman rules coincide with the corresponding rules (15) and (24) found in the minimal RS model, since the first components of (A.3) are the same as the profiles in (13). Combining all pieces, we find that instead of (17) we must perform the following replacement in the SM amplitude (with V = W, Z): The 5D propagator function is defined in terms of the infinite sum It has been calculated to all orders in v 2 /M 2 KK in [33]. Expanding the result to first non-trivial order, we obtain which is valid for momenta |p 2 | M 2 KK . Here c V 1 (t, t ) = 2π χ V 0 (t)χ V 0 (t ) is defined via the zero-mode profiles of the vector bosons in the minimal RS model, and c 2 (t, t ) coincides with the expression given in (19). The (11)-component of the propagator is thus the same as in the minimal model. Inserting (A.12) into (A.10), we arrive at (20) with c W and c Z given by (A.4), while remain the same as in the minimal model, see (16) and (25). The vector-boson fusion process analyzed in Section 2.3 can be studied analogously. In this case, we need to replace the first line of (29) by Using the expansions for the propagator functions and evaluating the rescaling factors, we confirm the second line of (29) with c V and c 1/2 Γ V given above. | 21,694.4 | 2014-08-19T00:00:00.000 | [
"Physics"
] |
The recurring collocation of vreiðr and vega in Old Norse poetry
: Poetry in early Germanic vernaculars exhibits variations on a metrical form predicated on a pattern of alliterating stressed syllables linking two halves of a line (in contrast to syllabic metres in which scansion requires a fixed number of syllables per line). This gave rise to the phenomenon of recurring alliterative collocations: the repeated combination of alliterating words or word-roots within a given poetic corpus. It is likely that such collocations originated, like formulae in oral-formulaic theory developed by Milman Parry and A.B. Lord, as building blocks for extempore composition during performance. However, there is strong evidence that Old Norse poetry was composed deliberatively and memorized for performance. Recurring collocations in Old Norse verse therefore reflect conscious artistic design rather than compositional expe-diency. This article focuses on one such collocation—the adjective vreiðr (angry) and the verb vega (to fight, to strike)—as a case study of the way in which composers of Old Norse eddic verse exploited the traditional resonances of certain collocations to shape audience understanding of character and plot.
Old Norse poetry, like other poetry in early Germanic vernaculars, was composed in alliterative metre, the scansion of which is predicated on a pattern of stressed alliterating syllables linking two halves of a full line. 1 The oral composition of alliterative verse gave rise to the phenomenon of recurring alliterative collocations-the repeated combination of certain alliterating word-roots.Alliterative collocations have been extensively studied in Old English poetry (e.g., Creed 1961;Quirk 1963;Lynch 1972;Kintgen 1977;Tyler 2006;Szöke 2014), but they have only recently begun to receive attention in the context of Old Norse verse (Ruggerini 2016;McKinnell 2022).Ruggerini in particular has illustrated how the occurrence of a certain word may prompt expectation of a given collocate-expectation which could be satisfied or subverted for rhetorical effect.Through innovative substitution of homophones or near-homophones, established collocating pairs could be expanded into broader collocational sets.The following discussion takes a narrower focus than Ruggerini's excellent analysis of several such sets, considering a single repeated alliterative coupling.The corpus of Old Norse eddic poetry features seven instances in which inflections of the adjective (v)reiðr (angry) are collocated with inflections of the verb vega (to fight, to strike).The recurrence of the collocation has long been noted (e.g., Sveinbjörn Egilsson and Finnur Jónsson 1931: 461-2;Schier 1986: 379;Fidjestøl 1999: 235;Thorvaldsen 2016: 77-8;Haukur Þorgeirsson 2017: 35).However, little has been said concerning its function in the artistic design of the poets who employed it.This paper seeks to identify a network of traditional resonances evoked by the use of this collocation.The corpus of eddic poetry comprises verse on mythological and heroic subjects, mostly composed between the ninth and thirteenth centuries in Scandinavia and associated colonies-though the date and provenance of individual poems, and the criteria for establishing these, remain the subject of scholarly debate.The principal source is the Codex Regius (GKS 2365 4°), henceforth CR, an Icelandic anthology manuscript written around AD 1270; alongside the 29 compositions contained in CR, the corpus also includes stylistically similar poems, stanzas, and isolated verses preserved in medieval and early modern Icelandic prose sagas, historical texts, and poetical treatises.Eddic verse is conventionally distinguished from 'skaldic' verse on a number of grounds: eddic verse is typically composed in less intricate metres, and tends to deal with mythological-legendary subject matter, whereas skaldic verse deals predominantly with occasional topics such as encomia for the poet's patron; skaldic verse is characterized by more complex and riddling diction including heavy use of kennings, a kind of compound periphrasis.2Eddic verse is generally anonymous, whilst skaldic poems and stanzas are often reliably attributed to named poets.However, all of these criteria admit of exceptions.The distinction remains useful for some critical purposes, though it is increasingly recognized as artificial and porous by modern scholarship (e.g., Haymes 2004: 54;Clunies Ross 2012: xiii-xviii;Schorn 2016a: 232-4).The poems with which this paper is concerned comprise three eddic poems preserved in CR, and one skaldic poem preserved in Snorri Sturluson's Edda, a treatise on mythology and poetics written in Iceland in the thirteenth century.Before turning to the texts, it is important to estab-lish the appropriate framework within which to discuss repetitive diction in eddic poetry.The phenomenon of formulaic language in oral-derived poetry inevitably calls to mind the pioneering work of the Homeric scholars Milman Parry and A. B. Lord, whose fieldwork with prevailingly illiterate poets in the Balkans underpinned insights into the repetitive nature of the Homeric epics as the residue, or expression, of oral composition. 3Parry and Lord held that oral formulae functioned as expedients to composition during performance, by expressing essential ideas under different metrical conditions (e.g., Parry 1971Parry (1928)); Lord 1960).A corollary of this view is that formulae have no rhetorical content: thus, for instance, common noun-epithet formulae such as γλαυκῶπις Ἀθήνη (bright-eyed Athene) or πόδας ὠκὺς Ἀχιλλεύς (swift-footed Achilles) respectively denote simply 'Athena' and 'Achilles'.Few oralists today would adhere to this hard line; the concept of 'traditional referentiality' developed by John Miles Foley (1991: 7 and passim) articulates the way in which traditional expressions acquire rhetorical significance through invocation of previous occurrences within a given oral tradition, situating each occurrence of a formula within the totality of the story-world known to the audience (see, e.g., Dunkle 1997;Kelly 2010;Burgess 2010 for Homeric examples).Elsewhere, Foley has suggested that formulae in a given tradtition will fall somewhere along a 'spectrum of rhetorical signification ' (1995: 95-6), with some having greater rhetorical content than others.Metrical utility may only be one of numerous factors in the perpetuation of a given formula.Daniel Sävborg (2018) has recently applied traditional referentiality fruitfully to formulae in Icelandic prose sagas, which are also believed to be orally derived;4 as we shall see, it is equally constructive to examine eddic collocations through this lens.The Parry-Lord theory is of limited utility in the analysis of eddic poetry for an additional reason.Parry and Lord described a process of extemporized composition during performance; due to the groundbreaking nature of their work, this model of oral composition has often been applied uncritically to oral poetic traditions across the board (Foley 1996: 23).It is probable that some collocations attested in the eddic corpus, in particular those with cognates in other Germanic verse corpora, originally had a compositional function similar to that of formulae in the Parry-Lord sense (Ruggerini 2016: 310-12).A range of evidence, however, points to Old Norse poetry being of the kind dismissed somewhat reductively by Lord as 'written literature without writing' (Stolz and Shannon 1976: 176).Joseph Harris (1983: 191) has suggested the term 'deliberative composition' to denote this process of composition and memorization prior to performance, in contrast to the Parry-Lord model of extempore composition during performance.The formulaic density of eddic verse is far lower than that of the Homeric poems or of the Serbo-Croat poetry documented by Parry and Lord (Haymes 2004: 53); 5 the terseness of the heroic poems likewise contrasts with the expansive narrative style characteristic of improvised compositions (Haymes 1976: 50-2); the Old Norse-Icelandic lexicon offers distinct terms for composition and performance of poetry (Harris 1985: 115); a much-discussed passage in Egils saga Skallagrímssonar describes the deliberative oral composition of a (skaldic) poem (Egils saga 61; Sigurður Nordal 1933: 177-92). 6The cumulative force of these observations, alongside the documentation of comparable oral poetic traditions by modern anthropologists, notably in Somalia, strongly suggests that Old Norse poetry was deliberatively composed and memorized for performance, producing relatively stable texts. 7The distinction between deliberative and improvised composition is an important one to set alongside that between oral and literary.Both may be considered spectra, rather than binaries. 8It is also crucial to realize that these two axes are not equivalent: oral poetry is not necessarily improvised, and deliberative poetry is not necessarily literary (Haymes 1976: 49).For present purposes, the distinction is of considerable significance in our evaluation of repetition.At face value, the deliberative composition of eddic verse invites comparison to strictly literary compositions, inasmuch as repeated phraseology may be assumed to be wholly the product of artistic design: as Bernt Øyvind Thorvaldsen notes (2008: 148): 'Når en dikter velger å gjenta et uttrykk, … så er det rimelig å anta at han eller hun har grunner til å gjøre nettopp det.' (When a poet chooses to repeat an expression, … it is reasonable to suppose that he or she has reasons to do just that.)Indeed, an essentially literary outlook underpins two influential perspectives on the study of eddic repetition.The first focuses on internal echoes as a structural principle within individual poems (e.g., Taylor 1963;Lehman 1963;Haymes 2004), the second on purported intertexual allusions indicating the direct dependence of one poem on another (e.g., de Vries 1928;Hallberg 1954;Andersson 1983;Jakobsen 1984;McKinnell 2014).The analysis given here seeks to situate at least some forms of repetition more firmly in the context of the eddic corpus' background in oral tradition.Refinements to oral-formulaic theory have posed serious challenges to textual loan arguments (Acker 2014: 77-80;Thorvaldsen 2008), though such studies can offer fruitful readings of In the field of early Germanic poetry, Benson (1966) and Haymes (1980) have shown that formulaic density per se is an unsound basis for asserting oral composition, though highly formulaic literary works composed in conscious imitation of oral works presuppose a tradition of oral-formulaic composition to emulate.Harris (1985: 114-17); Acker (2014: 85-86); Haymes (2004: 48-49).See Finnegan (1977: 73-75) on the Somali material; Haymes (2004: 48-49) draws the comparison to Old Norse poetry.Interestingly, classical Somali poetry is also bound by (rather different) rules concerning alliterating stresses (see Finnegan 1977: 91-5).Finnegan discusses Somali alliterative verse in conjunction with Old English and (more briefly) Old Norse, but does not bring the comparison directly to bear on the question of the composition of Germanic poetry.As Harris (1983) has pointed out, the mode of composition of a given text may differ from its subsequent mode(s) of transmission.For challenges to the binary distinction between oral and literary, see Zumthor (1988;1990: 25), and other papers in this volume which further address the question in a diverse range of temporal and cultural contexts.certain poems.Analyses of internal repetition have provided an important corrective to conceptions of eddic poetry as rustic or primitive, demonstrating that they display considerable compositional sophistication (Lehman 1963: 14).Haymes (2004: 51-53) has shown how repeated verses are used to draw structural and thematic links between paired scenes in the eddic poem Atlakviða (Akv.).I provide a synopsis of the poem for the benefit of nonspecialist readers: The Hunnic king Atli (Attila the Hun) lures the Burgundian king Gunnarr and his brother Hǫgni, the brothers of his wife Guðrún, to his hall and captures them in an attempt to learn where their fabled wealth is hidden.When they refuse to surrender the treasure, he has them killed.To avenge her brothers, Guðrún kills her sons by Atli and feeds him their flesh and blood, revealing their fate before murdering Atli himself in their marriage bed and burning down his hall.
At the opening of the poem, Atli's messenger rides through Mirkwood to the Burgundian hall to deliver Atli's invitation (Akv.1-5) and returns leading Gunnarr and Hǫgni to their fate (Akv.13-16).Clusters of verbal echoes underscore the symmetry of the two journeys, emphasizing that Gunnarr and Hǫgni will not return to their home (Akv.3/3-4 ≈ 13/3-4; 2/3 = 14/11; 3/7-8 ≈ 16/3-4).Later, Gunnarr refuses to divulge the location of his treasure hoard without proof of Hǫgni's death (Akv.21).Atli cuts out the heart of a scullion, Hjalli, attempting to pass it off as Hǫgni's (Akv.22-23), before cutting out Hǫgni's heart in earnest.Hǫgni laughs as he is butchered (Akv.24), and Gunnarr triumphantly declares that the secret of the treasure can now die with him (Akv.25).A further series of phraseological echoes between the two heart-cutting scenes serves to emphasize Hǫgni's heroic stature through contrast with Hjalli (Akv.22/1 cf.24/2; 22/3-4 = 24/5-6; 23/1-10 cf.25/1-10).This example is significant because, as Haymes further notes, the repeated verses in Atlakviða do not appear to be traditional phraseology, since they do not recur elsewhere in the eddic corpus.The rhetorical effect of the repetition can be fully appreciated in literary terms.This is not the case, however, with the collocation of vreiðr and vega which is the subject of this article.
The distribution of vreiðr and vega in the eddic corpus
The collocation of vreiðr and vega occurs across three poems as conventionally edited: three times each in Lokasenna (15/4-5; 18/6; 27/6) and Fáfnismál (7/3; 17/3; 30/3), and once in Sigrdrífumál (28/3).The CR collection includes a total of 428 lines alliterating on v-, of which the root vreiðr occurs in eight, and the root vega in 32. 9 The collocation thus accounts for seven of the 32 instances in which the root vega bears alliterative stress (21.9%), 10 and seven of eight (87.5%) for vreiðr. 11The clear impression that the observed level of co-occurrence is not coincidental can be confirmed statistically.The data can be presented as follows in a two-by-two contingency table: Fisher's exact test is a statistical test used to evaluate the independence of two variablesin this case, occurrences of the vreiðr and vega roots.The test returns the hypergeometric probability of a given distribution of the two variables.From the distribution in the table above, the test finds that there is a statistically significant association between the occurrences of the two word-roots (one-tailed p < 0.0001).In other words, it is exceedingly unlikely that the two roots could have been combined seven times by chance.
In addition to being a deliberate poetic device, the distribution of the collocation in the CR corpus indicates its traditionality.It should be acknowledged that the poems traditionally called Fáfnismál and Sigrdrífumál are not clearly separate entities in CR but are sections of a continuous prosimetric sequence beginning with Reginsmál.Nevertheless, the use of the collocation by at least two eddic poets indicates its nature as a traditional po- etic expression-an impression corroborated by its further occurrence in a skaldic poem, Þórsdrápa, by the tenth-century poet Eilífr Goðrúnarson (Haukur Þorgeirsson 2017: 42-3).
Aside from the unclear situation with Fáfnismál and Sigrdrífumál, there is nothing to suggest a stemmatic relationship between these poems (though it is not impossible that the recurrence of the collocation in the eddic compositions factored into the decision of the CR compiler to include them).The antiquity of the expression is further, and perhaps decisively, evinced by the observation that the alliterative metre in each of the verses in question demands the restoration of initial v-to the manuscript form reiðr.This indicates that the habitual collocation of these roots originated prior to the loss of this initial in West Norse dialects, seemingly by c. AD 1000 (Fidjestøl 1999: 245;Haukur Þorgeirsson 2017: 45). 12As noted above, the deliberative nature of eddic composition means that the repetition of certain expressions is particularly likely to be governed essentially by stylistic concerns, since compositional expedience is not a factor.In the case of a demonstrably traditional expression such as the collocation of vreiðr and vega, we may therefore expect it to fall towards the rhetorically rich end of Foley's spectrum (1995: 95-6), since much of its stylistic value consists in its rhetorical signification.Comparison of the narrative contexts in which the collocation occurs can elucidate the rhetorical resonances that it evoked in the minds of the poets and primary audiences of eddic poetry.
Let us now consider these contexts in the poems of CR.For the benefit of readers unfamiliar with the Old Norse sources, a summary of each poem with contextual background is followed by a survey of the occurrences of the collocation.The eddic poems are quoted from Jónas Kristjánsson and Vésteinn Ólason (2014); translations are my own (for stanzas not cited here, see Larrington 2014).To facilitate appreciation of the alliterative structure of the verses in question, I have underlined the alliterating initials in each verse containing the collocation and used italics for the collocating words in both quotation and translation.
Lokasenna (Ls.)
The gods are hosted by the sea-giant AEgir at a feast, to which the trickster-god Loki is not invited.Loki interrupts the feast and demands a seat, invoking oaths of bloodbrotherhood sworn with Óðinn.He then insults each of the gods and goddesses in turn, until the late arrival of Þórr prompts Loki to withdraw.He is subsequently captured and imprisoned; other sources tell that he will escape to lead the enemies of the gods at the apocalyptic battle of Ragnarǫk.
(1) Our collocation first appears during Loki's dispute with the god Bragi: after trying un-
Fáfnismál (Fm.)
Fafnísmál is part of a prosimetric narrative sequence concerning the youthful exploits of Sigurðr.As noted above, it follows on from Reginsmál and is not separately titled in CR.The précis given here incorporates key background from Reginsmál.
Hreiðmarr receives a gold-hoard from the gods as a wergild for his son.One of his sons, Fáfnir, murders Hreiðmarr and siezes the treasure, subsequently adopting the form of a dragon to guard it.
Fáfnir's brother Reginn fosters Sigurðr after the death of his father Sigmundr, and urges Sigurðr to help him take vengeance against Fáfnir for the murder of their father and the seizure of his inheritance.Reginn forges the sword Gramr for Sigurðr from the shards of Sigmundr's sword.Sigurðr fatally wounds Fáfnir in an ambush; Fáfnismál itself begins after the fight, as Sigurðr engages in a contest of wits with Fáfnir before the dragon dies.
Reginn instructs Sigurðr to roast the dragon's heart for him to eat.In the process Sigurðr accidentally tastes some of the blood and gains the ability to understand birds.
From some nearby nuthatches, he learns that Reginn intends to betray him, and preemptively kills him, claiming the dragon-hoard for himself.
I know, if you had managed to grow up in the bosom of your friends, a man would see you fight furiously; but now you are a captive, and a prisoner of war; they say the bound man is always trembling.
The helm of terror I wore among the sons of men, while I lay upon the necklaces; more powerful than all I thought myself to be, I didn't encounter many enemies.
The helm of terror protects nobody, whenever angry men must fight; a man finds out, when he comes among the throng, that nobody is bravest of all.
Courage is better than the might of a sword, whenever angry men must fight; for I have seen a brave man, fighting strongly, win victory with a blunt sword.
Sigrdrífumál (Sd.)
Like Fáfnismál, Sigrdrífumál is not demarcated as a separate composition in the CR manuscript, and continues the narrative after a linking prose passage.
On further advice from the nuthatches, Sigurðr rides to Hindarfjall, where a valkyrie is imprisoned in an enchanted sleep.Woken by Sigurðr, the valkyrie identifies herself as Sigrdrífa, and explains she was imprisoned as punishment after causing the death of a warrior favoured by Óðinn, to whom he had promised victory.Óðinn decreed that she would never again be victorious in battle, and additionally that she would be married; she swore an oath never to marry a man who felt fear.At Sigurðr's request, Sigrdrífa imparts gnomic and runic wisdom on him.
Foreseeing eyes the sons of men need, whenever angry men must fight
The text of Sigrdrífumál is interrupted by a lacuna in the CR manuscript, but we can trace the missing section of the narrative using Vǫlsunga saga, a fourteenth-century prose text whose author drew on older poetic sources including those preserved in CR.
Sigurðr and the valkyrie pledge themselves to each other, and Sigurðr departs.He stays at the home of Heimir, where he exchanges (or reaffirms) vows with Brynhildr, Heimir's sister-in-law.Eventually, he comes to the court of the Burgundian king Gjúki, where he swears blood-brotherhood to Gjúki's sons, Gunnarr and Hǫgni.Gjúki's wife Grímhildr wishes Sigurðr to marry their daughter, Guðrún, and gives him a potion which causes him to forget his prior betrothal.
Gunnarr resolves to marry Brynhildr, but she is imprisoned behind a wall of fire; Sigurðr alone is able to cross the flames and reach her, and he assists in a ruse to win her hand on Gunnarr's behalf.During an altercation with Guðrún, Brynhildr learns of the deception, which has vitiated her oath to marry only a man without fear.She thus resolves to destroy Sigurðr in revenge, coercing Gunnarr into arranging his death.In order to preserve their oaths, Gunnarr and Hǫgni enlist their brother Guþormr to murder Sigurðr.With Sigurðr dead, Brynhildr ends her own life by climbing onto his funeral pyre.
Guðrún is married to Atli, king of the Huns and Brynhildr's brother, in appeasement for his sister's death.Atli kills Gunnarr and Hǫgni in an attempt to seize their wealth; in revenge for her brothers, Guðrún murders her children by Atli and feeds their flesh to him, before murdering Atli himself and burning down his hall.
A complicated crux concerns the identity of the valkyrie to whom Sigurðr is betrothed on Hindarfjall.In CR, she identifies herself as Sigrdrífa, whilst in Vǫlsunga saga she is Brynhildr, who is later deceived into marrying Gunnarr.The narrative in CR evidently included a broken pledge between Sigurðr and Brynhildr, since in another CR poem, Sigurðarkviða in skamma 39-41, Brynhildr cites this as her motivation for orchestrating his death; what is unclear is whether this is the same or a separate event from his betrothal to Sigrdrífa.The difference in names may be plausibly explained by interpreting Sigrdrífa ('victory-driver') as an epithet for a valkyrie, rather than a proper noun (Bellows 1936: 386-8).Andersson (1980: 82-4) believes Sigurðr's betrothals or love affairs with Sigrdrífa and Brynhildr were originally separate, but if this is the case, they must have been conflated prior to the composition of both Vǫlsunga saga and the approximately contemporary Norna-gests þáttr, since both these sources treat them as identical.The thirteenth-century mythographer Snorri Sturluson likewise explicitly identifies the first valkyrie as Brynhildr (Skáldskaparmál 41),13 though Andersson detects a note of uncertainty on Snorri's part.Contrary to Andersson's claims, however, the prose inserts in Sigrdrífumál provide no sure indication either way.Sigurðarkviða in skamma notes Sigurðr's knowledge of Brynhildr's home, which is consistent with his visit there in Vǫlsunga saga.However, Brynhildr's presence when Sigurðr visits her home in Vǫlsunga saga sits ill with her prior and subsequent imprisonment.Both women swear the same oath to marry only a man who knows no fear, which may suggest initial identity (Larrington 2014: 303).Conceivably, an original betrothal to a single valkyrie was duplicated in some versions of the legend, with the two then imperfectly merged by the compiler of Vǫlsunga saga.However one accounts for the contradictions in the literary record, it is important for present purposes to note that Sigurðr's betrayal of his pledge(s) to Sigrdrífa/Brynhildr is presupposed in all accounts by his later marriage to Guðrún.
The stylistic use of the collocation vreiðr and vega
We are now in a position to examine possible stylistic reasons for the reuse of the collocation in the instances surveyed above.As already suggested, the rhetorical significations of the collocation can be inferred by identifying common elements in the narrative situations in which it is deployed.The most obvious point of continuity in the reccurrence of the collocation is that it consistently appears in the context of a hostile or insulting address.It first appears during Loki's dispute with Bragi, with Loki goading Bragi to follow through with his threatened violence.The third occurrence is also clear-cut, as Frigg angrily rebukes Loki for his insults against her.
This connection is less immediately apparent in the second instance.As we have seen, Iðunn uses the collocation as she plays peacemaker between Loki and Bragi.However, despite her ostensibly conciliatory tone in her first stanza (Ls.16), McKinnell (2014: 179) notes that Iðunn's mention of óskmegir (adoptive relatives: Ls. 16/3) makes for an implied slight against Loki's presence and status amongst the AEsir, since he is part-giant by patrilineal descent, and is only counted amongst the AEsir because of his blood-brotherhood with Óðinn (cf.Ls. 9).Iðunn's second stanza (Ls.18), containing the collocation, underscores this veiled hostility towards Loki through close verbal echoes: The kenning úlfs fǫður (wolf 's father) for Loki emphasizes Óðinn's animosity towards him by pointedly alluding to his future role as the enemy of the AEsir at Ragnarǫk.Thus, by having Iðunn echo Óðinn twice, the poet encourages the audience to hear the same antagonism also in her words.Additionally, the collocation may convey Iðunn's resentment towards her husband, whose posturing machismo has compelled her to intervene on his behalf.Notably, this instance exemplifies how the collocation functions rhetorically even in the context of an apparent negation of hostility and violence: 'vilkat ek at it vreiðir vegisk' (I do not want you two angry men to fight: Ls. 18/6).
These three instances in Lokasenna could very well be understood as a pattern of internal repetition, particularly since, as we have seen, this is a stylistic strategy employed by the poet in other instances.However, the uses of the collocation in Fáfnismál also cohere with this pattern, indicating a traditional resonance.The first two instances come during the verbal sparring between Sigurðr and Fáfnir, with Fáfnir first taunting Sigurðr for his lack of inheritance (Fm.7), and Sigurðr mocking Fáfnir in turn for thinking himself invincible (Fm.17).The third instance comes during Sigurðr's dispute with Reginn, as he rejects the latter's attempt to share in his glory for the dragon-slaying (Fm.30).
The single instance of the collocation in Sigrdrífumál may seem to be an outlier in this pattern of traditional referentiality.However, it can be seen as prefiguring future antagonism: as we have seen, Sigurðr's betrayal of his pledge to the valkyrie is presupposed by the subsequent events of the legend.The use of a collocation connoting hostility may therefore draw on the audience's familiarity with the narrative to hint at Sigrdrífa's future resentment at Sigurðr's faithlessness.If we consider the possibility that the poet and audience identified Sigrdrífa with Brynhildr, this foreshadowing becomes particularly momentous, since Brynhildr's anger at Sigurðr's betrayal is the catalyst for a tragic cycle of revenge which encompasses Sigurðr's murder and (indirectly) the extinction of the Burgundian and Hunnic royal lines.
In view of the semantics of the collocates in question, the collocation's association with hostilility and insult is perhaps unsurprising, though we have seen that it can be deployed in unexpected ways, for instance in revealing the veiled hostility of Iðunn or presaging the strife between Sigurðr and Brynhildr.Moreover, within this general context, the collocation further appears specifically to connote an indictment of the addressee's courage or martial prowess.In Lokasenna, Loki first exposes Bragi's cowardice by inviting him to make good on his threats of violence.In the second instance, Iðunn's attempt to shield her husband from Loki's accusation of cowardice has the unintended consequence of reinforcing its validity, by creating the impression that Bragi needs rescuing by his wife et al. 1997-2019: 5: 415).However, the fact that Sigurðr ambushed Fáfnir rather than confronting him openly may well be pertinent to the insult (cf.Larrington 1993: 82). 14The collocation recurs after Fánfir boasts of his preeminent strength: 'einn rammari | hugðomk ǫllum vera' (more powerful than all I believed myself to be: Fm. 16/4-5).Sigurðr ripostes: 'OEgishjálmr | bergr einugi, | hvars skulu vreiðir vega' (The helm of terror protects nobody, whenever angry men must fight: Fm. 17/1-3).The context of challenging professed strength and courage is further emphasized as Sigurðr continues: 'þá þat finnr, | er með fleirom kømr, | at engi er einna hvatastr' (a man discovers, when he comes into the throng, that nobody is bravest of all: Fm. 17/4-6).Finally, the collocation punctuates Sigurðr's retort to Reginn as they dispute the credit for Fáfnir's death.Sigurðr first highlights Reginn's cowardice (Fm.28), noting that he made sure to keep a safe distance from the action.Then, when Reginn asserts his role in arming Sigurðr for the fight (Fm.29), Sigurðr uses the collocation as he pointedly assigns greater value to courage (which Reginn lacks) than to fancy wargear (Reginn's sole contribution to the victory): 'Hugr er betri | en sé hjǫrs megin, | hvars vreiðir skulu vega' (Courage is better than the might of a sword, whenever angry men must fight: Fm. 30/1-3).
It is also worth noting that the collocation as it is used near-verbatim at Fm. 17/3 ≈ 30/3, 'hvars vreiðir skulu vega' (whenever angry men must fight), has a pronounced gnomic character, an impression strengthened by its further use at Sigrdrífumál 28/3.The two occurrences of the collocation in this form in Fáfnismál may therefore be invoking a background of wisdom poetry, giving Sigurðr's words in each instance a weight of gnomic authority-in other words, the resonance of the traditional expression signifies to the audience that Sigurðr's rebuke in each case should be considered successful because it is expressed through the diction of transmitted wisdom.
Furthermore, an association of the collocation with an act of treachery or deceit on the part of the addressee, which we have seen in Sigrdrífumál, is also present in several other occurrences.In Lokasenna, Iðunn's use of the collocation points to the duplicity underlying her placatory intervention between Bragi and Loki.Frigg's use of it while rebuking Loki invokes Baldr's death, which Loki brought about through deception: in disguise, he tricked Frigg into divulging her son's vulnerability to mistletoe; then, he tricked Baldr's blind brother Hǫðr into shooting Baldr with a mistletoe arrow (Gylfaginning 49).In Fáfnismál, Fáfnir uses the collocation while addressing Sigurðr, who has just fatally wounded him in a stealth-attack, rather than an open confrontation.The collocation is then echoed by Sigurðr in response to Fáfnir's boast of pre-eminence, in which Fáfnir makes reference to 'arfi … miklum mins fǫður' (the great inheritance of my father: Fm. 18/2-3).This recalls to us (and presumably to primary audiences conversant with both the poetic language and the legendary background) that Fáfnir treacherously murdered his father Hreiðmarr-while he slept, a prose insert at Reginsmál 9 reports-and stole his treasure.The verse containing the collocation then recurs nearly verbatim when Sigurðr rebukes Reginn's attempt to claim responsibility for Fáfnir's death.This in turn foreshadows the revelation of Reginn's intention to betray Sigurðr now that Fáfnir has been dealt with.
A skaldic example
It has been briefly mentioned above that the vreiðr/vega collocation also appears once in the extant skaldic corpus, in a verse of Eilífr Goðrúnarson's Þórsdrápa.The courage of Þórr and Þjálfi is emphasized in implied contrast to that of the giants they have vanquished earlier in the poem (e.g., at Þórsdrápa 13).Additionally, if (as seems likely) the 'victorious strike' in verse 2 is a specific reference to Þórr killing Geirrøðr with an iron ingot, it is worth noting that in Snorri's account of the episode a similar contrast is drawn between Þórr and Geirrøðr: as Þórr prepared to hurl the ingot, 'Geirrøðr hljóp undir járnsúlu at forða sér' (Geirrøðr leapt behind an iron pillar to avoid it: Skáldskaparmál 18).We should also note that Þórr's battle with Geirrøðr is the result of a treacherous plan to lure him to Geirrøðr's hall unarmed (Skáldskaparmál 18; cf.Þórsdrápa 1/1-6, 3/1-4).Whilst skaldic diction is beyond our immediate concern here, it is significant that the collocation evokes the same rhetorical overtones here as in its eddic occurrences: hostility and implications of cowardice and treachery.The Þórsdrápa occurrence thus corroborates the case for identifying these as aspects of its traditional resonance.
Conclusion
A full appreciation of the stylistic possibilities generated by traditional referentiality requires an intimate knowledge of the tradition in question.Even with a far more extensive corpus than we possess, much of great significance to the original audiences of the eddic poems would doubtless remain opaque to us as spectatores ab extra.However, a comparison of the contexts in which the collocation of vreiðr and vega occurs in eddic poetry indicates a series of traditional resonances, which poets could exploit in addition to internal structural repetitions to inform their audiences' understanding of particular kinds of character interactions in the characteristically terse and allusive narrative style of eddic poetry (Schorn 2016b: 271).Specifically, the traditional referentiality of the collocation includes associations with hostile speech acts, accusations of cowardice, and acts of betrayal.Aside from contributing to our critical appraisal of individual compositions, this conclusion emphasizes the need for extreme caution in the construction of stemmatic relationships between eddic poems.It is widely recognized that verbal echoes alone are insufficient to establish borrowing from one poem by another (Andersson 1983: 250;Acker 2014: 77-8).Typically, therefore, a case for borrowing is bolstered by the identification of parallel phrasing in comparable narrative contexts (e.g., Andersson 1983: 253-5;von See, La Farge, et al. 1997-2019: 4: 156-7).However, if the traditional resonances of a given expression render it particularly appropriate to certain scenarios, we should expect poets drawing on the same traditional diction to deploy this expression in similar contexts independently (cf.Thorvaldsen 2016: 80-7).
The rhetorical resonances of this collocation highlight the artificiality of a distinction between the oral and the written in the context of Old Norse literature.The CR manuscript is a decidedly literary artefact, displaying meticulous selection and arrangements of its contents on the part of its compiler (Harris 1985: 77;Lindow 2001: 13-14;Clunies Ross 2016: 22-5), and attempts to date the compositions it contains or to reconstruct their preliterary forms are in most cases fraught with uncertainty (Thorvaldsen 2016).Nevertheless, it is likely that even in the literate era in which CR was compiled, the reception of eddic poetry was predominantly aural, with primary audiences highly attuned to the rhetorical resonances of traditional phraseology.With the exception of Þórsdrápa (composed prior to the introduction of literacy to Scandinavia), we cannot know whether the poems discussed here are themselves oral or written compositions; yet, as this case study of a single alliterative collocation has shown, the potency of such expressions was augmented by the ability of hearers and readers to recall occurrences beyond the confines of the immediate performance or manuscript context.This is not to deny the importance of internal repetitions as a stylistic tool in the arsenal of Old Norse poets; indeed, as has been noted in the cases of both Lokasenna and Fáfnismál, the recurrent use of our collocation can be understood within either poem as a closed unit.However, whilst repetition was used by eddic poets in ways that superficially resemble written poetry, given the evident traditionality of the combination of vreiðr and vega and its distribution across multiple unrelated poems, our aesthetic appreciation of eddic poetry is diminished by a conception of recurring phrases which disregards additional layers of signification.
(McKinnell 2014: 179); the repetition of the collocation contributes to emphasizing this dynamic.Similarly, Frigg uses the collocation to impugn Loki's courage and strength in comparison to Baldr, who she suggests would quickly put a stop to Loki's abuse if he were present: 'ok vaeri þá at þér vreiðum vegit' (and there would be furious fighting against you: Ls. 27/6).This attack is unsuccessful, however, since it allows Loki to flaunt his responsibility for Baldr's absence (Ls.28).As implied by CR's opening poem Vǫluspá (31-2, 34) and detailed in Snorri Sturluson's Edda (Gylfaginning 49), it was Loki who engineered Baldr's death by a fatal dart of mistletoe.By repeating the collocation, the Lokasenna poet foregrounds the contrast between Frigg's failed rebuke of Loki and Loki's effective rebuke of Bragi.The same overtones accompany the occurrences of the collocation in Fáfnismál.First, Fáfnir uses it whilst mocking Sigurðr for his upbringing: if he had grown up with his family, 'saei maðr þik vreiðan vega' (a man would see you fight furiously: Fm. 7/3); yet his fosterage by Reginn allows Fáfnir to vilify him as 'haptr | ok hernuminn' (a captive and a prisoner of war: Fm. 7/4-5) and therefore as a coward.To be sure, Fáfnir has already acknowledged his slayer's courage whilst inquiring about Sigurðr's lineage (Fm. 1, 3 and 5), so his comment here should be understood 'in erster Linie als Beleidigung … deren Wahrheitsgehalt unerheblich ist' (primarily as an insult … the truth of which is irrelevant: von See, La Farge, The poem is partially preserved in the Skáldskaparmál section of Snorri Sturluson's Edda.It tells how the giant Geirrøðr contrived to have Þórr brought to his hall without the protection of his hammer Mjǫlnir.Although he is unarmed, Þórr and his servant Þjálfi manage to defeat the giants who attack them, and Þórr himself dispatches Geirrøðr.Eilífr alludes to the final | 8,363.6 | 2024-03-25T00:00:00.000 | [
"Linguistics"
] |
Hopf Bifurcation Analysis of a Diffusive Nutrient–Phytoplankton Model with Time Delay
: In this paper, we studied a nutrient–phytoplankton model with time delay and diffusion term. We studied the Turing instability, local stability, and the existence of Hopf bifurcation. Some formulas are obtained to determine the direction of the bifurcation and the stability of periodic solutions by the central manifold theory and normal form method. Finally, we verify the above conclusion through numerical simulation.
Introduction
One of the most complex and difficult problems in water pollution treatment is the prevention and control of algal bloom. Due to the complexity of the pollution source and the difficulty factor of material removal, it takes a lot of energy, but it is not very effective. Therefore, scientists search for better methods to prevent and cure algal bloom, especially using mathematical models, in order to find reasonable prevention and cure measures [1][2][3][4][5][6][7]. In addition, many scholars further study the dynamics of the N-P model by considering factors such as time delay and diffusion [8][9][10][11][12]. M. Rehim et al. studied a nutrientplankton-zooplankton system with toxic phytoplankton and three delays, and showed the phenomenon of stability switches [8]. Y. Wang and W. Jiang considered a differential algebraic phytoplankton-zooplankton system with delay and harvesting, and indicated that the toxic liberation delay of phytoplankton may affect the stability of the coexisting equilibrium [10]. In particular, Huppert et al. [13] considered the following N-P model where N is the nutrient level and P is the density of phytoplankton. a denotes the constant external nutrient inflow. b represents the maximal nutrient uptake rate. c represents the maximal conversion rate of nutrients into phytoplankton. d stands for the per capita mortality rate of phytoplankton. e denotes the per capita loss rate of nutrients. Relevant research work has analyzed the reasonable, deterministic, and empirical relationship between the abundance of toxin-producing phytoplankton and the diversity of plankton communities with large amounts of plankton but no toxins (called nontoxic plankton plants, NTP) [14]. In the case of toxic substances released by toxic phytoplankton (TPP), a simple model of vegetative phytoplankton was proposed and analyzed to understand the dynamic changes of the phenomenon of the seasonal mass reproductive cycle. The presence of chemical and toxic substances helps explain this phenomenon [15][16][17]. In [18], Chakraborty et al. considered the effect of toxins produced by toxic phytoplankton on the death of nontoxic phytoplankton, and produced the following equation where θ is the release rate of toxic chemicals by the TPP population, and µ denotes the half-saturation constant.
Since the spatial distribution of nutrients and phytoplankton is inhomogeneous, there is diffusion. In addition, there is a time delay in the conversion from nutrients to phytoplankton. So, we incorporate reaction diffusion and time delay into the model (2), that is where d 1 and d 2 are diffusion coefficients for N and P, respectively. is the Laplace operator. This is based on the assumption that the prey and predator are not stationary and will spread randomly . τ is the time delay that occurs for nutrients to be converted to phytoplankton. For analysis convenience, we have denoted The corresponding problem has the following form The content of the paper is arranged as follows. In Section 2, we study the stability and the existence of the Hopf bifurcation. In Section 3, we analyze the property of Hopf bifurcation. In Section 4, we provide a numerical simulation to verify the previous conclusions. Finally, we conclude this paper.
Stability Analysis
In [18], Chakraborty et al. studied the existence of equilibria. We cite the following result. The equilibrium points satisfy the following equation It can be calculated that trivial equilibrium 1 s , 0 and interior equilibrium (N * , P * ), where N * = 1 hP * +s , and P * is a root of the equation We provide the result from [18] as follows.
Lemma 1. The existence of a positive equilibrium for the model (4) can be divided into the following cases.
Proof. Suppose d 1 = d 2 = 0, τ = 0, and hypothesis (11) hold, we can obtain T 0 < 0, D 0 > 0, so the real part of the roots of the characteristic equation is negative, then the equilibrium (N * , P * ) is locally asymptotically stable.
, and It is easy to verify that a − < d 1 d 2 a 0 < a + under the hypothesis (11). (11) hold. For the system (4), we have the following conclusion.
a 0 , then the equilibrium (N * , P * ) is locally asymptotically stable.
a 0 , then the equilibrium (N * , P * ) is locally asymptotically stable.
Proof. We can obtain T n < 0 and D n > 0 for a ≥ d 1 d 2 a 0 . It can be concluded that all the characteristic roots have a negative real part. Then, the equilibrium (N * , P * ) is locally asymptotically stable (so, statement (1) is true). In the same way, statements (1)-(3) are also correct. Suppose the conditions in statement (4) are true, then at least there is a positive real part of eigenvalue root. Then, the equilibrium (N * , P * ) is Turing unstable.
which leads to Let z = ω 2 , Equation (15) is By direct computation, we have Proof. The roots of Equation (16) are It is easy to verify that z + n > 0 if and only if n ∈ M, and z − n is always negative or a non real number.
Suppose one of the conditions (1)-(3) in Theorem 2 and hypothesis (11) hold, from Equation (14), we can obtain For n ∈ M, then Equation (8) has a pair of purely imaginary roots ± iω n at τ j n , j ∈ N 0 , Proof. From (8), we can obtain Theorem 3. For system (4), assume one of the conditions (1)-(3) in Theorem 2 and hypothesis (11) hold, then we have the following conclusion.
Then, we can obtaiṅ That is, Using the definition of Aτ and (46), we have that for −1 ≤ θ < 0 That is, Similarly, we have That is, Then,
Conclusions
Diffusion and time delay was incorporated into a nutrient-phytoplankton model. The instability and Hopf bifurcation induced by the time delay was studied. Through the central manifold theory and normal form method, some parameters were given to determine the property of bifurcating periodic solutions. The results indicate diffusion may induce Turing unstable. The release rate β of toxic chemicals by the TPP population has a stabilizing and destabilizing effect on the stability of the positive equilibrium. In addition, the time delay can also affect the stability of the positive equilibrium, and it can induce periodic oscillation of prey and predator population density. | 1,600.2 | 2022-01-29T00:00:00.000 | [
"Mathematics",
"Environmental Science"
] |
Electricity Theft Detection in Smart Grids based on Deep Neural Network
Electricity theft is a global problem that negatively affects both utility companies and electricity users. It destabilizes the economic development of utility companies, causes electric hazards and impacts the high cost of energy for users. The development of smart grids plays an important role in electricity theft detection since they generate massive data that includes customer consumption data which, through machine learning and deep learning techniques, can be utilized to detect electricity theft. This paper introduces the theft detection method which uses comprehensive features in time and frequency domains in a deep neural network-based classification approach. We address dataset weaknesses such as missing data and class imbalance problems through data interpolation and synthetic data generation processes. We analyze and compare the contribution of features from both time and frequency domains, run experiments in combined and reduced feature space using principal component analysis and finally incorporate minimum redundancy maximum relevance scheme for validating the most important features. We improve the electricity theft detection performance by optimizing hyperparameters using a Bayesian optimizer and we employ an adaptive moment estimation optimizer to carry out experiments using different values of key parameters to determine the optimal settings that achieve the best accuracy. Lastly, we show the competitiveness of our method in comparison with other methods evaluated on the same dataset. On validation, we obtained 97% area under the curve (AUC), which is 1% higher than the best AUC in existing works, and 91.8% accuracy, which is the second-best on the benchmark.
I. INTRODUCTION
E LECTRICITY theft is a problem that affects utility companies worldwide. More than $96 billion is lost by utility companies worldwide due to Non-Technical Losses (NTLs) every year, of which electricity theft is the major contributor [1]. In sub-Saharan Africa, 50% of generated energy is stolen, as reported by World Bank [2].
The ultimate goal of electricity thieves is to consume energy without being billed by utility companies [3], or pay the bills amounting to less than the consumed amount [4]. As a result, utility companies suffer a huge revenue loss due to electricity theft. [5] reports that in 2015, India lost $16.2 billion, Brazil lost $10.5 billion and Russia lost $5.1 billion. It is estimated that approximately $1.31 billion (R20 billion) revenue loss incurred by South Africa (through Eskom) per year is due to electricity theft [2]. tacks [4], [7]. Recently, researchers have worked towards detecting electricity theft by utilizing machine learning classification techniques using readily available smart meters data. These theft detection methods have proved to be of relatively lower costs [8]. However, existing classification techniques consider time-domain features and do not regard frequencydomain features, thereby limiting their performance.
Regardless of the fact that there is active ongoing research on electricity theft detection, electricity theft is still a problem. The major cause of delay in solving this problem may be that smart grids deployment is realized in developed nations while developing nations are lagging behind [9]. The challenges of deploying smart grids include the lack of communication infrastructure and users' privacy concerns over data reported by the smart meters [10]. However, [10] reports that smart meters are being considered by many developed and developing countries with aims that include solving NTLs. [11] predicted smart grids global market to triple in size between 2017 and 2023, with the following key regions leading smart grids deployment: North America, Europe and Asia.
In this paper, we present an effective electricity theft detection method based on carefully extracted and selected features in Deep Neural Network (DNN)-based classification approach. We show that employing frequency-domain features as opposed to using time-domain features alone enhances classification performance. We use a realistic electricity consumption dataset released by State Grid Corporation of China (SGCC) accessible at [12]. The dataset consists of electricity consumption data taken from January 2014 to October 2016. The main contributions are as follows: • Based on the literature, we propose a novel DNN classification-based electricity theft detection method using comprehensive time-domain features. We further propose using frequency-domain features to enhance performance. • We employ Principal Component Analysis (PCA) to perform classification with reduced feature space and compare the results with classification done with all input features to interpret the results and simplify the future training process. • We further use the Minimum Redundancy Maximum Relevance (mRMR) scheme to identify the most significant features and validate the importance of frequencydomain features over time-domain features for detecting electricity theft. • We optimize the hyperparameters of the model for overall improved performance using a Bayesian optimizer. We further employ an adaptive moment estimation (Adam) optimizer to determine the best ranges of values of the other key parameters that can be used to achieve good results with optimal model training speed. • Lastly, we show 1% improvement in AUC and competitive accuracy of our model in comparison to other data-driven electricity theft detection methods in the literature evaluated on the same dataset.
The remainder of this paper is organized as follows. Section II covers the related work done in literature to tackle the electricity theft problem. In Section III, we briefly introduce techniques used in this paper. Section IV covers step by step method taken in this work; which includes dataset analysis and work done to improve its quality and customers' load profile analysis which lead to features extraction and classification. In Section V, we show and discuss the results. We finally conclude the paper in Section VI.
II. RELATED WORK
Research on electricity theft detection in smart grids has attracted many researchers to devise methods that mitigate against electricity theft. Methods used in the literature can be broadly categorized into the following three categories: hardware-based, combined hardware and data-based detection methods and data-driven methods.
Hardware-based methods [13]- [19] generally require hardware devices such as specialized microcontrollers, sensors and circuits to be installed on power distribution lines. These methods are generally designed to detect electricity theft done by physically tampering with distribution components such as distribution lines and electricity meters. They can not detect cyber attacks. Electricity cyber attack is a form of electricity theft whereby energy consumption data is modified by hacking the electricity meters [7].
For instance, in [13], an electricity meter was re-designed. It used components that include: a Global System for Mobile Communications (GSM) module, a microcontroller, and an Electrically Erasable Programmable Read-Only Memory (EEPROM). A simulation was done and the meter was able to send a Short Message Service (SMS) whenever an illegal load was connected by bypassing the meter. Limited to detecting electricity theft done by physically tampering with distribution components such as distribution lines and electricity meters. Authors in [16] used the GSM module, ARM-cortex M3 processor and other hardware components to solve the electricity theft problem done in the following four ways: bypassing the phase line, bypassing the meter, disconnecting the neutral line, and tampering with the meter to make unauthorized modifications. A prototype was built to test all four possibilities. The GSM module was able to notify with SMS for each theft case.
Authors in [17] designed ADE7953 chip-based smart meter which is sensitive to current and voltage tempering, and mechanical tempering. ADE7953 was used to detect overvoltage, dropping voltage, overcurrent, the absence of load and other irregularities in voltage and current. It sent an interrupt signal to the Microcontroller Unit (MCU) which reported tampering status. Mechanical tampering was overcome by connecting a tampering switch to MCU's IO ports so that it can send alarm signals to MCU once tampered with. The design was tested with tampering cases such as connecting the neutral and the phase lines, connecting the meter input and output in reverse mode, and bypassing the phase line to load. The probability of detection failure was 2.13%.
Authors in [15] used a step down transformer, voltage divider circuit, microchip and other hardware components to design a circuitry to detect electricity theft by comparing forward current on the main phase line with reverse current on the neutral line. The circuitry was installed before the meter.The design was tested on Proteus software and on actual hardware. When the meter was bypassed, the problem was detected and an alarm sounded. In [14], a circuit to detect electricity theft done by bypassing the meter was designed. The transformers, rectifiers, microcontroller, GSM module and other hardware components were used. The GSM controller notified the operator with SMS when the meter was bypassed.
Authors in [18] proposed putting the Radio Frequency Identification (RFID) tags on ammeters and capturing unique data about each ammeter. Ammeters were to be tracked and managed real-time. Electricity theft was to be inspected onsite. Damaged, removed or a tag with a different information from the original one means high possibility that an electricity theft happened. Evaluation based on analysis on cost of deployment. With a case study made on utility company in China, Return on Investment (ROI) was found to be >1. In [19], An Arduino-based real-time electricity theft detector was designed. The following hardware was used: Arduino Uno, GSM module, current sensors and LCD. The Arduino Uno obtained measurements from current sensors which were located one on the secondary side of the transformer and the other on the electric service cap. If the difference between current sensors' measurements exceeded a set threshold, the message would be sent to the operator via a GSM module. The simulation was done using Proteus 8 software and the prototype was built on hardware, which was able to report theft cases when tested.
Apart from their inability to detect cyber attacks, these methods are also expensive due to their need for special hardware deployment and maintenance. Combined hardware and data-based electricity theft detection methods [20]- [22] employ the use of hardware, machine learning and/or deep learning techniques to tackle the electricity theft problem. Due to hardware requirements, these methods also pose the challenge of being expensive to deploy and maintain.
In [20], a method to measure the total consumption of a neighbourhood and compare the results with the usage reported by the smart meters in that neighbourhood was proposed. A significant difference between smart meters' and transformers' measurements would mean the presence of unfaithful customers in the neighbourhood. To locate the unfaithful customers in the neighbourhood, the authors proposed using a Support Vector Machine (SVM) classifier. The classifier was tested on a dataset of 5000 (all faithful) customers. A maximum detection rate of 94% and a minimum false positive rate of 11% were achieved.
Authors in [22] developed a predictive model to calculate TLs. To get NTL, TLs would be subtracted from total distribution network losses. Based on an assumption that distribution transformers and smart meters share data to the utility after every 30 minutes, a smart meter simulator was used to generate data for 30 users in 30 minutes intervals for 6 days. On the simulator, unfaithful users stole electricity by bypassing the meter. Stolen electricity was varied between 1% and 10% of the total consumption. For stolen electricity value over 4%, the detection rate was 100%, which diminished as stolen electricity percentage was decreased.
In [21], a method which would use an observer meter that would be installed on a pole away from households and record the total amount of electricity supplied to n households where it is suspected that one or more meters have been tampered with was proposed. The observer meter would have camera surveillance to protect it from being tampered with. A mathematical algorithm that utilizes data from an observer meter and smart meters to detect a smart meter tempered with was developed. A mathematical algorithm was tested with a real-world consumption dataset by increasing the consumption of some meters which were picked randomly. The algorithm was able to detect the meters with altered consumption.
Due to high-cost demand in the above categories, many researchers work on data-driven methods to overcome the electricity theft problem. For instance, the authors in [3] designed an electricity theft detection system by employing three algorithms in the pipeline: Synthetic Minority Oversampling Technique (SMOTE), Kernel function and Principal Component Analysis (KPCA) and SVM. They used SMOTE to generate synthetic data for balancing an unbalanced dataset, KPCA to extract features and SVM for classification. They obtained maximum overall classifier quality characterized by Area Under the Curve (AUC) of 89% on validation.
Authors in [4] used wide and deep Convolutional Neural Networks (CNN) model to detect electricity theft. Based on that normal electricity consumption is periodical while stolen electricity consumption data is not periodical, wide was to learn multiple co-occurrences of features for 1-D series data, while deep CNN was used to capture periodicity with data aligned in a 2-D manner by weeks. They varied training and validation data ratios, to obtain maximum AUC value of 79%. By utilizing the same dataset used in [3] and [4], the method we present in this paper achieves AUC results beyond 90% on both validation and testing.
In [23], PCA was used to transform original highdimensional consumption data by extracting Principal Components (PCs) which retained the desired variance. An anomaly score parameter that was defined between set minimum and maximum thresholds was introduced. For each test sample, the anomaly score parameter was calculated. If the result was not between the set thresholds, the sample would then be treated as malicious. The true positive rate (TPR) was used to evaluate the method, which hit the best-recorded value of 90.9%. Authors in [24] used One-Class SVM (O-SVM), Cost-Sensitive SVM (CS-SVM), Optimum Path Forest (OPF) and C4.5 tree. From customer consumption data, VOLUME 4, 2016 different features were selected, and the performance of each classifier was analyzed independently on a different set of features, followed by combining all classifiers for the best results. Best results were achieved when all classifiers were combined, with 86.2% accuracy.
Authors in [25] employed a combination of CNN and Long Short-Term Memory (LSTM) recurrent neural network deep learning techniques. Seven hidden layers were used, of which four of them were used by CNN and three were utilized by LSTM. This method relied on CNN's automatic feature extraction ability on a given dataset. Features were extracted from 1-D time-series data. On model validation, the maximum accuracy achieved was 89%. The authors in [26] used a combination of Local Outlier Factor (LOF) and k-means clustering to detect electricity theft. They used kmeans clustering to analyze the load profiles of customers, and LOF to calculate the anomaly degrees of customers whose load profiles were from their cluster centres. On the evaluation of the method, they attained an AUC of 81.5%. Our model achieves a maximum value of 91.8% accuracy and 97% on validation.
In [27], two electricity theft models were developed. The first model is based on Light Gradient Boosting (LGB) classifier. A combination of SMOTE and Edited Nearest Neighbour (ENN) was used to balance the dataset. Feature extraction was done using AlexNet, followed by classification with LGB. This proposed model was named as SMOTEENN-AlexNet-LGB (SALM). The second model is based on the Adaptive Boosting classifier. Conditional Wasserstein Generative Adversarial Network with gradient penalty (CWGAN-GP) was used to generate synthetic data that resembled the minority class data to balance data of the unbalanced classes. Feature extraction was performed using GoogleNet, then classification by AdaBoost followed. The proposed model was named as GAN-NETBoost. The models were evaluated with SGCC data used in this work. SALM and GAN-NetBoost attained an accuracy of 90% and 95%, and AUC of 90.6% and 96% respectively on validation.
Although these models were able to achieve impressive results, their consideration of time-domain features alone limited their performance. Our solution shows that adding frequency-domain features on time-domain features improves classification performance.
III. PRELIMINARIES
In this section, we give a summary of the main techniques used, which are: Deep Neural Networks (DNNs), Principal Component Analysis (PCA), and Minimum Redundancy Maximum Relevance (mRMR).
A. DEEP NEURAL NETWORKS
Artificial Neural Networks (ANNs) are a class of machine learning techniques that have been built to imitate biological human brain mechanisms [28], [29]. They are typically used for extracting patterns or detecting trends that are difficult to be detected by other machine learning techniques [30].
They consist of multiple layers of nodes/neurons which are connected to subsequent layers [29]. A neuron is the basic element of a neural network, which originates from the McCulloch-Pitts neuron, a simplified model of a human brain's neuron [31]. Figure 1 shows a model diagram of a neuron that comprises a layer following the input to the ANN.
Inputs
Weights Bias g FIGURE 1. First hidden layer neuron model It consists of an activation function f , which takes a weighted sum of the real number input signal and gives real number output y given by Equation (1).
x is input vector, w is weights vector and b is the bias [31]. Neural network nodes mimic the brain's neurons, while connection weights mimic connections between neurons, which are unique for each connection [28], [29]. A neural network stores information in the form of weights and bias.
The Deep Neural Networks (DNNs) concept originates from research on ANNs [32]. DNNs are characterized by two or more hidden layers [28]. They are able to learn more complex and abstract features than shallow ANNs [33]. Oftentimes in classification problems, the output layer is made up in such a way that one neuron represents a certain class [29]. All neural network layers are used to filter and learn the complicated features, except for an output layer which classifies based on learnt features [29] [34]. Before DNNs development, most machine learning techniques explored architectures of shallow structures which commonly contain a single layer of non-linear transformation [32]. Examples of these architectures include SVMs, logistic regression and ANNs with one hidden layer.
DNNs have different architectures, which are used to solve different problems. Examples of DNN architectures include feed-forward DNN, convolutional DNN and recurrent DNN. In this research work, a fully connected feed-forward DNN was used. the typical structure of a fully connected feedforward DNN is shown in Figure 2.
The DNN given in Figure has the following major parts: • Input layer (x) A layer that comprises input data features or representation.
Hidden Layers
Output Layer Input Layer The layers of neurons between the input and output layers. They are used to analyse the relationship between the input and output signals [30].
Weights of the connections between the hidden layers.
Weights between the last hidden layer and the output layer. • Output layer (y) The last layer of a DNN. It gives the output of the network from network inputs. In a feed-forward architecture, computation is a sequence of operations on the output of a previous layer. The final operations generate the output. For a given input, the output stays the same, it does not depend on the previous network input [33]. [33] reports that ANNs were first proposed in the 1940s, and research on DNNs emerged in the 1960s. In 1989, the LeNet network, which used many digital neurons, was built for recognizing hand-written digits. Major breakthroughs were seen in the years beyond 2010, with examples such as Microsoft's speech recognition system, AlexNet image recognition system, and DNN accelerator research such as Neuflow and DianNao brought into play.
1) History of DNNs Development
The following reasons are reported by [30], [32], [33] as major contributors to DNNs' improved development: • Advancements in semiconductor devices and computer architecture, leading to parallel computing and lower costs of computer hardware. • Huge amount of data obtained by cloud providers and other businesses, making large datasets that train DNNs effectively. • Advances in machine learning and signal/information processing research which leads to the evolution of techniques to improve accuracy and broaden the domain of DNNs application. With present technology permission, DNNs can have a count of layers that is beyond a thousand [33].
2) DNN Training
A large dataset and high computational abilities are the major requirements in training the DNN since weight updates require multiple iterations [33]. DNN training process is concerned with adjusting the weights between the neurons [30]. Through the training process, the DNN learns information from the data. Learning can be in the following major four ways: supervised, semi-supervised, unsupervised or reinforcement [33]- [36].
In this work, supervised learning was used. The typical procedure for supervised learning in DNNs as given by [28], [34] is as follows: 1 3) Output error is calculated, and then weights adjusted with an aim to reduce an error. 4) Steps 2 and 3 are repeated for all training data.
3) Backpropagation
A loss function of a multi-layered ANN is composed of weights from successive layers between input and output layers [36]. Backpropagation uses chain rule to obtain the gradient of the loss function in terms of summation of local gradient products over different nodes connections between input and output layers [28], [29], [36]. Backpropagation algorithms typically use gradient-based optimization algorithms to update the neural network parameters on each layer [37].
4) Activation functions
An activation function takes an input signal, by simulating a response of a biological neuron, transforms the signal into an output signal which may be an input to another neuron [38], [39]. There are many activation functions, which can be generally divided into two kinds: the linear and non-linear activation functions. The type of activation function used in a DNN plays a major role in the prediction accuracy of the model [39]. The selection of an activation function depends on the reasons such as computational power, analytic flexibility and whether the desired output should be continuous or discrete [30]. Let z = (w i x i ) + b. Then Equation (1) can be re-written as shown in Equation (2).
Linear activation functions Linear activation functions usually have an activation that is directly proportional to the input. They can be expressed in the form of Equation (3).
where C is a constant. The output of the linear activation function is in the range (−∞, ∞) and its derivative is f (z) = C. Since the gradient is not related to the input, an error can not be minimized by the use of a gradient [40]. This activation function is normally used in regression problems [41].
Non-linear activation functions Non-linear activation functions are widely used in DNNs because of their ability to adapt to data variations and differentiate outputs [40]. Among the many developed nonlinear activation functions, the most popular are described as follows [38]- [41].
Due to less computation in finding its derivative, this activation function is widely used in shallow neural networks. It is rarely used in DNNs' hidden layers because of its soft saturation property which makes DNNs delay converging during training. • Hyperbolic tangent activation function Like the sigmoid, hyperbolic tangent is continuous and differentiable everywhere. It is given by Equation (6). Its derivative is given by Equation (7).
The input z ∈ (−∞, ∞) and an activation f ∈ (−1, 1). Using a hyperbolic tangent for activation makes the neural networks converge faster than when using a sigmoid, therefore a hyperbolic tangent is more preferred than a sigmoid.
• Rectified linear unit activation function
Rectified linear unit (ReLU) activation function is given by Equation (8) and is derivative by Equation (9).
Compared to sigmoid and hyperbolic tangent activation functions, ReLU is the simplest and most commonly used in DNNs because of its good property of being close to linear, hence better convergence. It is more efficient since it activates less number of neurons at the same time. For z > 0, its gradient is constant thereby avoiding the vanishing gradient problem. Its gradient is cheaper to compute as there are no calculations that involve exponents. • Softmax activation function Softmax activation function is given by Equation (10).
where K is the number of classes. Softmax is typically used in the output layer of a DNN for classification purposes. The output of a softmax is a probability of a particular class j, therefore if the softmax activation function is used in the output layer, all of the output layer activations sum to 1.
B. PRINCIPAL COMPONENT ANALYSIS
PCA [42] is used to extract important information from a data table of inter-correlated features/variables that represent observations. This extracted information is represented as a new set of orthogonal variables known as Principal Components (PCs). In this work, PCA uses a Singular Value Decomposition (SVD) algorithm [43] which works in the following manner: for input feature matrix X, SVD decomposes it into three matrices, i.e., X = PQR , such that: • P is the normalized eigen vectors of the matrix XX , where E is a diagonal matrix of eigen values of matrix XX , and • R is the normalized eigen vectors of matrix X X. When PCA is applied to a matrix X of size m × n, n PCs {c} n i=1 are obtained, which are ordered in descending order with respect to their variances [23]. A PC at position p is given by and its variance is obtained by evaluating ||Xc p || 2 .
The main goals achieved with PCA are as follows: • Extraction of most important information from data/feature table, thereby compressing and simplifying dataset description, and • Analysis of observations and variables' structure.
For dimensionality reduction purposes, the first r ≤ n PCs that retain acceptable variance can accurately represent feature matrix X in a reduced r-dimensional subspace.
C. MINIMUM REDUNDANCY MAXIMUM RELEVANCE
An mRMR [44], [45] is a feature selection scheme that selects features that have a high correlation with the response variable and low correlation with themselves. It ranks features based on mutual information of a feature and a response variable, and pairwise mutual information of features. Mutual information between variables A and B is given by For all features {X i }, maximum relevance R l is implemented using mean value of their mutual information with an output class O.i.e., Minimum redundancy R d helps to select features that are mutually maximally dissimilar. It is given by: where X i , X j ∈ X. mRMR feature selection goal is achieved by optimizing relevance and redundancy in the following manner: max(R l − R d ).
IV. DNN-BASED ELECTRICITY THEFT DETECTION METHOD
The electricity theft detection method outlined in this section consists of the following three steps: Data Analysis and Preprocessing, Feature Extraction, and Classification. Figure 3 shows the workflow diagram.
A. DATA ANALYSIS AND PRE-PROCESSING
In this sub-section, we present the dataset used and its quality improvement by identifying and removing observations that had no consumption data. In this work, an observation refers to a single instance/record in the dataset, for the duration of measured consumption. i.e., given a dataset A of size N , We show customers' load profiles analysis. We further present data interpolation and synthetic data generation details that have been undertaken. As stated in Section I, we used a realistic electricity consumption dataset released by SGCC, which is accessible at [12]. The dataset consists of daily electricity consumption data taken from January 2014 to October 2016, summarized in Table I. The sampling rate of the data is uniform for every customer, it is one measurement per day; which corresponds to the total power consumption for that day. The used dataset consists of 42372 observations, of which 3615 observations are electricity consumption data of unfaithful customers and the remaining observations are electricity consumption data of faithful customers.
1) Dataset Analysis and Preparation
As with many datasets used in the literature, data comes with many errors caused by factors such as smart meters failures, data storage problems, data transmission issues and unscheduled systems maintenance [4]. Dataset used in this work is no exception. It consists of traces of non-numerical or null values.Using data analysis methods, we found approximately 5.45% of observations in this dataset to either have only null values, or zeros, or a combination of both, for the whole duration of 1034 days. These observations were regarded as empty observations. i.e., An observation a is regarded as an empty observation if a i = 0 or a i / ∈ R for all a i ∈ a. These observations do not have any differentiating characteristics between the classes since they do not have any consumed electricity record greater than 0 kWh. To improve the dataset quality, these observations were removed. They could not be identified with any class as they were labeled with either of the classes, therefore they were discarded. The third column of Table I shows a summary of observations left after the removal of empty observations. Figure 4 shows line plots of consumption data of a faithful customer and an unfaithful customer against the consumption days, for the duration of three months. Comparing the two graphs, we observed that the consumption behaviour of the honest customer is mostly uniform and has a predictable trend, while electricity thief's consumption behaviour takes different forms and is not predictable. We further carried out histogram analyses for both classes of customers, as shown in Figure 5.
From the histograms shown, we observe that for faithful customer's consumption data, statistical parameters mean, mode, and median are generally closer to the histogram centre as compared to unfaithful customer's consumption data. We did a similar analysis for many customers and found that an observation presented here is true for most of the dataset. From these observations, we argue that by defining outliers as values beyond three Median Absolute Deviations (MAD), honest customers can be characterized as having fewer outliers percentage in a given data, than unfaithful customers.
2) Data Interpolation
For all observations consisting of a combination of null or non-numerical values and real consumption values, data were interpolated. Piecewise Cubic Hermite Interpolating Polynomial (PCHIP) [46] was used to fill in missing data during data interpolation while preserving consumption patterns. A cubic Hermite interpolating polynomial H(x) is a shape-preserving interpolant which preserves data monotonicity on a sub-interval x i ≤ x ≤ x i+1 applied to. For the data consumption vector containing NaN values at the beginning, the raw data mean was evaluated excluding NaN values and then inserted as the first vector element. The rest of the elements were filled in using PCHIP. This helped to maintain consumption shape and avoided adding outliers to data. Figure 6 shows an example of one observation taken randomly before and after interpolation. A consumption duration of 200 days around days with missing consumption data is shown for clear presentation. Interpolated data points make a smooth curve that lies between the minimum and maximum near points with no overshooting, as can be seen from Figure 6b. In this manner, the consumption data is preserved from the addition of outliers and data points that can make interpolated data pattern to resemble unfaithful customer's consumption pattern of the minority class of unfaithful customers, such shown in Figure 4b. (b) Consumption data after interpolation FIGURE 6. Plots of consumption data before and after interpolation
3) Synthetic Data Generation
After eliminating empty observations and interpolating data, we carried out the initial classification process. Experimenting with the dataset as is, we observed that the classifier satisfactorily classified faithful customers and performed badly on unfaithful customers due to a class imbalance problem [20], [25]. A class imbalance problem is a situation whereby the number of observations in one class is much greater than the number of observations in the other class. In a class imbalanced problem, classification models classify the majority class on a dataset successfully, while performing badly on the minority class [25]. Dataset used in this work has faithful customers number that is much greater than that of unfaithful customers. We solved the class imbalance problem in the following manner: 1) Define q and r as the number of faithful and unfaithful customers respectively and evaluate the difference p = q − r.
2) From a set of faithful customers observations, randomly select p observations represented by p × 1034 matrix O defined by Equation (15) 3) Inspired by [20] and dataset analysis observations in IV-A, we evaluated synthetic observations O s by Hadamard product in Equation (16).
where C is a matrix of randomly generated numbers of size p × 1034 with elements between 0 and 1. This helps to distort the pattern of consumption as observed through faithful customers' consumption data line plots shown in IV-A; hence the result better represents unfaithful customers' consumption data. This approach of generating synthetic is cheap and fast to do as it uses the available data of faithful customers' class to generate data for the opposite class. It involves a single operation on the measured data, which is multiplication of measured data by a matrix of randomly generated numbers. The resulting data was added to the original dataset, labeling it as belonging to unfaithful customers consumption class. The fourth column in Table I shows a summary of observations after synthetic data generation.
B. FEATURE EXTRACTION
Electricity consumption data used in this project is univariate time-series data. A univariate measurement is a single measurement frequently taken over time [47]. For solving classification problems, data can be represented by its features (properties), which can then be fed as input to the classifier, as is the case in [29], [34] and [48]. Data is classified based on the similarity between features [47] given a dataset of different samples. In this work, time-domain and frequencydomain features were extracted and used as input to a deep neural network for classification. Classification performance comparison between time-domain, frequency-domain and combined features from both domains was carried out.
1) Time-domain Feature Extraction
As shown in IV-A, faithful and unfaithful customers' consumption data differs clearly by a pattern of consumption, as shown by line plots and histogram graphs. Based on this information, time-domain features stipulated in Table II can collectively be used to differentiate between the two classes of customers. Apart from an observation that consumption data of faithful customers roughly follow a predictable pattern, and unfaithful customers consumption behaviour is not VOLUME 4, 2016 predictive, as shown in Figure 4, customers do not consume an equal amount of energy per given time. Energy needs per customer may differ due to different reasons such as the number of appliances used, kind of appliances per household, household size, etc. To achieve higher accuracy in classifying features, all observations are made to fit within the same axes. This is achieved by normalizing data for each observation using the Min-Max method [49] given by Equation (17). The Min-max method shrinks the data between 0 and 1 while keeping the original consumption pattern.
2) Frequency-domain Feature Extraction
Fourier theorem states that a periodic signal x(t) can be represented by a summation of complex sinusoidal signals with frequencies that are an integer multiple of fundamental frequency f T [50]. Using the Fourier theorem, the consumption data graphs shown in IV-A can be seen as a time series signal that can be transformed into the frequency-domain by using Fourier transform. Represented in frequency-domain, we extracted frequency-domain features from each observation. Since neural networks are sensitive to diverse input data, using Equation (17), features were normalized after being extracted so that they could be fed as input to the classifier. Table II shows features extracted from both domains.
1) Network Architecture
A fully connected feed-forward DNN architecture shown in Figure 7 was used for the classification process.
In order to avoid network underfitting and overfitting [35], the following rule of thumb methods [35], [51] were considered in the design of hidden layers of a deep neural network classifier shown in Figure 7:. Rectified Linear unit (ReLU) activation function was used in the hidden neurons because of its better convergence property in comparison to other activation functions [28].
2) Training
The maximum number of training iterations was limited to 1000. The classification approach was split into four parts. In the first part, only time-domain features were used for classification. In the second part, only frequency-domain features were used. The third part comprised of combined features from both domains, while in the last part, classification was performed in reduced feature space by incorporating PCA.
Holdout validation scheme was used as follows: in all the procedures, as a rule of thumb, 80% of the whole data was used for training and validation, while 20% of the whole data was used for testing. Within training and validation data, 80% was used for training while 20% was used for validation. Similar results were obtained when using k-fold cross-validation scheme with k = 5. More about using k-fold cross-validation scheme with k = 5 can be seen in [52] as an example.
Recall/True Positive Rate (TPR): is the measure of the fraction of positive examples that are correctly labeled. It is given by: Precision/Positive Predictive Value (PPV): is the measure of the fraction of examples classified as positive that are truly positive. It is given by: F1-Score: shows the balance between precision and recall. It is given by: Accuracy: shows the fraction of predictions classified correctly by the model. It is given by:
Accuracy =
Number of correct predictions Total number of predictions Matthews Correlation Coefficient (MCC): a single digit that measures a binary classifier's performance. Its value ranges from -1 to +1, with values closer to +1 signifying good performance, while values closer to -1 signify bad performance. MCC is given by: Area Under the Curve (AUC): measures the classifier's overall quality. Larger AUC values indicate better classifier performance.
4) Hyperparameters Optimization
To achieve the best classification performance at a reasonable amount of time, we used the Bayesian optimization method [57] to tune the following hyperparameters: number of hidden layers, size of each layer, regularization strength and activation function. Bayesian optimization is derived from Bayes' theorem which states that for events A and B, This optimization method determines the distribution of hyperparameters by assuming that an optimization function obeys the Gaussian distribution. To get the best combination of hyperparameters, 100 optimization steps were conducted. The resultant optimized network was trained and tested in a similar manner as the network in Figure 7.
5) Impact of Key Parameters Investigation
Using adaptive moment estimation (Adam) optimizer [58], an impact of the following three key parameters were investigated on the optimized network: initial learning rate, minibatch size and l2-regularization parameter. Data was divided into two parts: the training and validation data.
The volume of the training and validation/test data plays an important role in classification success. The higher the correlation between input features and the class label, the lesser the data needed for training [59]. However, given a dataset, the training data portion of less than 50% is not adviced for as it will negatively affect the test results [59]. With this in mind, we therefore determined parameters' impact with different training data percentages.
We carried out the following procedure for 60%, 70% and 80% training data portions. For each parameter, its impact was investigated by determining training and validation accuracies with varied parameter values. Parameters were logarithmically varied in 100 steps between the initial and final values. For each step, the number of training epochs was limited to 30. The other parameters were held at fixed values while adjusting a parameter under study. Table III shows investigated parameters' initial values, step values, final values as well as fixed values.
V. RESULTS AND DISCUSSION
In this section, we show and discuss the experimental results. In Section V-A, we present results obtained before synthetic data generation. In Section V-B, we show a comparison between classification performance when using time-domain features, frequency-domain features and combined features from both domains as inputs to the classifier. We analyze PCA dimensionality reduction impact on experimental results in Section V-C. We present Bayesian optimization results as well as best results attained with optimized classifier in Section V-D, and we finally present an investigation of optimal parameter settings for best classification performance by varying different parameters using Adam optimizer in Section V-E.
A. VALIDATION RESULTS BEFORE SYNTHETIC DATA GENERATION
As stated in Section IV, when there was an imbalance in the number of observations between two classes, the classifier performed badly on the class with a relatively lower number of observations. The classifier shown in Figure 7 was trained with features extracted from an original dataset with no augmented synthetic data. 80% of the data was used for VOLUME 4, 2016 training while 20% was used for validation. The third column of Table IV shows the validation results. For the faithful customers class, validation results are much better than the unfaithful class. This can be seen by a comparison between faithful and unfaithful customers' recall, precision and F1score shown.
Compared with validation results in combined domains before the incorporation of PCA, there was no significant change in the recall, precision and F1-score for faithful customers' class since the difference in corresponding values was within 1% margin. However, for the unfaithful class, which was the minority class, validation results in terms of recall, precision and F1-score were not good at all before balancing the classes. A significant improvement was obtained after balancing the classes. This shows that the sensitivity of the classifier to the minority class was not as good as its sensitivity to the opposite class.
The subsequent subsections show the results which were obtained after augmenting synthetic data to the original dataset to balance classes.
B. DIFFERENT DOMAINS FEATURES' CONTRIBUTION ANALYSIS
To ensure the reliability and robustness of the method introduced in this work, we present experimental results based on widely-accepted performance metrics summarized in Table IV. To simplify the analysis, classification performance between time-domain, frequency-domain and combined features from both domains is graphically presented in Figure 8.
From Table IV and Figure 8, it can be seen that the classification process taken with time-domain features gave impressive validation and test results for both faithful and The best results were obtained when all features from both domains were combined. For example, on validation, accuracy was 87.5%, which improved to 89.9%, and finally 91.1% when the experiment was done with time-domain features, frequency-domain features and all features from both domains respectively. The red trend line in Figure 8 graphs portrays significant improvement on results obtained from experiments done with time-domain features, frequencydomain features and all features from both domains. This improvement can be explained by a bar chart of predictors presented in order of their prominence shown in Figure 9, which has been produced through the mRMR scheme. As shown by Figure 9 bar chart, there are more frequencydomain features to the left of the bar chart (i.e., features with the best scores) than time-domain features, with mean frequency achieving the highest predictor score. We confirmed the exactness of features' ranking through the mRMR scheme by doing classification tasks using top 3, middle 3 and bottom 3 features on the same network in Figure 7. Figure 10 bar chart shows classification accuracy and AUC-ROC results.
Comparing the results in Figure 10, we observed that accuracy and AUC-ROC are best for the top 3 features and worst for the bottom 3 features, as expected. MCC was determined on the last experiment when all features were combined. Its values were found to be 0.84 and 0.75 on validation and test respectively, which are closer to +1 than -1. AUC-ROC values were found to be 97% and 93% on validation and test respectively. These results portray a satisfactory overall classification task.
C. ANALYSIS OF COMPONENTS REDUCTION WITH PCA
When PCA was incorporated with the component reduction criterion of leaving enough components to explain 95% Figure 11, we observed that frequency-domain features contributed more to principal components. This was also confirmed by features importance scores analysis shown by Figure 9 based VOLUME 4, 2016 on the mRMR scheme. The last two columns in Table IV shows both validation and test results obtained after components reduction with PCA. We observed that with just seven principal components, we were able to achieve results very close to when no feature reduction criterion was used.
D. HYPERPARAMETERS OPTIMIZATION RESULTS
Following the hyperparameters optimization procedure stipulated in Section IV-C4, Figure 12 shows observed objective function values vs optimization steps. The best hyperparameters combination was obtained at the 26 th optimization step and remained unchanged till the 100 th step. Their values are shown in Table V. An improved classification network architecture constructed with optimized hyperparameters achieved maximum validation and test accuracies of 91.8% and 88.1% respectively, which are 0.7% and 0.8% higher than an unoptimized architecture. The classifier obtained a maximum AUC-ROC value of 97%.
E. KEY PARAMETERS' IMPACT ANALYSIS 1) Impact of initial learning rate
To determine the impact of the initial learning rate on training and validation accuracies, the initial learning rate was varied between 10 −5 and 10 −2 in 100 steps. Figure 13 shows scatter plots of the results with fitted curves to simplify analysis. For all tested training data portions, training and validation accuracies values were lowest for the lowest initial learning rates, with recorded values less than 90%. Significant improvement in both accuracies was seen for initial learning rate values
2) Impact of minibatch size
To determine the impact of the minibatch size on the accuracy, the minibatch size was varied between 10 1 and 10 5 in Training Accuracy (%) Training data -60% Training data -70% Training data -80% (a) Training Validation Accuracy (%) Training data -60% Training data -70% Training data -80% (b) Validation FIGURE 14. Impact of varying minibatch size on accuracy at different training ratios 100 steps. We present training and validation accuracy versus minibatch size parameter plots in Figure 14. For all tested training data portions, the training and validation accuracies averages were a little bit higher than 90% for minibatch size values less than 10 3 . For minibatch sizes closer to 10 1 , the training accuracy varied significantly between 80% and 100% for each training task, however, this did not have an impact on validation as validation accuracy stayed the same just above 90%. Both training and validation accuracies declined drastically as minibatch size increased beyond 10 4 . This is because as the value of the minibatch size increased, the model had to learn from increased data size, resulting in poor generalization. However, smaller minibatch size values required relatively much time to train a model. A minibatch size less than but closer to 10 3 is recommended to balance efficiency and generalization. To determine the impact of the L2-regularization parameter on validation accuracy, the L2-regularization parameter was varied between 10 −8 and 10 −2 in 100 steps. Figure 15 shows the results. For all training data portions, training accuracy laid between 83% and 99%, with an average value at around 91% for l2-regularization parameter values in the range [10 −8 , 10 −4 ). Unstable average values of training accuracy were observed for l2-regularization parameter values ≥ 10 −4 . On the other hand, validation accuracy significantly decreased for l2-regularization parameter values ≥ 10 −4 . This may be caused by the fact that when the l2regularization parameter ≥ 10 −4 , at each training iteration, a significantly large number of weights was left not updated, thereby making it hard for the model to converge to a good solution. Best results were obtained when L2-regularization parameter values were in the range [10 −8 , 10 −4 ]. For all investigated parameters, the best validation accuracy was obtained for the 80% training data portion, followed by the 70% training data portion and lastly 60% training data portion. This shows that the more data is available for training the model, the more accurate the model becomes in detecting electricity theft.
F. COMPARISON WITH EXISTING DATA-BASED ELECTRICITY THEFT DETECTION METHODS
Based on electricity customers consumption data, different data-driven methods have been used to tackle the electricity theft problem. Due to the scarcity of datasets containing both faithful and unfaithful customers' consumption data, many methods have been evaluated on different uncommon datasets. In Table VI, we present an analysis in the difference between our work and the recent works in the literature. For each work, dataset details are given. We look at the techniques and/or algorithms used, as well as features extracted from the data in respective methods.
For the four methods which used the same dataset as ours (References [3], [4], [27]), we compare the results in terms of AUC and accuracy percentages. We obtained AUC that is 1% higher than the best AUC in the benchmark and accuracy that is the second best. The results show that our work is very competitive against other methods recently undertaken.
VI. CONCLUSION
In this work, the detection of electricity theft in smart grids was investigated using time-domain and frequency-domain features in a DNN-based classification approach. Isolated classification tasks based on the time-domain, frequencydomain and combined domains features were investigated on the same DNN network. Widely accepted performance metrics such as recall, precision, F1-score, accuracy, AUC-ROC and MCC were used to measure the performance of the model. We observed that classification done with frequencydomain features outperforms classification done with timedomain features, which in turn is outperformed by classification done with features from both domains.
The classifier was able to achieve 87.3% accuracy and 93% AUC-ROC when tested. We used PCA for feature reduction. With 7 out of 20 components used, the classifier was able to achieve 85.8% accuracy and 92% AUC-ROC when tested. We further analyzed individual features' contribution to the classification task and confirmed with the mRMR algorithm the importance of frequency-domain features over time-domain features towards a successful classification task. For better performance, a Bayesian optimizer was also used to optimize hyperparameters, which realized accuracy improvement close to 1%, on validation. Adam optimizer was incorporated and optimal values of key parameters were investigated.
In comparison with other data-driven methods evaluated on the same dataset, we obtained 97% AUC which is 1% higher than the best AUC in existing works, and 91.8% accuracy, which is the second-best on the benchmark. The method used here utilizes consumption data patterns. Apart from its application in power distribution networks, it can be used in anomaly detection applications in any field. Our work brings a small contribution towards accurately detecting energy theft as we detect theft that only took place over time.
We wish to extend our method to detect real-time electricity theft in the future. Since this method was evaluated based on consumption patterns of SGCC customers, it can further be validated against datasets from different areas to ensure its applicability anywhere. | 11,762.8 | 2022-01-01T00:00:00.000 | [
"Engineering",
"Computer Science",
"Environmental Science"
] |
Brewed Robusta Coffee Increases Nickel Ion Release from Dental Alloys: An In Vitro Study
Alloys in oral cavity always interact with dynamic oral environment, such as pH, temperature, salivary conditions, and dietary habits. Coffee can further decrease pH in the oral cavity. Thus, coffee may increase the release of metal ions that may lead to various health diseases. This study aimed to quantitively investigate the effect of brewed Robusta coffee on the nickel ion release and their morphological structures; Methods: 20 alloy specimens were divided into 4 groups and placed in solutions for 48 and 168 h: (1) distilled water, (2) artificial saliva, (3) Robusta coffee, and (4) mixture of artificial saliva and Robusta coffee. AAS, XRF, and SEM were used for examinations; Results: The release of Ni2+ was found in all groups and robust release were found in the coffee only and mixture of coffee + artificial saliva solution after 168 h. Likewise, SEM showed that internal oxidation was high after 168 h of immersion; Conclusions: The concentration of nickel increased in saliva of low pH due to brewed coffee. Though the release of these ions is still within the tolerable amount in human body, it should be realized that it usually lasts for months or years. Dentists should be cautious when using instructions for patients with a history of allergies especially for dietary with low acidity.
Introduction
Metals are still often used for various purposes in dentistry since up to now distinct metals are still irreplaceable by other materials. Moreover, mechanically, and physically, it has the greatest strength to withstand chewing loads. In dentistry, metal is never used in a singular form but always mixed with at least two different types of metals called alloys [1].
Nickel (Ni) is an important transition element essential for many dental alloys. Nickelbased (non-precious) alloys are used in various types of dental restoration (fillings, crowns, bridges, partial dentures) and orthodontic appliances (wires, dental bands, brackets, etc.) [1,2]. Today, nickel is still used in the dental field for a variety of reasons such as corrosion resistance and low costs [3]. Nickel is used in dental construction from a few percent to over 50 percent. However, nickel is the most common metal sensitizer in humans, which leads to the controversy of the long-term use of nickel casting alloys in dentistry [4]. In sensitized individuals, even low doses of nickel (about 6-200 µM) can cause skin inflammation [5]. Exposure to metal ions in the oral cavity can cause adverse reactions, such as inflammatory effects, allergic reactions, and mutagenic effects, depending on the concentration of metal ions released. Immunotoxicity of dental alloy is largely due to the release of Ni 2+ ions, which can cause several local symptoms such as oral lichen(oid) lessions/oral lichen planus (OLL/OLP) to autoimmune disease (AID) and neurotoxicity [6].
Nickel based alloys in the oral cavity are influenced by temperature, plaque, quality, and quantity of saliva. Likewise, food or drink that is consumed can cause alteration of pH of oral cavity, which can trigger the release of metal ions [1]. The normal pH range of saliva is 6.5-7.0. Of note, protein and chloride ions in saliva affect the release of metal ions. Protein acts as an electrolyte medium that can trigger chemical reactions; meanwhile, chloride has a metal destruction mechanism when they come into contact with the chromium oxide layer which is a protective layer from corrosion in NiCr alloy [7]. Coffee consumption is suggested as one of the activities that can increase the release of metal ions [8].
Coffee is one of the most consumed beverages in the world due to its pleasant taste and aroma [9]. Robusta coffee contains several components such as alkaloid, flavonoid, saponins, tannins, caffeine, and phenol. It has a low pH of around 5.0-5.5 [10] which may cause an increase in the release of metal ions [11]. It can also trigger reduction and oxidation reactions, which lead to increased release of metal ions [12]. The World Health Organization (WHO) guidelines for drinking water currently accept a nickel concentration of 70 µg/mL (10.85 ppm), and the normal range of metal ions in the body is 300-600 µg which is equal to 46.5-93 ppm [13]. Of note, the maximum limit of Ni 2+ ion in medical applications is <1.10 ppm. However, there are only very limited studies on the corrosion of orthodontic appliances and release of metal ions due to coffee consumption. Some in vivo studies have shown that the level of metal ions in the saliva of patients undergoing orthodontic treatment varies greatly. These changes can be attributed to differences in sample preparation techniques, dietary behavior and different analytical methods. Therefore, in this study, we aimed to analyze in vitro the amount of Ni 2+ ion released in the alloy after immersion in Robusta coffee brews to prevent variation. Knowledge on the number of ions released could assist the practitioner in advising an appropriate dietary instruction for the patient's benefit.
Alloy Specimen Preparation
NiCr dental alloys were selected (Dentecon Inc./Thermabond alloy super cast, MfG, Los Angeles, CA, USA) with the composition of 75% Ni, 15% Cr, 5% Molybdenum (Mo), and 1.6% Beryllium (Be). Each dental alloy was formed into 20 discs, each of which has a diameter of 10 mm and a thickness of 1 mm. All samples were polished with silicon carbide paper (400, 800, 1200 grit) with a grinder polishing machine (M2V; Manfredi). Next, according to [14], samples were cleaned in ethanol and deionized water with an ultrasonic cleaner for 5 min to remove contaminants, and finally autoclaved. Alloys were cast according to the manufacturer's instructions using the lost-wax technique. All processes of finishing and polishing were carried out in a similar way to simulate the preparation of the cast metal alloys for clinical cases [15,16].
Alloy Immersion in the Solution
Each alloy was placed into a 100 mL clean and dry beaker glass that has been filled with various solutions and incubated at 37 • C to simulate the oral temperature. Next, the pH of each solution was determined by using a pH meter (Hanna Instruments, Hungary). The solutions used included (1) distilled water, (2) artificial saliva, (3) Robusta coffee brews, and (4) mixture of artificial saliva + Robusta coffee. Robusta coffee brew was obtained by dissolving 3 mg of Javanese Robusta coffee powder (PTPN XII, Jember, Indonesia) in a total volume of 100 mL of water. The composition of non-protein added artificial saliva used in this study consisted of 36.0 gr of Sodium Chloride (NaCl); Potassium Chloride (KCl) 1.9 g; Calsium Chloride (CaCl 2 ) 0.956 g; Sodium bicarbonate (NaHCO 3 ) 0.85 g; and 400 mL distilled water. After the NiCr alloys were added to each solution, the beaker glasses were wrapped by using aluminum foil. All samples were stored in an incubator at 37 • C for 0, 2 (48 h), and 7 days (168 h). Once every 24 h, the solution containing Robusta coffee was stirred using a glass stirrer.
X-ray Fluorescence (XRF) Analysis
An X-ray Fluorescence (XRF) (Malvern Panalytical Ltd., Malvern WR14 1XZ, United Kingdom) was used to determine the composition of the sample before and after immersion. The following are the test steps using XRF: (1) Prepare a disk-shaped alloy sample that has been immersed, and (2) follow the Standard Operational Procedure (Crocker Nuclear) (Laboratory, 2015).
Atomic Absorption Spectrometry (AAS) Analysis
The total nickel concentration in the solution sample was analyzed by flame atomic absorption spectrometry Flame-AAS (Thermo Scientific iCE 3000 Series, Thermo Fisher Scientific, Cambridge, UK). First, we diluted the solution sample with ultrapure water to increase the volume of the solution. All analyses were based on three repeated readings of each solution sample, and quality control samples of known concentrations were also analyzed. All results given were based on the mean and standard deviations of at least triplicate samples for each alloy specimens, solution, and time period, and subtracted to the respective blank sample concentration. The detection limit of each element was calculated 0.10 as 3 times the SD of the blank (3 s blank, n = 5 specimens); following the Graphite Furnace (GF) -AAS method, the detection limit for Ni 0.05 was calculated as 0.003 parts per billion (ppb).
Scanning Electron Microscopy (SEM) Analysis
Next, the surface morphology of NiCr alloy before and after immersion was measured using SEM analysis (Hitachi TM3000, Hitachi, Tokyo, Japan). The measurement were in the form of the percentage of ions and oxides. In addition, the surface morphology of the NiCr alloy was observed at a magnification of 2500×.
Data Analysis
The statistical significance of the effects of Robusta coffee brews on the Ni 2+ ion release was analyzed by using two-way ANOVA and Dunnett test (parametric ANOVA), with statistic program GraphPad Prism Software version 9.0 (San Diego, CA, USA). p ≤ 0.05 was considered statistically significant. All data are presented as mean ± SD.
The Composition of Nickel Chromium Alloys
First, to quantitatively explore the effect of Robusta coffee brews on the Ni 2+ ion release and their morphological structures, XRF was conducted to calculate the original composition of metal ion in gram per amount (wt%). The results of the purity of NiCr alloy (pre-test) can be seen in Table 1. The highest percentage of ions is Ni 75%, followed by chromium 15%. Whilst the percentage of Ni 2+ ion after immersion can be seen in Table 2 which shows that several treatments resulted in a lower percentage of Ni than the pretested alloys. These results confirm that the alloy used is a NiCr alloy, of which nickel is the main composition. The data in Table 2 indicate that there are differences in the composition of the alloy specimens before and after immersion. It also shows that the more Ni 2+ ions are released, the composition in the NiCr alloy also decreases.
pH Meter Result
The solutions-pH results are shown in Table 3. Test results are included (1) distilled water pH of 7.2, (2) artificial saliva pH of 6.5, (3) Robusta coffee brews pH of 5.0, and (4) mixture of artificial saliva + Robusta coffee pH of 5.5. Knowledge of the results obtained in this section is useful in supporting the hypothesis that the release of Ni 2+ ions is thought to be caused by the low acidity of the coffee. Table 3. Average pH solutions in four groups (n = 5 in each group), according to pH meter measurements. Results represent mean ± SD.
Nickel Ion Released according to Atomic Absorption Spectrophotometry (AAS)
Subsequently, Nickel ion released according to Atomic Absorption Spectrometry (AAS) is summarized in Figure 1, Table 4 Amongst 48 h immersion of NiCr + (artificial saliva + Robusta coffee) showed the highest concentration of Ni 4.26 ppb. It gradually increased and was statistically significant in all groups of 168 h of immersion. A bar chart of Ni 2+ ion release can be seen in Figure 1 and in numerical Table 4. (Table 4), the data represent mean ± SD from five specimens (n = 5). Asterisks specify statistically significant (Two-way ANOVA and Dunnett test (parametric ANOVA)) differences in Ni 2+ ion release from each solution as compared to the control NiCr + distilled water, ** p < 0.01, **** p < 0.001.
The Surface Morphology of Nickel Chromium Alloys
The next phase carried out was Scanning Electron Microscopy (SEM). This process resulted in the before and after immersion surface morphology of NiCr alloys which can be seen in Figure 2 below. The arrows show the parts of the alloy which have undergone internal oxidation, thus forming a pore. The results indicate that the positive control group immersed in artificial saliva (2C) with 4.24 ppb and Robusta coffee brew after 168 h (2D) showed the release of 5.67 ppb Ni 2+ ions which can cause significant changes in the surface morphology of the alloy. SEM results of NiCr alloys that have been immersed in various immersion solutions showed different surface roughness, pore sizes, and pore numbers. In Figure 2E, the alloy surface morphology which has been immersed in the treatment solution (artificial saliva + coffee) appears coarser with higher number of pores than the others. In Figure 2A the pretest The results indicate that the positive control group immersed in artificial saliva (2C) with 4.24 ppb and Robusta coffee brew after 168 h (2D) showed the release of 5.67 ppb Ni 2+ ions which can cause significant changes in the surface morphology of the alloy. SEM results of NiCr alloys that have been immersed in various immersion solutions showed different surface roughness, pore sizes, and pore numbers. In Figure 2E, the alloy surface morphology which has been immersed in the treatment solution (artificial saliva + coffee) appears coarser with higher number of pores than the others. In Figure 2A the pretest alloys and (B) the alloys that have been soaked in distilled water show smoother alloy surface morphology, and there are no oxidized surfaces. The level of surface roughness is directly proportional to the results of the AAS, except in the distilled water group. A higher ion release concentration indicates a higher degree of surface roughness.
The SEM results conclude that the treatment group (saliva + coffee) has the highest roughness level; the positive control group (NiCr + Artificial Saliva; NiCr + Coffee) generates a moderate roughness level; the negative control group (NiCr + distilled water) and the pretest have the lowest roughness level.
Discussion
The release of nickel ions in oral cavity is caused by the electrolyte content in artificial saliva. One of the electrolytes that play a role in releasing ions is chloride ion. Chloride can damage the oxide layer on the alloy surface, causing the release of ions [17]. Artificial saliva contains organic components in the form of proteins which can act as an electrolyte medium, thus triggering chemical reactions. In addition, nickel ions are more likely to detach due to the structure of their atomic elements. Therefore, the release of nickel ions in artificial saliva immersion is quite high [18]. Figure 1 shows the increasing release of Ni 2+ ions in the immersion solution of pure Robusta coffee. Correspondingly, as seen from the low pH of Robusta coffee compared to other soaking solutions (Table 3), the results of nickel ions release are in line with [19] who state that in acidic environments the number of H + ions will increase causing them to become corrosive, thus the ions are easily released. Next, when compared to the results of combining artificial saliva + Robusta coffee on 48 and 168 h, the amount of nickel ion released is even higher. In fact, the pH in pure Robusta coffee immersion is the lowest among other solutions (pH 5), while the pH of the Robusta + saliva coffee mixture is 5.5. Presumably, this may result from the corrosion rate inhibitory properties in the alloy of one of the ingredients of pure Robusta coffee, namely concentrated caffeine. Caffeine (C 8 H 10 N 4 O 2 ) is a compound containing an N group which has free electrons. The N group will donate its free electrons to the alloy, thus inhibiting the corrosion rate in the immersion of pure coffee [20]. According to [21], the high concentration of caffeine in a solution will reduce the corrosion rate of an alloy. This is in accordance with the results of their study which evinces that applying a concentration of 2% caffeine results in a greater reduction in corrosion rates compared to the application of 1% caffeine over time.
In addition, the antioxidant content in Robusta coffee can also affect the release of ions. Antioxidants are compounds that have an inhibition mechanism toward oxidation reactions, by binding to free ions and highly reactive molecules. The antioxidants in Robusta coffee beans include the tannins, flavonoids, and polyphenols. Tannins and flavonoids have properties as chelating agents, which means they can bind metal ions [19,21]. Therefore, the results of this study indicate that the release of ions in pure Robusta coffee is not higher, despite acidic pH, compared to the mixture of coffee and artificial saliva, which reflects the state of brewing coffee when consumed and mixed with saliva in the oral cavity. The high release of nickel ions is caused by the interaction between artificial saliva and Robusta coffee, which results in a decrease in buffer function. The decrease in buffer function distracts saliva from maintaining its pH balance, therefore it cannot bind H + . In addition, the carbohydrate content in coffee can be fermented by acid producing bacteria; thus, reducing pH in saliva [22]. Therefore, the release of nickel ions in the mixture of Robusta coffee + artificial saliva group is the highest.
The release of metal ions is not only influenced by pH, but is also influenced by the type of alloy, manufacturing process, surface area, immersion time, and the composition of the drink/food consumed [8,23]. Although there is no literature investigating the release of Ni 2+ ions in vitro due to coffee immersion as a comparison, several research results show that soaking orthodontic braces with several types of carbonated drinks and orange juice shows an increase in the release of Ni 2+ ions [24]. In line with this study, Ref. [8] show that consumption of food containing low pH (such as fruit juices, coffee, yogurt, and vinegar) can change the acidity of oral cavity therefore it can also increase the release of Ni 2+ ions from the use of orthodontic devices used. There are also in vivo references to patients who state that the increase in Ni 2+ ions release in coffee-consuming patients is approximately 1.22× higher than in those who do not consume coffee [8].
The interaction between saliva + Robusta coffee causes an increase in the release of Ni 2+ ions and this sample even shows the highest release. The high Ni 2+ ion release stems from the influence of saliva content. Saliva consists of various electrolytes, such as sodium, potassium, calcium, magnesium, bicarbonate, and phosphate. In addition, saliva also contains immunoglobulins, enzymes, mucin, other proteins, and several products such as urea and ammonia [10]. In this study, the artificial saliva contained components of potassium, calcium, bicarbonate, and chloride. These are electrolytes that can trigger electrochemical reactions. An electrochemical reaction is the reaction between anode and cathode. Anode is associated with an oxidation reaction (releasing electrons), and cathode is associated with a reduction reaction (accepting electrons). In this case, metal ions serve as the anode, and H + ions from the electrolyte medium serve as the cathode. As a corollary, an electrochemical reaction occurs, which causes the release of ions in the alloy [25]. Therefore, the release of nickel ions in the immersion test involving artificial saliva + coffee was found the highest.
The XRF test results in Table 2 shows that there is a correspondence between the AAS and XRF test results. This is in line with the theory which states that the group found to have the highest amount of nickel ion release tends to have the lowest nickel composition. This was shown by the XRF test data in this study, showing that the percentage of nickel in the alloy after immersion was lower than that in the pre-test alloy with a nickel percentage of 75%. Meanwhile the alloy immersed for 168 h immersion in a mixture of saliva + Robusta coffee had a nickel percentage of 67.39%. In addition, the XRF test results confirmed that there were differences in the composition of the alloys before and after immersion.
SEM was conducted to determine the surface roughness and porosity of the NiCr alloy. Surface roughness is the irregularity of a surface in the form of curves or scratches [20]. Based on Figure 2 shows that different alloys display different surface roughness, number of pores, and pore sizes. To date, there is no literature on the amount of minimal Ni 2+ ion levels that can cause changes in the surface morphology of an alloy. The results of this study, the Ni 2+ ion content of 1.4 ppb in the NiCr alloy immersed in distilled water underwent changes in surface morphology.
The SEM assays were observed in the 168 h immersion. The findings demonstrated that longer immersion time leads to more Ni 2+ ions released. Therefore, the alloy surface morphological structure showed the difference between pre-test samples and those in several types of immersion: distilled water, artificial saliva, coffee, and mixtures (artificial saliva + Robusta coffee). SEM test results showed that the pre-test and NiCr alloys immersed in distilled water had the lowest surface roughness level. Meanwhile, NiCr immersed in artificial saliva had medium surface roughness, the alloy surface roughness increases, such as what was found in NiCr immersed in coffee. In addition, the mixture of Robusta coffee and artificial saliva resulted in the highest surface roughness. SEM test results were directly proportional to AAS test results. The high release of nickel ions will indicate a higher level of surface roughness and a higher number of pores. In all types of immersion, black nodules were found on the surface of the NiCr alloy caused by internal oxidation of less noble alloy elements, such as copper and zinc [25]. Black nodules were also more clearly seen in NiCr + artificial saliva, NiCr + coffee and NiCr + (Saliva + Robusta coffee). This was due to the pH of the solution with potent acidity, causing more alloy parts to be oxidized.
The release of nickel ions in all groups after 168 h immersion was higher than 48 h. According to ASTM International (2019), the standard immersion time is often used is from 48 to 168 h. Immersion time which is less than 48 h will result in a high rate of ion release. Subsequently, the ion release rate will drop/stabilize after 168 h. Furthermore, according to [26], long immersion times can lead to increased ion release associated with the metal's susceptibility to corrosion. Of note, although the release of metal ions may be negligible, it should be realized that it usually lasts for months or years. Likewise, our previous results showed that the optimal effective innate stimulatory dosages range from 125-750 µM for Ni 2+ . As a result, the levels of metal ion released in the oral cavity and thereafter absorbed in the gastrointestinal system are extremely negligible [25,26]. Nonetheless, several secondary factors may promote the development of local and systemic complaints [1].
A more detailed examination of the influence of coffee consumption on the release of metal ions from dental appliances will be useful to allow nutritional recommendations for patients. These recommendations will reduce patient exposure to nickel released from dental appliances.
Conclusions
Coffee consumption can increase the release of Ni 2+ ions from metal constructions in the oral cavity. Immersion of NiCr + (artificial saliva + Robusta coffee) showed the highest concentration of Ni 2+ with 4.26 ppb (in 48 h) and 6.77 ppb (in 168 h). Even though the release of these ions is still within the tolerable amount in the human body, dentists should be cautious when giving instructions to patients with a history of allergies. Therefore, it may be useful to recommend dental patients to limit the consumption of food and beverages characterized by low pH to reduce the number of ions dissolved from the dental alloys.
Author Contributions: D.R., contributed to the concept, design, data acquisition, analysis, and interpretation, the initial draft and critical revision of the manuscript; D.A.C., contributed to the concept, design, data acquisition, and interpretation; A.T.F. contributed to design, data acquisition, and analysis, and to critically revised the manuscript; L.H., contributed to the interpretation and critically revised the manuscript; C.J.K. contributed to valuable discussion and critical revision of the manuscript. All authors provided their final approval and agreed to be accountable for all aspects of the work. All authors have read and agreed to the published version of the manuscript.
Conflicts of Interest:
The authors declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.
AAS
Atomic Absorption Spectrometry ACD allergic contact dermatitis AID autoimmune disease NiCr nickel chromium OLL/OLP oral lichen(oid) lesions/oral lichen planus ppb parts per billion SEM Scanning Electron Microscopy XRF X-ray Fluorescence | 5,635 | 2021-11-01T00:00:00.000 | [
"Medicine",
"Materials Science"
] |
The gravitational dynamics of warped throats
We investigate the time evolution due to gravitational dynamics of a particular spacetime commonly used in brane-cosmology and string compactifications, namely the Klebanov-Strassler geometry, which is achieved by adding a perturbation to the momentum of the static solution. We observe the effects this has on the spacetime and look for evidence of black hole formation or collapsing cycles which could lead to singular geometry. The cycles are seen to commonly re-expand after reaching a minimum value, showing the stability of the solution against perturbations which would change its size. However black holes are observed to form for certain perturbations, which could impede common uses of the throat's stable tip.
Introduction
Producing realistic models of our own universe using the knowledge we have of string theory is a task plagued with difficulties, such as the selection of a vacuum out of many choices, and the existence of moduli. String theory requires that extra dimensions are present, but observations restrict them to be unobserved. Such extra dimensions may be in the form of a compact manifold, the choice of which is a choice of vacuum with the moduli being continuous parameters characterizing the manifold. These moduli take the form of massless scalar fields within the low energy effective theory, which are strongly constrained [1,2]. With appropriate addition of fluxes and the inclusion of quantum mechanical effects these moduli fields can take on an expectation value and at the same time can acquire a mass, this is desirable as a large mass would explain why these fields have not been detected. In addition to the values taken by the moduli is the more fundamental question of the topology of the compact manifold, however the seemingly insurmountable challenge of selecting one topology was improved by the possibility that vacua with different topology are connected by paths in the moduli space, ones going through singular geometry manifolds [3,4,5,6,7]. Such a change to the topology could be a very drastic process, altering intersection numbers or even the Hodge numbers of the compact topology. These transitions can be made regular, and their low energy dynamics studied within the realm of string theory [8,9,10,11]. The range of possible vacuum topology and moduli is collectively called the string landscape [12] and our own position within this huge range of vacua will determine many of the phenomenological predictions of the construction. With the introduction of an expectation value to the moduli fields some points within the string landscape become preferable and the universe will flow to these points, maybe even changing topology to get there if need be. With this additional knowledge about the Calabi Yau manifold being compactified on, string theory can make phemomonological predictions which may test it.
Warped throats are a possible feature within flux compactifications, they look like an extended protrusion of the manifold, whose base does not grow in size very quickly as we move away from the tip. Previously extra dimensions have been compactified upon manifolds with such a region in efforts to produce inflationary models (warm inflation, brane inflation, DBI inflation, spinflation) ; recreating the standard model using anti-D3 branes [13] ; creating a hierarchy between the UV compactification scale and the IR at the tip of the throat [14] or other interesting phenomenological effects. These generally involve using this manifold as the background upon which some probe brane is moved, where it is assumed that the probe does not influence the background manifold. Warped throats are often chosen as a background manifold also because they possess only a few moduli with flat directions. Most parameters which define the size, shape and other properties of the throat, such as the dilaton and the complex structure moduli, may be stabilized by the choice of flux, making the moduli at the supersymmetric vacua (potential minima) precisely determined. The stabilized moduli are less susceptible to backreaction from the branes and other probes added to create the wanted interesting effects like inflation.
A good example of such a throat is the deformed conifold which can be combined with fluxes to give a Klebanov-Strassler throat [15], this solution is the one commonly used in investigations involving warped throats; it is this solution which we too will use as a starting condition as we proceed to model the evolution of warped throats in time. We intend to use type IIB supergravity to perform a numerical simulation of the gravitational effects of perturbing the throat in the region around its tip. Unlike some previous studies, generally performed within the 4D-effective low energy theory of the moduli space, we do not trust the moduli approximations alone due to the immense freedom of the flux-containing, gravitationally-backreacting spacetime of IIB supergravity. We hope that our more elaborate numerical simulations (ones able to detect black hole formation and effects undetectable in the moduli approximation) will shed more insight on the possible limitations of these previous attempts.
Lagrangian and equations of motion
Our study takes place within the framework of type IIB supergravity, whose action is given in the Einstein frame as follows [16,17], The fields comprise a scalar dilaton φ, an R-R scalar with field strength F 1 = dC 0 , an R-R two form with field strength F 3 , an NS-NS three form field strength H = dB and a self dual five form field strength We have made gauge choices as we write these potentials, even though the four potential, C 4 , appears in the Chern-Simmons term of the Lagrangian it still has a great deal of gauge freedom. We need to separately impose the self duality condition upon F 5 by hand, as it is unconstrained by the Lagrangian The Lagrangian gives the following equations of motion for these fields: The fluxes also contribute to the energy momentum tensor, which means that our spacetime will not be Ricci flat but will obey the Einstein equation, In the above we have been using a mostly plus metric signature and an antisymmetric tensor obeying ǫ 0 1 2 3... = +1, (2.9) with the ten dimensional Hodge dual being given by * e abc.. = 1 n! ǫ abc..
Klebanov-Strassler static solution
A static warped throat solution found by Klebanov and Strassler [15] will be used as our starting condition to which we will add a small perturbation in the form of a momentum. This in turn was based on the deformed conifold [18], which is a Calabi-Yau space with one extended radial dimension, labelled by r, and a compact five dimensional base. At high r, far from the origin, the deformed conifold tends to look like the standard conifold (where the five dimensional base is a Sasaki Einstein metric with the topology S 2 xS 3 ). However at lower radius the deformed conifold has a base dependent on r, and so loses scale invariance in r, the new scale being introduced by the new parameter ǫ. We can write this line element in terms of a basis of one forms, g i defined and described in detail in [15]. Using this basis of one forms to describe the five dimensional base of ds 6 , we can write the deformed conifold as Where we have used .
Note that K(r) does not vanish at the origin but tends to the constant value (2/3) 1/3 , implying that the deformed conifold does not tend to a singular point at r = 0, but at the tip there is a three sphere in the direction g 3 ∧g 4 ∧g 5 . This six dimensional manifold will make up six of the ten dimensions in the solution to the Einstein equations. In the case with no flux contributions we can product the deformed conifold with a 3+1 Minkowski metric ds 1,3 . ds 2 10 = ds 1,3 + ds 2 6 . (3.3)
D-brane sourced fluxes
If we introduce N D3branes and further supplement this with M D5branes wraped arround the two sphere of a deformed conifold (these have previously been coined "fractional D3branes") then it corresponds to taking a Calabi Yau manifold with deformed conifold singularity and introducing a large flux through the three sphere [19,20]. The effect of combining ds 6 with (fractional) Dbranes is to source fluxes and so contribute to the Energy-Momentum tensor of the Einstein equation. This means that the spacetime metric can no longer be Ricci flat and it changes the static solution to the solution of [15]. The new fluxes require a change to the metric (3.3), making the minkowski slices depend upon the radius of the deformed conifold component and so we get conformal symmetry breaking (for non-zero M). This r dependence is introduced by means of a function, h(r).
The static solution is described in detail in [15], we intend to use this metric and these fluxes as initial conditions which we will then go on to perturb. The fluxes, three-forms and the five-forms of the static case are described in terms of the metric coordinates.
The scalar dilaton and R-R scalar go as, In addition to the usual potential, the M fractional branes we have placed at the tip of the deformed conifold, consistently give flux through the g 5 ∧ g 3 ∧ g 4 direction at the origin, this is the 3 sphere, H can be described by the potential B, The final flux is the five form, self dual F 5 . Its self duality condition along with the equation of motion and our choices of F 3 and H lead to the solution that, The nature of h(r) in the static case (this is the value for h(r) which we impose as an initial condition) is given by a differential equation.
The introduction of this h(r) changes the scales and removes the conformal invariance.
To totally define h(r) we also need a boundary condition (to complement the 1st order differential equation), Klebanov and Strassler impose the restriction that h must vanish at high r. lim Meaning that the radius of the throat tends to grow only very slowly for large r.
Superpotential and stabilized moduli
The potential created by the introduction of the flux can be found from the Hamiltonian constraint, as described in [21] and used in [22]. This potential is then used to find a prediction to the evolution of the moduli field. Taking a slice through this moduli space along which only the volume of the three-sphere is permitted to change, we find the potential as a function of this volume. This method results in a potential of the form plotted in figure.1. This diverges very quickly as the volume gets small, it permits a minima at a position determined by the other moduli and parameters (such as M), and tends to grow (albeit quite slowly) as the volume gets very large. The minima represents the static warped deformed throat solution. The scale of the compactified dimensions is now set by the fluxes, the size of the three sphere at the origin is stabilized according to the minima of the potential and is no longer a free modulus, in the static case it must conform to
Time dependent spacetime anzatz
If we start with the static solution then no change will happen as we move forward time, however with only a small initial perturbation the metric and the fluxes are observed to evolve. It is our intention to introduce an initial perturbation that changes the size Figure 1: The potential as a function of the volume of the three sphere in planck units of the three sphere at the origin of the deformed conifold, possible outcomes include the formation of a black hole solution; the collapse of the three sphere to a naked singularity; or the sphere may change size without collapsing all the way to zero. To observe the effects of an initial deformation we use a more general metric and flux ansatz, a system with the capacity to be time dependent, and then observe the effects we can incite with a small initial perturbation. We choose a metric that is capable of changing in time and is also stable to evolve numerically at the origin [23,24].
The profiles T (t, r),a(t, r),b(t, r),c(t, r) and d(t, r) define the metric at all times. We also had to impose boundary conditions at the origin of the simulation. These conditions were to ensure that local flatness remained at later times [25].
We also required that all these profile functions were always even at the origin. At later times the size of the three sphere can be found from d 2 (t, r)| r=0 and c 2 (t, r)| r=0 . Of course we must also allow the fluxes to change with time (as they almost certainly will when the metric is perturbed). Initially the axion is constant and the equations of motion show this can continue to be the case at later times, also the dilaton is initially constant at all points however this is permitted to change at later times according to the equations of motion, The M fractional branes that we have placed at the origin will not change but will always give flux through the three-sphere, however the potential C 2 can change, The other three-form flux, H, is described by two separate functions B α (t, r) and B β (t, r), these are used as a description of B, and B defines H.
Even at later times the five-form flux is still determined by the other fluxes according to (3.9). All the fluxes are defined by the metric and four profile functions, φ(t, r), C α (t, r), B α (t, r) and B β (t, r). It is these functions that we will evolve using the equations of motion. In addition to the equations of motion, we also imposed boundary conditions on these functions, we required that B α (t, r) and B β (t, r) be odd, φ(t, r) be even and C α (t, r) be even and must vanish at the origin. This is the choice of fluxes that are capable of acting as the initial conditions and evolving consistently to later times.
Initial conditions
By comparing the static Warped deformed conifold metric (3.4), and our time dependent ansatz (4.1), we can read off the initial metric conditions a term at a time.
Flux is added when we give M a non-zero value (we introduce fractional branes), its strength depends upon our string coupling g string and the number of branes M. The initial values of the fluxes can be found from (3.6), (3.7) and (3.8). They are defined by the functions e φ(0,r) = g string , (4.9) This also requires that h(r) to take on the value which obeys the differential equation (3.10) and also tends to zero asymptotically. We found h(r) numerically as we input the initial conditions. These initial conditions give the static solution, so if all the momenta (e.g.Ṫ ) are zero to begin with then no evolution should occur. If instead we start with non zero momenta we perturb the metric away from the static case and can go on to see the future evolution. In order to best represent a physical system make our perturbation vanish as we go away to large distances, representing a localized perturbation. Our initial momentum must also conform to the constraints upon the Hamiltonian and the momentum imposed by the Einstein equations.
Results
We kept the values of the string coupling and the number of fractional branes consistent throughout all plotted simulations, Mg string = 120 and M = 30, we also specified the warping α so that the static solution was at ǫ = 1. If we add momentum going like Then a positive value of P will cause the size of the three sphere at the origin to initially fall but this may only be temporary, whereas a negative P will cause the three sphere to grow (the symmetry between c and d maintained the local flatness (4.2)). As we impose the initial conditions we must obey the Hamiltonian and momentum constraints, this requirement was used to numerically find the initial values ofȧ andḃ. The choice (5.2) was made to aid this numerical integration. In order to best summarise the results of our perturbed evolution we shall constantly be watching the size of the three sphere at the origin. If this shrinks it shows that the origin is becoming closer to that of a conifold, approaching the formation of a conical singularity, with the three-sphere vanishing being the most extreme case. Alternatively we may find other outcomes, such as the formation of black holes.
Formation of black holes and apparent horizons
We will attempt to discover if and when black holes have formed by constantly looking for apparent horizons on the timeslice. The existence of an apparent horizon will show that there exists an event horizon outside it or coinciding with it [26]. The event horizon is a sure sign of a black hole spacetime. The apparent horizon can be detected upon any single timeslice [27], upon a timeslice with unit normal n i and where K ij is the extrinsic curvature of the slice, the apparent horizon is at the outermost shell of points satisfying 0 = ∇ i n i + K ij n i n j − K.
(5.4)
Where K is the trace of K ij . Such a shell will show that the origin is now encased within a black hole event horizon. If the area of the apparent horizon converges upon a constant value then we can take this value to be a good estimate to the area of the resultant event horizon [26].
Bounce
In order to prompt the size of the three sphere to drop we introduce a momentum of the form (5.1)-(5.3) where P > 0, this drop in the size of the sphere is, however, only temporary. As is seen in Fig. 2, after quickly reaching some minimum value (which depends on the strength of the momentum) the size of the three sphere then proceeds to grow, tending back to a value close to its starting value. This is an expected behaviour since the size of the three sphere is no longer a free modulus, it is determined, in the static case, by the fluxes. Since the string coupling and the number of branes is The size of the three sphere begins to fall but reaches a minima then returns to its starting value unchanged by the momentum, the ground state of the three sphere is the static value, the three sphere will tend to return to this value. In these cases no horizon is formed and the size of the three sphere tends to flow to the flux-preferred value. This can be seen to be true and quickly realized even for initial momenta hundreds of times the warped deformed scale, showing the restoring force to be very strong indeed. This is expected behaviour due to the swift divergence of the potential at low radius, as shown Fig. 1.
How low can it go?
Though the size of the three sphere can be seen to return to its initial value, it first drops to a minimum value dependent upon the initial momentum. If we continue to increase the scale of initial momentum we can ask how low we can force the three sphere to drop, could it be that there is some (very high) momentum which causes the sphere to drop to zero before it stops falling? We can find the lowest value which the three Figure 3: The smallest size the three sphere reaches for a range of momenta sphere falls to for a range of initial momentum. As shown in Fig. 3 the size does drop with the initial momentum but it drops at a decreasing rate and it would take a huge momenta to even approach zero (it actually looks as though the asymptotic behaviour may not be to zero but to a constant, lowest possible, sphere size). If we fit this to an exponential function of the form, (also plotted in Fig. 3) then we can see that causing the sphere to vanish (if it is possible) would require incredible initial momentum way beyond the capabilities of our simulation.
Growth
We also consider cases of (5.1)-(5.3) where P < 0, these will tend to cause the size of the sphere at the origin to grow. Again we would expect (from our potential) this growth to be only temporary and that the size would fall back towards the starting value, as the static case is still determined by the fluxes and it is this value we would expect the size of the tip to flow to. We do see this slowing of the growth in Fig. 4, but slowing down takes so long that the restoration of the size is not seen within the timescaleof the simulation, this can be attributed to a shallow restoring potential. We The size of the three sphere begins to grow but at a decelerating rate believe that the three sphere would eventually return to the starting value (the static case) but this takes a very long time.
Black hole formation
Relaxing the condition (5.3) was also attempted. This made the situation far more susceptible to the formation of black hole horizons, detectable by shells obeying (5.4). The presence of an apparent horizon often occurs already in the initial conditions, but the late time creation and growth of an apparent horizon is also possible, as shown in the example of Fig. 5. These horizons would be intolerable if we wished to achieve results such as inflation, topology change or moduli stabilization, any interesting effects would be enclosed behind the horizon. Even very weak initial conditions (|P | = 1) already contain apparent horizons before the simulations starts, and weaker conditions still form them within a small time. This shows that adding even a small initial momentum to appropriate metric functions (g rr and g 11 , g 22 in this case) introduces a risk of creating black holes. A momentum which would solely change the size of the three sphere is disallowed by the Hamiltonial and momentum constraints, other changes to the inital conditions must be applied and the nature of these will determine the creation of a black hole.
Conclusions
We have used the static warped deformed conifold as an initial condition to which we have added a momentum tending to alter the size of the three sphere at the origin. The size of the three sphere seems very stable against momenta which would provoke it to shrink, this is explained by the stabilization of the sphere by the flux. The flux fixes the size of the three sphere and induces a potential that resists any change to the size. We have seen in the simulations that, due to the very steep potential in the direction of reducing the three-sphere, the sphere soon recovers its original size and, presumably, returns to the original geometry. The geometry was also seen to be remarkably robust to high-momentum perturbations in the direction of making the sphere smaller, with simulations even suggesting a minimum size of the three-sphere.
On the other hand, if we insert momentum which tends to increase the size of the three sphere then the growth slows down on a much longer timescale, as one would expect on physical grounds by diluting flux-lines rather than squeezing them. This leads to a shallow potential in this direction, and a geometry that is more susceptible to growth than collapse of the three sphere. We believe the growth would eventually stop and the size of the three sphere would tend back to its starting value, however this is not seen in simulation due to the much larger timescales involved.
The theme seems to be that the size of the three sphere cannot be collapsed to zero by adding initial momentum, the three sphere will reduce in size temporarily but will return to a value close to its starting size and will not vanish. This seems to rule out the possibility of forming a conical singularity when there are fluxes to consider. It does verify the stable radius of the three sphere in the Klebanov-Strassler static solution, as expected, and it also makes manifest the difficulty of dynamical topology changing transitions being realized in string theory when fluxes are present. We should, of course, make clear that there is a huge degree of freedom in choosing the initial data, despite the resrictions of the Hamiltonian and momentum constraint, and such conclusions are based on the initial data we chose.
While the size of the three-sphere may be stabilized by the fluxes, they do not guarantee anything about the risk of black hole formation. As we have demonstrated in our simulations, black holes can be formed from the throat with only a very small perturbation if it is in the "wrong" direction. This is a big risk (though not a certainty) in any procedure that involves dynamics on a deformed conifold, and such perturbations must be ruled out or otherwise addressed while making any models using probes on throats. The assumption that the manifold is unaffected by small probes may turn out to be too rash. | 5,916.4 | 2009-09-09T00:00:00.000 | [
"Physics"
] |
Heavy-quark-mass expansion of vector and tensor currents and intrinsic charm in nucleon form factors
We compute asymptotic expansions for the vector and the tensor current in the limit of large quark masses in perturbative QCD using the framework of the expansion by subgraphs. We apply the results to estimate the influence of heavy quarks on the nucleon’s electromagnetic and tensor form factors.
Introduction
The intrinsic heavy-quark content of light hadrons is a fundamental property of QCD [1][2][3]. As such, it is expected to have significant influence on the nucleon structure or, more explicitly, on those observables that are related to it. Among the most important of these observables are nucleon form factors; their investigation provides a possibility to JHEP01(2016)092 quantify the impact of heavy quarks on the nucleon structure. Form factors parametrize the expectation values of bilinear fermion operators in a single-nucleon state. Thus, the influence of intrinsic heavy quarks on the nucleon structure can be seen in those bilinear fermion operators that contain heavy quark fields. It is natural to employ a large mass expansion to study such operators. One tool to perform large-mass-expansions which is particularly suited to generate operator-product-expansions (OPE's) is the heavy-quarkmass expansion (HQME), which was used in [4] and [5] to expand the vector and the tensor current of heavy quarks in gluon field operators. It was observed in [6] that the HQME-approach is not complete. The problem arises in the estimation of the influence of muons on the electron's anomalous magnetic moment µ e in QED. If the muon mass is treated as large parameter (compared to the electron mass) the HQME can be used to compute the muonic contribution to µ e by expanding the muon's vector current in photon field operators. The first contribution to the expansion is of order 1/m 4 µ [7]. But this result is in contradiction to the outcome of a direct analysis by Feynman diagrams [8], which shows that the contributions of muons to µ e start at order 1/m 2 µ . Due to the similarity of the calculations, the same problems can be expected for the HQME of the vector current of heavy quarks in QCD. In [6] the contradiction is resolved by the suggestion that the 1/m 4 µ -suppressed photon operator has to be renormalized by 1/m 2 µ -suppressed electron operators. Our goal is to generalize this idea to devise a systematic procedure for finding those additional operators that complete the operator product expansions of the HQME.
To formulate a systematic procedure of generating asymptotic expansions of QCDoperators, we use the language of Feynman diagrams instead of that of path integrals, which was used to derive the HQME results in [4].
In this language, rigorous results for the influence of virtual heavy particles are known for a long time. The most prominent is the decoupling theorem [9]: one can find renormalization schemes, in which, to leading order in the mass of the heavy particles, the effects of the heavy degrees of freedom can be neglected altogether. This result was generalized to a systematic expansion that allows to take into account the effects of heavy particles both on the diagrammatic level and on the level of the Green's functions (see for example ref. [10], ref. [11]). The first treatments used momentum subtraction schemes, which allow for a derivation of asymptotic expansions using standard renormalization-techniques. As dimensional regularization became the preferred method for regularization because of its technical simplicity and its preservation of gauge invariance, it was desirable to derive similar results within the minimal subtraction scheme (MS-scheme). In the MS-scheme decoupling is not straightforward: not all effects of heavy particles are suppressed by powers of their masses. Instead, one has to absorb effects of heavy particles in the physical coupling constants of the theory [12]. Nevertheless, a systematic procedure for the asymptotic expansions within the MS-scheme was formulated (see for example [13]). Finally, the technique of expansion by subgraphs [14] as a particular transparent way to find asymptotic expansions of Feynman diagrams was developed. Although this technique works on the diagrammatic level in the first place, the counterterm technique can be used to generalize the expansion to the level of operators as explained in ref. [13].
JHEP01(2016)092
In this work we compute large-mass expansions for the particularly important examples of the vector current and the tensor current using the expansion-by-subgraphs technique and use our results to analyze the validity of the HQME-approach. Section 2 explains the basic idea of asymptotic expansions. In the following sections the expansion is carried out for the vector and the tensor current: in section 3 the relevant Feynman diagrams for the expansion are listed; section 4 outlines the actual computations. Finally, we use the expansion of the vector current to estimate the influence of charm quarks on the electromagnetic and tensor form factors of the nucleon. The results of the operator-productexpansions are summarized in section 5. Applications for the intrinsic charm in nucleon form factors are discussed in sections 6.1 and 6.2.
Asymptotic expansions in heavy quark masses
The theoretical foundations of perturbative asymptotic expansions in renormalizable quantum field theories are discussed in a form that is particularly suitable for our work in refs. [15] and [13]. We shall summarize their results to highlight the main ideas that underlie asymptotic expansions of composite operators in the special case of large-mass expansions.
Consider a renormalizable quantum field theory with one type of particle with large mass M , and several light particles of masses m i ≪ M . The first step to understand the asymptotic behavior of the theory on the perturbative level is the investigation of single Feynman diagrams. We denote a Feynman graph by Γ, its corresponding analytic expression by I Γ ({p}, m, M ) and the superficial degree of divergence of I Γ ({p}, m, M ) by ω Γ .
For an arbitrary Feynman graph Γ we are interested in the kinematic region in which the external momenta, collectively denoted by {p}, are negligible compared to the mass of the heavy particle, that is p ≪ M .
As already mentioned in the introduction, asymptotic expansions can be derived with methods similar to those used for renormalization. To illustrate this remark, we consider a divergent diagram Γ in a theory regularized by a cut-off Λ in a zero-momentum-subtraction scheme. To renormalize the diagram, we state a power-counting theorem: there is a special class of subdiagrams of Γ, called one-particle-irreducible (1PI) graphs with the following property: if all 1PI-subgraphs of Γ have negative mass-dimension, each 1PI-subgraph and Γ are finite. If we succeed in isolating the divergences from the 1PI-subgraphs, we have also isolated the divergences of the complete diagram. To isolate the divergent part of an 1PI-subdiagram without subdivergences, we can perform a Taylor-expansion in its external momenta to reduce the mass-dimension of the diagram until it is convergent. If we perform Taylor expansions on all 1PI-subgraphs in the order as described in the R-operation of the zero-momentum-subtraction scheme, the Taylor expansion is always performed on 1PIsubgraphs without subdivergences; thus, the divergences are contained in the leading terms of the expansion while the remainder of the expansion contains 1PI-subgraphs with negative mass-dimension: it is finite. Expressed differently, the Taylor expansions generate the leading terms in the Λ-expansion of the diagram, as the power counting theorem ensures that the remainder is of higher order in 1/Λ. For large-mass expansions, the large mass M JHEP01(2016)092 plays similar role as Λ does in renormalization. In same way as the divergent terms -the leading terms in the 1/Λ-expansion -are isolated in renormalization, the leading terms in 1/M are isolated in the large mass expansion.
Guided by analogy, we first look for a power counting theorem that distinguishes the class of subdiagrams that rule the 1/M -behavior of the complete graph. Such a theorem can be found in ref. [15].
Let Γ be a diagram with l loops. The asymptotically-irreducible (AI) subdiagrams of Γ are those connected subdiagrams that contain heavy-particlepropagators and cannot be made disconnected by cutting a single light line. The the asymptotic behavior of I Γ ({p}, m, M ) is bounded by where S is that set of disconnected AI graphs containing all heavy lines which has the highest degree of divergence.
Consequently, by introducing an operator that reduces the degree of divergence of the AIdiagrams sufficiently (as the R-operation in momentum subtraction schemes reduces the degree of divergence to render 1PI graphs convergent) one can generate a remainder of an arbitrarily chosen order in the heavy mass. The difference between this remainder and the original (renormalized) diagram will then constitute the correct asymptotic expansion for the diagram. As this procedure is extensively described in [13], we only give the main result. To state it, some notations are required. Let S AI (Γ) be the set of mutually disjoint AI-subdiagrams, S an arbitrary set of disjoint subgraphs. Γ/S denotes the diagram Γ with all elements of S shrunk to a point. I Γ/S • γ∈S V γ is the expression corresponding to the diagram in which the vertex V γ replaces the subgraph γ for each γ ∈ S. R un I Γ/S denotes the R-operation that only acts on those parts of the diagram that do not contain vertices to which the graphs of S were shrunk.
Finally, M aγ γ performs a Taylor expansion of I γ ({p}, m, M ) in the momenta {p} external to the graph γ and the light masses m up to the order a γ .
In [13] it was shown that for a γ = a + ω γ one has, up to O M −a−1 -terms, It was also proven that this result is free of artificial ultraviolet-and infrared-divergences, that is, the divergences of this expression are the same as those for the original diagram. To summarize: in performing an asymptotic expansion in large masses on has to find all sets of mutually disjoint AI-subdiagrams of a diagram Γ. In each subgraph γ of such a set, one has Taylor-expand in external momenta and light masses. The result is a new vertex factor V γ that is reinserted in the original diagram to replace the subdiagram γ. Then the unaffected parts of Γ are renormalized as usual.
JHEP01(2016)092
We now consider the transition from the diagrammatic to the operator level; we want to derive an operator product expansion of an operator O with heavy quarks in terms of light degrees of freedom. We will merely summarize the argument of section 4.4 of ref. [14]. O can be considered as identical to a sum of operators from light degrees of freedom if all their Green's functions coincide. We concentrate on a Green's function with n light external fields Φ and an insertion of O, schematically written as: Peturbatively, this Green's function can be computed in terms of Feynman graphs. For each of the graphs Γ, we can use the relation (2.2). As O contains heavy quarks, it is always part of an AI-subdiagram. We single out this special subdiagram and leave the remaining AI-subdiagrams unexpanded; to complete the elimination of heavy particles in the theory they can be considered after the expansion of O, for example by using an effective lagrangian as obtained in ref. [4]. This procedure yields: We sum over all diagrams Γ contributing to eq. (2.3) and regard Γ/γ as new graph Γ ′ Vγ with a special vertex V γ where γ was shrunk to a point. The sum over Γ can now be divided into a sum over all vertices V that can be generated from AI-subgraphs and a sum over all possible graphs Γ ′ V with vertex V . We can exchange the sum over Γ ′ V and γ. The sum over γ is now over all AI-diagrams γ V with number and type of external lines appropriate for the vertex V : {q}, m, M ) has to be inserted at the location of the special vertex V in Γ ′ V and can be regarded as effective vertex V γ generated by composite operators. We realize that eq. (2.5) is the sum of all diagrams that contribute to eq. (2.3) with an insertion of effective vertices generated by all possible AI-subdiagrams involving O: The operators related to V γ constitute the desired asymptotic expansion. Thus, we have the following recipe: find all AI-diagrams involving O, compute their asymptotic expansion, express the result in terms of effective vertices generated by composite operators and read off the operator product expansion. We now consider the expansion of a heavy operator O in QCD. To expand the operator O of dimension dim(O) to the order a, one has to expand each AI-subgraph γ to the order a γ = ω γ + a on the diagrammatic level. Since in theories with dimensionless coupling constant the dimension of γ is number of external boson-and fermion-fields in γ, it is enough to consider diagrams that satisfy 0 ≤ a + dim(O) − E B − 3 2 E F . For example, at the order 1/M 2 for dim(O) = 3, only diagrams with E B ≤ 5 and E F ≤ 2 have to be taken into account as external fermions have to come in pairs. As we are working in a gauge theory gauge theories, Ward-identities will reduce the actual degree of divergence for diagrams with external vector bosons. This reduces the number of diagrams that have to be taken into account.
In this paper the vector current and the tensor current are considered. An operator product expansion is performed to the order 1/M 2 for the vector current and to the order 1/M for the tensor current. We consider terms up to the order α 3 in the strong coupling constant as this is the lowest order with purely fermionic operators.
The asymptotically-irreducible diagrams for fermion-bilinears
We now use the procedure outlined in section 2 to derive an operator product expansion of the vector and tensor current of a quark of mass M in perturbative QCD for the case of M being large compared to all external momenta, all other mass terms and -to ensure that perturbation theory is applicable -to Λ QCD .
The first step towards an expansion is the identification of the relevant AI-diagrams. First, some the general statements about their structure are discussed. These statements are then used to obtain a list of the AI-diagrams relevant for the expansion of the heavy vector and tensor current to the order α 3 in the strong coupling constant and 1/M 2 or 1/M in the large mass respectively.
The structure of the expansion is constrained by the following argument (see the appendix of ref. [10]). Since the heavy particles should not occur as external particles, every AI-diagram will contain heavy fermions only inside closed loops. Consider the fermion propagators S F (p, M ) of such a loop. If we assume that a regulator that admits the usual definition of γ 5 is used, they satisfy the relations Now, the emerging factors of γ 5 can be absorbed in the vertex factors via This procedure cancels all factors of γ 5 in the heavy-fermion-loop. The diagrams with vector current insertion remain unchanged while the signs of the diagrams with tensor current insertion are inverted. Thus, the expansion of the vector current is in even powers of M , that of the tensor current is in odd powers of M . We can further restrict the types of relevant diagrams. Only gluons can couple directly to the heavy quark loop. This means that each AI-diagram will have a subdiagram that can be considered as off-shell matrix element of the Green's function (3.5)
JHEP01(2016)092
Matrix elements with one external gluon are zero due to color conservation. Let us consider the case of two external gluons. Under charge conjugation, we have Global color conservation requires the matrix element with two gluons to be proportional to the only invariant color-tensor with two indices, δ a b . If one determines the proportionality constant by contracting with another factor of δ a b , one obtains: Applying charge conjugation to both sides of this relation yields: Therefore, for the vector and tensor current one needs to consider only diagrams where the fermion loop is connected to the rest of the diagram by at least three gluon propagators. Similar arguments show that there is only one possible color structure for the matrix elements with three external gluons: due to global color conservation two color structures for this matrix element are possible (8 ⊗ 8 ⊗ 8 contains two different singlets). These can be chosen as the two independent trace structures. In combination with charge conjugation invariance this leads to: For the case of the vector current, QED current conservation requires an additional factor of the momentum entering the diagram at the operator insertion. Dimensional analysis shows that this reduces the power of the heavy mass by one.
JHEP01(2016)092
We will show in section 4.1.1 that if three gluons couple directly to the fermion loop each of the external gluons causes an additional momentum-factor. Taking into account both kinds of momentum factors, the power of the heavy mass is g is the number of external gluons coupled directly to the heavy loop, δ = 1 for the vector current and δ = 0 for the tensor current if no more than three gluons couple directly to the heavy loop. If there are more than three gluons coupled to the loop, we have The general arguments about the large-mass dependence of matrix elements can now be used to give a complete list of relevant AI-diagrams for our expansions as shown in figure 1. Note that for all diagrams given in figure 1 one also has to compute the crossed diagrams. We start with one loop diagrams. Following the arguments given above, the diagrams with three external gluons, shown in figure 1a, give the first contributions for the vector current and the tensor current. For the vector current these diagrams are of order ω γ = −4, for the tensor current of order ω γ = −3. Actually these diagrams can be excluded from the computations at the order we consider. They are computed nevertheless, because we want to compare our results to the HQME-results of ref. [5]. The other diagrams relevant for the expansion have four external legs, as shown in figure 1b. These diagrams have ω γ = −2 for the vector current and of order ω γ = −1 for the tensor current. Our explicit computation and the results of section 4.1.1, however, showed that there are no 1/M 2 or 1/M contributions. This is consistent with the HQME results, which predict that all one-loop contributions are of order 1/M 4 for the vector current and 1/M 3 for the tensor current. Now, consider two-loop diagrams. Since at least three gluon lines must couple to the fermion loop, the relevant AI-diagrams are given by the figures 1c, 1d, 1e and 1f at order g 5 s and by 1g, 1h, 1i and 1j at order g 6 s . The three-loop diagrams are the first which contain external fermions. In the computation we will consider one arbitrary light quark flavor and afterwards take the sum over all light flavors to obtain the complete operator product expansion. If only two of the gluons are coupled to the fermion line, we have at least ω γ = −3 for the vector current and ω γ = −2 for the tensor current. Thus, the only possibility is to couple all three gluon legs to the fermion line, see figure 1k.
We now explain the absence of diagrams with ghost fields. Up to the order α 3 s in the strong coupling constant only external ghost lines can occur. Due to ghost number conservation the number of ghost fields must be even. Charge conjugation invariance shows that diagrams with two external ghost fields vanish: All nonzero diagrams with more than two external ghost fields are of higher order We now turn to those terms in the expansion that contain only gluonic operators. The requirement of local gauge invariance severly restricts their structure: they can contain only field strength tensors and covariant derivatives of them. Since the field strength tensor behaves under charge conjugation as the vector potential, arguments identical to those leading to eq. (3.12) restrict the result for both operators to the schematic structure tr c F 1 , F 2 F 3 . The vector current, which has to be the derivative of some antisymmetric tensor due to current conservation, has the structure ∂ tr c F 1 , F 2 F 3 . Power counting now shows that the gluonic contributions to the expansion should be of order 1/M 4 for the vector current and 1/M 3 for the tensor current to all orders of perturbation theory. Our computations up to O(α 3 s ) confirm these results.
JHEP01(2016)092 4 Computation of the asymptotically-irreducible diagrams
We can now use the relation (2.2) to compute the large mass expansion for the diagrams shown in figure 1. There is one additional simplification. In general, single diagrams in the heavy-quark mass expansion of the vector and tensor current have divergences, but the sum over all diagrams at a given order in the heavy mass and the coupling constant turns out to be finite. Actually even the sums of all diagrams of a given type (as indicated in figure 1) are finite. Thus, it is not necessary to perform the R-operation for them. To obtain the desired expansion, each AI-diagram has to be expanded in small masses and external momenta. For this purpose it is convenient to rescale the integration momenta according to l = Ml (this also makes the integration variables dimensionless). Since the complete Feynman integral is a homogeneous function of dimension ω γ , we have for n-loop integrals I n (M, {m}, {p}): In eq. (4.1) {l i } labels the set of integration momenta, {p} that of external momenta and {m} the set of light masses. Eq. (4.1) clearly shows that an expansion in small masses and momenta is equivalent to an 1/M -expansion. In the discussion of the different Feynman diagrams in the following subsections, we proceed as follows. The algebraic expression for the given diagram is given before rescaling. Prior to the Taylor expansion the momenta are rescaled as described above; the following expressions are given in terms of the rescaled variables.
After the Taylor expansion of the AI-diagrams we obtain several thousand of different tensor integrals and after tensor reduction there are thousands of scalar integrals. In the following we explain how the tensor reduction was done and how each type of diagram was computed. The computation was performed by a Mathematica program which made use of the package 'FeynCalc' [16]. In most cases the expansion of the AI-diagrams given above does not result in scalar integrals. This is either because of uncontracted Lorentz-indices in the diagram or because of scalar products of external and loop momenta occurring in the numerator in the 1/M -expansion of the integrand. We will explain how tensor integrals were reduced to scalar ones. Since the expansion is in all external momenta, the integrals that we obtain effectively correspond to diagrams without external momenta; they are vacuum diagrams. For these, the tensor decomposition is easy: the metric tensor is the only tensor that can occur in the result. All integrals with an odd number of indices vanish.
JHEP01(2016)092
An arbitrary integral F µ 1 ...µ 2n in the expansion can be parametrized as F µ 1 ...µ 2n = A 1 g µ 1 µ 2 · · · · · g µ 2n−1 µ 2n + all other contractions . (4.2) Here A i are Lorentz scalars. In general, there are (2n)!/(n! 2 n ) = (2n − 1)!! different contractions. In many cases, the integral is symmetric under the interchange of some of its indices. Then one can symmetrize both sides of eq. (4.2) such that the number of independent constants A i is further reduced. Now, contracting (4.2) with each of the independent tensor structures in turn, one obtains a system of equations for the A i with scalar integrals on the left-hand site. Solving for the constants and reinserting the solution on the right-hand side of (4.2), one obtains a decomposition of the integral in terms of scalar ones. The computation of the scalar integrals is described for each type of AI integral separately. Note, however, that the Feynman rules for the composite operator O(x) contain an additional factor of e iq·x in comparison to the usual Feynman rules for an identical term in the Lagrangian (this results from the fact that there is no integration over x).
The translation of the results of the Feynman diagrams to the operators occurring in the OPE can be done with different sophistication (for example with the help of the counterterm technique [17] or the method of projectors [18]). Here we simply give operators that yield vertices with the correct external fields and with vertex factors that are those polynomials resulting from the computation of the AI-graphs.
The vertex factor corresponding to an operator O(x) is: It is useful to note that the operator G b αβ corresponds to the projection operator on the transversal component of the momentum that enters the vertex: The generalization to higher powers of gluon fields is straightforward. Additional momentum factors are of course generated by additional derivatives of the gluon field operators. The situation is especially easy for additional factors of the overall momentum flowing into the vertex: . The O(g s )-contribution is of higher order in comparison to the diagrams considered here and can be neglected. We shall denote the OPE as Here '≃' indicates that the relation gives an asymptotic series. where J α a (x) = Q γ α T a Q (x) denotes the color current. In QCD the color current is not exactly conserved, but it satisfies the relation ∂ α J α a (x) = 0 + O (g s ). The fermion loop that we consider contains only the contributions of LO in g s . Thus, to analyze the loop we can assume that the current is conserved. Taking the divergence of the matrix element, LO terms are only generated by moving the derivative inside the time ordering: The commutators are determined by the transformation properties of the operators under SU(3) c -transformations:
JHEP01(2016)092
This gives the result (4.12) In momentum space, we have (4.13) Similar relations hold for all external momenta p 2 . . . p n . These results allow to draw conclusions for the case of three and four external gluons.
For three external gluons, we have (4.14) The last equality follows from charge-conjugation invariance as discussed above. From this relation (and from the corresponding ones for p 2 , p 3 ) it is clear that (4.15) Now, the power counting arguments given above apply: the matrix element for the tensor current is suppressed as M −3 and that for vector current as M −4 .
In the case of four external gluons: where n = 3 for the tensor current and n = 4 for the vector current. Since the same argument applies for all external momenta, those parts of the matrix elements not suppressed as described above must have at least four projection operators, that is, their Lorentz structure must be such that the contraction of the diagram with any external momentum is zero. Power counting and the general structure of the expansion for tensor and vector current yield a suppression of M −5 and M −6 for contributions with these projectors respectively.
Feynman integrals for the one-loop contribution
The only one-loop integrals to be computed are shown in figure 3. In general, we use the following conventions: momenta of external gluons are incoming, fermion momenta flow JHEP01(2016)092 For the diagrams of the type shown in 3a the analytic expression reads: where we use Γ = γ µ for the vector current and Γ = σ µν for the tensor current. For the diagram 1b with four external lines we obtain where we use l 3 = −q − l 1 − l 2 to simplify the notation (this is the momentum entering the last gluon vertex). The master integrals that occur after the expansion are of the form:
Result for the vector current
First consider the vector current in figure 3a. Up to the order 1/M 4 , the result of expanding the diagram and summing over all permutations of external momenta is: In this form the result clearly shows the expected projector structure: contracting with q µ , (l 1 ) α , (l 2 ) β or (l 3 ) τ we obtain zero. Due to the projector-structure of the results they can be easily rewritten in the form of vertices generated by the insertion of local composite-operators. If we omit the argument x and neglect higher terms in the coupling constant, a short calculation yields: With the application to instanton solutions in mind, we introduce the field strength tensor F µν = g s G µν . Thus, the contribution can be generated by This is exactly the result from the calculation of ref. [5] after continuing to Minkowskispacetime and rescaling the gluon fields. Explicit computation showed that the result for the diagrams of the type shown figure 3b corresponds exactly to the O g 4 s -contribution to eq. (4.22).
Result for the tensor current
For the tensor current a calculation similar to that of subsection 4.1.3 yields the following result: As expected the result vanishes for contractions with (l 1 ) α , (l 2 ) β or (l 3 ) τ . We can again write this in terms of an operator insertion: Thus, the one-loop contribution to the operator product expansion is which coincides with the result of ref. [4] if one takes into account the analytic continuation to Minkowski-spacetime and the rescaling of the gluon fields. As in the case of the vector current, the diagram figure 3b corresponds to the O g 4 s -contribution to equation (4.25).
Two-loop contribution
There are several different kinds of integrals at two-loop level. Their explicit forms are given in the appendices A and B. All relevant integrals can be computed in closed form and after rescaling have the form (4.28)
Three-loop contribution
At the three-loop level, the relevant diagram is shown in figure 4a. The corresponding integrals have the form where m is the mass of any of the light quark flavors. The integrals appearing after expansion have the form (4.30)
JHEP01(2016)092
These integrals are hard to compute directly, but the integration-by-parts (IBP) technique can be used to solve this problem. We discuss this in the next section.
The integration-by-parts technique
The integration-by-parts technique is a well-known tool to reduce large classes of Feynman integrals that are hard or impossible to compute analytically to a small number of so-called master-integrals. The procedure for the case of eq. (4.30) was first formulated in [19]. We will described a slightly modified version of this procedure below. There are several software packages that compute such integrals ('MATAD' [20], 'FIRE' [21]). However, as these integrals occur at an intermediate step of our computation and as one has to compute about 50.000 integrals, it was more convenient to write a program specialized on exactly this type of integral.
We will now show that we can use the IBP-technique to reduce an integral with arbitrary values of the indices α i to integrals which fall in one of the following classes: 1. α 1 ≤ 0, α 2 ≤ 0 or α 3 ≤ 0 2. α 5 ≤ 0 and α 6 ≤ 0.
Afterwards, we show how to compute the integrals for these special cases.
Using the relations one can use the fact that the integral of a total derivative is zero (if the boundary terms vanish), to obtain Each application of eq. (4.37) reduces the sum α 2 + α 4 + α 5 by one. Eq. (4.37) can be used recursively until one of the indices is zero. In the cases α 4 < 0 or α 5 < 0 this relation cannot be used. However, because of the conventional ordering of the indices, this case would imply a negative value of α 6 and it would require α 5 to be the second non-positive index. If finally either α 4 or α 5 is zero, one can stop, if α 6 is already non-positive. If this is not the case, one can interchange the indices to make α 6 the index which is zero. Then one can use the relation: This relation can be used until α 2 or α 5 is 0. We are now in position to discuss special cases. First we consider the case α 1 ≤ 0, α 2 ≤ 0 or α 3 ≤ 0. The cases α 1 ≤ 0, α 2 ≤ 0 can be reduced to the case α 3 ≤ 0. The relevant integral is: If one of the indices α 5 or α 6 is nonnegative, the integral is zero. Expanding the numerator and eliminating the factors of k +l 1 2 ,l 1 ·l 2 andl 2 2 from the numerator by cancellation with terms in the denominator, one is left with integrals of the type: Further cancellations yield integrals of the form (4.42) If α 1 or α 2 is non-positive, the integral is zero. If all indices are positive, the result is given by (4.27). Even if α 3 is negative, one can use this result as analytic continuation to α 3 < 0. Let us consider the case α 5 ≤ 0 and α 6 ≤ 0.
Renaming and exchanging integration variables in eq. (4.30) yield: If any of the massive lines has non-positive indices, the integral is 0. If α 4 is non-positive, the integral reduces to a product of three integrals like which can be computed using eq. (C.1). If all indices are positive we get: Performing thel 2 -integration and changing integration variables such that p < q, we get
JHEP01(2016)092
Note that in this case all terms in the numerator can be canceled with those in the denominator since all exponents are integers. The result is: At this point we can use eq. (4.27).
Result for the vector current
We now use the techniques of section 4.3.1 to derive the contributions for the vector current.
With α s = g 2 s /(4π) we obtain: where ζ(3) = ∞ n=0 1/n 3 is the zeta-function. If we denote the creation and annihilation operators for the light quark in the three-loop diagram by Ψ and Ψ respectively, it is possible to read off the corresponding operators immediately: (4.50) Note that we can freely interchange derivatives with covariant ones since the difference is of higher order in g s . Using the QCD equations of motion, / ∇ Ψ = −im Ψ and Ψ ← − / ∇ = im Ψ and the fact that the vector current for the light quarks is conserved, ∂ µ Ψγ µ Ψ = 0, we have (4.51) Applying these relations yields: (4.52)
Result for the tensor current
For the tensor the application of the method of section 4.3.1 yields: , (4.53)
JHEP01(2016)092
which, in terms of operators, can be written as: After applying equations of motion and standard relations for the γ-matrices we obtain: (4.55) The result for the tensor current can now be written as: (4.56)
Summary
We can now collect the contributions from the one-, two-and three-loop diagrams to the large-mass expansion of the vector and tensor current of heavy quarks. One has to remember that each light flavor will contribute to the three-loop diagrams. The result is: Here f denotes the sum over all flavors of quarks that are light compared to M . These operator identities can be used to analyze the intrinsic heavy quark content of light hadrons. In the next section we study the intrinsic charm influence on the nucleon's electromagnetic and tensor form factors.
Applications
The expansions of the heavy vector and tensor current in eqs. a single-nucleon state. The sum is over all quark flavors; we concentrate on the contribution of charm quarks, considered as heavy quarks, and regard up, down-and strange-quarks as light. Using eqs. (5.1) and (5.2), those terms involving charm-quarks can be expressed in terms of operators with light degrees of freedom. The expectation values of these operators can be expressed in terms of form factors of the light quarks and gluons. Thus, the influence of charm-quarks on the nucleon structure can be parametrized by the 'light form factors', which is a good starting point to estimate the relative importance of charm-quarks compared to light quarks for the nucleon structure. In section 6.1, this procedure is applied to the electromagnetic current and an estimation of the influence of charm-quarks on the charge radius and anomalous magnetic moment of the nucleon is obtained. Section 6.1 deals with the tensor current and provides estimates for the influence of charm on the tensor form factors of the nucleon.
Heavy-quark contribution to magnetic moment and electromagnetic radii of the nucleon
We can use the results of the previous section to derive a relation for the gluonic contribution to the nucleon's charge radius that is due to heavy quarks. We denote the momentum transfer by q = p ′ − p and the sum of the momenta by P = p ′ + p; the spinors for a nucleon of momentum p and spin σ are denoted by u (p, σ) and u (p, σ) and the nucleon mass by m N . First of all, we need the form factor decomposition for the vector and the tensor current. Using the form factors F 1 q 2 + iσ µν q ν 2m N and F 2 q 2 , the decomposition for the vector current is standard: The tensor current can be parametrized by form factors H T q 2 ,H T q 2 and E T q 2 as [22]: Actually, a parametrization of q ν p ′ , σ ′ | Ψ iσ µν Ψ(0) |p, σ is required: where we introduced the tensor magnetic form factor κ T q 2 = E T q 2 + 2H T q 2 and used the Gordon-identity. Additionally we introduce form factors of the gluon operator
JHEP01(2016)092
Since this operator is an antisymmetric tensor of rank 2, it can be decomposed as the tensor current. Thus, introducing the form factors R q 2 , S q 2 andS q 2 , and Now, we consider the nucleon matrix element of the vector current made of heavy quarks. Using the derived operator identity (5.1) we obtain the heavy quark contribution to the electric form factor G Q E q 2 = F Q 1 q 2 − q 2 /4m 2 N F Q 2 q 2 and the magnetic form We see that if we neglect the chiral corrections of order ∼ m f /m N , the leading ∼ (α s /π) 3 1/M 2 contributions can completely be expressed in terms of singlet electromagnetic form factors. The sub-leading corrections of order ∼ 1/M 4 are expressed in terms of form factors of the gluon operator eq. (6.5). This gives the following result for the heavy quark JHEP01(2016)092 contribution to the electric and magnetic radii r 2 : and (6.10) Finally, the heavy quark contribution to the magnetic moment (in nucleon magnetons) is: We see that the leading ∼ 1/M 2 contribution to µ Q has an additional suppression factor ∼ m f /m N indicating that the subleading correction ∼ 1/M 4 can be numerically more important than the leading one. The result for the heavy quark contribution to the magnetic moments (6.11) coincides with the result obtained in ref. [6]; the results for the electromagnetic radii (6.9), (6.10) are new. From eqs. (6.9), (6.10), neglecting the corrections of order ∼ m f /m N , one obtains the following model independent limits for the electromagnetic radii of the nucleon: We see that the limiting values of the heavy quark contribution to nucleon electromagnetic radii are always negative, so the intrinsic heavy quarks shrink the electromagnetic size of the nucleon. These limiting expression can be useful for lattice QCD simulations. Now we give numerical results for the heavy quark contributions to magnetic moment and electromagnetic radii in the case of the charm quark. We use the quark masses [23] and the coupling constant α s m 2 c = 0.3. The tensor form factors and the tensor anomalous magnetic moments were computed in the chiral quark soliton model [24,25]. The values for the proton and neutron are H u T,p (0) = H d T,n (0) = 0.92, H d T,p (0) = H u T,n (0) = −0.27, κ u T,p (0) = κ d T,n (0) = 3.03 and κ d T,p (0) = κ u T,n (0) = 1.496 [26,27]. For these calculations isospin symmetry was assumed and the values were evolved from a renormalization scale of µ 2 = 0.36 GeV 2 to µ 2 = m 2 c by the method described in these publications. The numerical result for the charm quark contribution to the electromagnetic radii of the nucleon is: The result for protons and neutrons is the same since the isospin violating effects due to mass difference of u and d quarks are negligible. We see that if the form factors of the gluon operator in eq. (6.5) are numerically of order of one, then the subleading term ∼ 1/M 4 is larger than the leading term for the case of the charm quark. This stresses the importance of the estimates of the gluon form factors in eq. (6.5). One of possibilities to estimate these form factors is the theory of instanton vacuum [28,29]. However, one can easily see that the gluon operator (6.5) is exactly zero on the instanton field. This implies that one has to consider the contribution of the instanton-anti-instanton pair to this operator; hence, the gluon form factors (6.5) are suppressed by the instanton packing fraction in the vacuum. Given such suppression, we can very roughly estimate the size of the gluon form factors as: S ∼ 10 −2 . (6.16) In eq. (6.5) the factor (N c − 2) takes into account that the gluon operator in eq. (6.5) is zero for the case of N c = 2, the factor πρ 2 /R 2 ∼ 1/3 is the instanton packing fraction, and f S ∼ 0.1 is the twist-4 contribution to the nucleon structure functions (see details in refs. [4,30,31]).
Of course, eq. (6.16) provides only a very rough estimation. Nevertheless, it indicates that suppression of the gluon form factors by the instanton packing fraction can be not enough to make the leading ∼ 1/M 2 term in charm quark mass expansion dominant numerically. Therefore, it is important to perform more accurate calculations of the gluon form factors; we shall give detailed a estimate of them elsewhere. Let us note obvious general properties of the gluon form factors (6.5): 1. they are exactly zero for the case N c = 2, 2. they are zero for general self-dual gluon field configurations.
For the heavy quark contribution to the magnetic moment the leading ∼ 1/M 2 term is suppressed by the factor ∼ m f /m N ; therefore we expect that for the case of the charm quark the sub-leading contribution ∼ 1/M 4 is dominant numerically. Indeed, if one takes
Conclusion and outlook
We derived the heavy quark mass expansion of the vector and tensor currents up to three loops using method of 'expansion by subgraphs'. The corresponding operator identities are summarized by eqs. (5.1), (5.2). We applied these results to analyze the influence of the intrinsic charm on the nucleon's electromagnetic and tensor form factors. We showed that the leading orders of the 1/M -expansion are model independent and can be expressed in terms of known light flavor nucleon form factors. For the sub-leading terms one needs the calculation of the nucleon matrix elements of the gluon operators of dimension six. We showed that the corresponding operators in the instanton vacuum are suppressed by the instanton packing fraction. However, the contribution of the gluon operators can still be numerically important for the case of charm quark.
The heavy quark mass expansion eqs. (5.1), (5.2) can used to study the intrinsic heavy quark content of other hadrons, for example of vector mesons. The detailed studies of these topics will be published elsewhere. In addition, the methods developed in this paper can be generalized to the case of other fermionic operators containing heavy quark fields. For example, one can derive the heavy quark mass expansion of the twist-2 heavy-quark operators. This will provide direct access to the intrinsic heavy quark content in the nucleon structure functions. Acknowledgments M.V.P. acknowledges support of RSF grant 14-22-0281.
We thank Arseniy Filin for useful remarks and suggestions concerning the preparation of this paper. there is a set of Feynman diagrams to compute. By changing the order in which the gluons couple to the fermion loop, several topologically different diagrams are generated from each basic type of diagram. Each of these diagrams had to be computed separately. However, all integrals in one class can be computed with the same methods. There are three different integrals of the type shown in figure 5a, three different integrals of that shown in 5b, six integrals of that shown in 5c and ten different integrals of the type shown in figure 5d. Additionally, all permutations of the external gluons have to be considered. This was achieved by symmetrising the results in the sets of external momenta, color-and Lorentz-indices. We now list the analytic expressions corresponding to the types of diagrams in figure 5, denoting the three-and four-gluon-vertices as V µντ abc (l 1 , l 2 , l 3 ) = g f abc g µν (l 1 − l 2 ) τ + g ντ (l 2 − l 3 ) µ + g τ µ (l 3 − l 1 ) ν , (A.1) W µντ ρ abcd = −ig 2 f abe f cde (g µτ g νρ − g µρ g ντ ) + f ace f bde (g µν g τ ρ − g µρ g ντ ) + f ade f bce (g µν g τ ρ − g µτ g νρ ) . (A.2) | 10,938.2 | 2016-01-01T00:00:00.000 | [
"Physics"
] |
Variational Autoencoders for Network Lifetime Enhancement in Wireless Sensors
Wireless sensor networks (WSNs) are structured for monitoring an area with distributed sensors and built-in batteries. However, most of their battery energy is consumed during the data transmission process. In recent years, several methodologies, like routing optimization, topology control, and sleep scheduling algorithms, have been introduced to improve the energy efficiency of WSNs. This study introduces a novel method based on a deep learning approach that utilizes variational autoencoders (VAEs) to improve the energy efficiency of WSNs by compressing transmission data. The VAE approach is customized in this work for compressing WSN data by retaining its important features. This is achieved by analyzing the statistical structure of the sensor data rather than providing a fixed-size latent representation. The performance of the proposed model is verified using a MATLAB simulation platform, integrating a pre-trained variational autoencoder model with openly available wireless sensor data. The performance of the proposed model is found to be satisfactory in comparison to traditional methods, like the compressed sensing technique, lightweight temporal compression, and the autoencoder, in terms of having an average compression rate of 1.5572. The WSN simulation also indicates that the VAE-incorporated architecture attains a maximum network lifetime of 1491 s and suggests that VAE could be used for compression-based transmission using WSNs, as its reconstruction rate is 0.9902, which is better than results from all the other techniques.
Introduction
Wireless sensor networks (WSNs) have revolutionized the process of sensing data in various domains by comprising multiple sensor nodes.WSNs include sensors to detect environmental data and an analog-to-digital converter to convert analog signals into digital data.They also comprise a microcontroller or Raspberry Pi for processing data with the help of the stored machine learning (ML) or optimization algorithms.A communication module, like XBee, is also included for wireless transmission, along with a power source for supplying energy to the node.Therefore, WSNs can be placed in various remote and Sensors 2024, 24, 5630 2 of 19 harsh environments where traditional wired sensors cannot be placed.Hence, WSNs are widely implemented in various fields, which include environmental monitoring, agriculture, healthcare, automation, surveillance, and military defense.The sensors included in WSNs create a distributed network that works to collect and transmit data to the source from its own base station.To achieve this, several wireless communication protocols are incorporated within the WSNs that permit the collection of information to be processed at the base station and enable several decisions to be made.The size, cost effectiveness, and flexible nature of WSNs make them suitable for various applications.However, their energy efficiency, network flexibility, and scalability are all factors that need to be improved in their present form.
Amongst their other limitations, energy efficiency occupies the highest priority, as it directly affects the overall performance of WSNs.The energy efficiency of WSNs can be improved by utilizing stored energy in an optimized way.Optimization methods are required, as WSNs are implemented with multiple sensors that can drain energy very quickly when all the sensors are in active mode.This can reduce the reliability of the system when it is implemented in the most important applications, such as healthcare and military surveillance, that necessitate continuous operation without any interruptions.Also, the draining of the energy supply from the battery may lead to the degradation of the WSN system, and so it is not suitable for long-term monitoring purposes.This limitation can be addressed by implementing an efficient network algorithm that can provide longer-term operation periods with a constant power supply.An efficient WSN model can also improve the costs spent on the monitoring system and protect the environment by reducing the number of batteries used and replaced.
Overview of Transmission Efficiency Improvement Methods
Traditional energy enhancement methods have optimized energy use by addressing the issues of signal interference, communication degradation, and bandwidth issues.Changing the characteristics of the carrier signal is the primary technique used for transmitting encoded data effectively to a destination with minimal energy requirements.Amplitude, frequency modulation, and phase shift keying are regular techniques that also provide reliable data communication between destinations that are great distances apart with minimal signal adjustments.Error control coding is also one of the traditional methods used to improve redundancy in WSNs in terms of the transmission of data to a destination by correcting errors.
The convolutional codes and hamming codes are some of the techniques that are widely used for such redundancy improvements.These methods improve the reliability of the data transmitted, even in noisy environments.Frequency-and time-based multiple access algorithms are methods that provide the simultaneous transmission of data from multiple sources to destinations connected to WSNs.Certain signal processing algorithms and equalization techniques have also been implemented in WSN systems to improve transmission efficiency.Equalization methods have been utilized in some applications where the transmission of data is dynamic due to channel conditions.Figure 1 indicates an overview of general transmission efficiency improvement techniques used for WSNs.
Variational Autoencoders
Variational autoencoders (VAEs) are a generative-model-based neural network approach that is widely used for unsupervised learning processes in data representation applications.The concept of VAEs is to extract the continuous latent information from the given high-dimensional data, like text, image, or any other signal, to provide compact data values that reflect the input data distribution.Unlike the regular autoencoders, the VAEs are included with a probabilistic framework based on a Gaussian distribution model that acts like an encoder, which allows for extracting the latent information effectively, in a distributed manner.Further, the output of the encoder is connected to a decoder network for resampling the distributed information received from the input.VAEs utilize an optimized loss function that regulates the reconstruction process on the latent space, and that improves the training process by learning only the meaningful information.Therefore, the performance of VAEs is comparatively better than that of the traditional autoencoders, as it provides scalable information.The reparameterization feature included in VAEs can provide gradient-based optimization from the useful information extracted from raw data.This interpretable ability makes VAEs suitable for big and complex data analysis.
Variational Autoencoders
Variational autoencoders (VAEs) are a generative-model-based neural network approach that is widely used for unsupervised learning processes in data representation applications.The concept of VAEs is to extract the continuous latent information from the given high-dimensional data, like text, image, or any other signal, to provide compact data values that reflect the input data distribution.Unlike the regular autoencoders, the VAEs are included with a probabilistic framework based on a Gaussian distribution model that acts like an encoder, which allows for extracting the latent information effectively, in a distributed manner.Further, the output of the encoder is connected to a decoder network for resampling the distributed information received from the input.VAEs utilize an optimized loss function that regulates the reconstruction process on the latent space, and that improves the training process by learning only the meaningful information.Therefore, the performance of VAEs is comparatively better than that of the traditional autoencoders, as it provides scalable information.The reparameterization feature included in VAEs can provide gradient-based optimization from the useful information extracted from raw data.This interpretable ability makes VAEs suitable for big and complex data analysis.
Motivation for Using VAEs in WSNs
The performance of WSNs is not satisfied in several applications, where it is required to operate with huge data generated by multiple sensors simultaneously.The performance is degraded due to limited energy availability, inefficient computational model, and reduced bandwidth allocation.These constraints can be addressed by implementing an efficient compression technique, and that reduces the size of data to be
Motivation for Using VAEs in WSNs
The performance of WSNs is not satisfied in several applications, where it is required to operate with huge data generated by multiple sensors simultaneously.The performance is degraded due to limited energy availability, inefficient computational model, and reduced bandwidth allocation.These constraints can be addressed by implementing an efficient compression technique, and that reduces the size of data to be transmitted effectively.The nature of VAEs indicates that they can compress the information available on any data by preserving the important features.The encoding option of VAEs can provide the compressed sensor data in a lower dimension latent space, to enable reduced data communication, to achieve a better energy conservation on limited bandwidth resources.Moreover, the robustness and intelligence of a WSN model can be improved with VAEs, and that can result in anomalies, faults, and intrusion detection.The latent space representation of data in VAEs can provide privacy to the sensitive data that are used for communication.In general, the integration of WSNs with VAEs can improve the overall integrity of WSNs including energy efficiency, security, and fault tolerance.The motive of the proposed work is as follows:
•
Provide an efficient compression technique for sensor data without losing valuable information;
•
Improve the routing process for the transmission of data from the source to the destination;
•
Enhance the energy efficiency of the overall sensor network to improve the network lifetime.
Energy Efficiency Improvement Techniques in WSNs
An improved grey wolf optimization technique [1] was developed to increase the energy efficiency of WSNs in industrial IoT applications.This improved model addressed the limitations of the traditional grey wolf method in terms of premature convergence and reduced population diversity.The simulation analysis indicated 333.51% betterment over the regular grey wolf optimization method on the network stability analysis [1].A threshold-enabled scalable and energy-efficient scheme [2] was proposed to support the wireless networks that was implemented in a large-scale IoT scenario with around five or more different sensor nodes for regulating the data transmission process by avoiding unnecessary data transmission.It was achieved by implementing a hybrid threshold-based minimum cost cross layer transmission at every node to stabilize the energy saving mode.Hence, the model allowed data transmission only when it is necessary by understanding the static and dynamic factors of the connected sensor nodes at different stages.The simulation result indicated a betterment of 29% on energy efficiency and 68% of network lifetime enhancement over the traditional scalable and energy efficient scheme [2].An alternative protocol approach [3] was designed to improve the energy efficiency by adjusting the time division and carrier sense multiple access in industrial wireless sensor networks.The work utilized carrier sense multiple access on light-weight data transmission and a modified selective activation technique for energy optimization and interference reduction between the redundant nodes.The work minimized the end-to-end delay and reduced the lower packet loss up to 25% on heavy traffic conditions when compared to the traditional industrial wireless network model implemented with IEEE 802.15.4 [3].
An advanced distributed energy-efficient clustering technique [4] was structured to improve energy efficiency in the autonomous cellular networks.The work transfers the data information in a better way through heterogeneous contexts with a 19% improvement on throughput over the LEACH [4].A hybrid particle swarm optimization technique was incorporated with improved low-energy adaptive clustering hierarchy [5] for improving the energy efficiency by determining a best cluster head and corresponding cluster nodes.The simulation work indicated an improvement of 28% in energy efficiency and 55% in network lifetime over the previous methods [5].A collaborative energy-efficient routing protocol [6] was designed for making a sustainable network model in the 5G and 6G communication systems.The work utilized the reinforcement learning approach for making a reliable cluster network for providing a successful transmission with the available energy.The multi-objective improved seagull algorithm was also included in the work for optimizing the overall performances.The experimental work indicated an improved energy efficiency of 50% over the previous methods [6].
Machine Learning in WSNs
A refined version of the Levenberg-Marquardt neural network [7] was proposed to improve energy efficiency by finding anomalies in WSNs.The work was also equipped with LEACH and energy-efficient sensor routing for making a reliable network connection between the source and the destination.The experimental work indicated a better performance with the model included with the machine learning approach over the regular methods [7].An energy-efficient machine learning-based regression algorithm was included with the fuzzy based intelligent routing approach [8] for improving the energy efficiency in WSNs.A fine cluster head was identified in the work, through a fuzzy interference system using the hop-count method.The experimental analysis indicated a betterment in terms of packet delivery ratio and throughput with energy efficiency [8].A reinforcement-learning-based multi-objective routing approach [9] was proposed with dynamic objective selection algorithm for optimizing energy consumption in IoT networks.The algorithm utilized informative-shaped rewards with correlated objectives for an efficient learning process.The work indicated an excellent delivery ratio along with a perfect data delivery latency [9].An artificial-neural-network-based approach was implemented [10] to select a better cluster head from the connected WSNs.The artificial neural network algorithm was equipped to analyze residual energy, number of nearby nodes, and distance to the base station for selecting the best cluster head.The algorithm was also included with energyefficient clustering algorithm for minimizing the energy consumption.It was achieved by switching OFF the cluster heads and their corresponding nodes, when there is no signal received for transmission, for a certain duration.The experimental work indicated a betterment in terms of energy enhancement and network lifetime over the traditional methods [10].An enhanced energy optimization approach was structured with a machine learning technique [11] to improve the energy efficiency in industrial wireless sensor networks.A knowledge-based learning technique was included in the work to detect the sensor node, one that can deliver the data information with minimum energy usage.The model also had a feedback control system for estimating the best routing process in the network.Hence, the work reduced the network traffic and improved the transmission energy consumption to 64.72% when compared to the regular methods [11].A multi-agentbased reinforcement learning approach was designed [12] to predict best energy efficient routing in WSNs.The work reduced the transmission delay and thus improved the average latency and network lifetime [12].A novel self-driven continual learning framework [13] was designed for motor fault diagnosis.The model can detect faults in WSN by making considerable customizations [13].
Autoencoders in WSNs
An error bond mechanism was incorporated to the autoencoders [14] for making an image compression technique suitable for WSNs.The work minimized the redundancies from the input data to improve the energy efficiency through exploitation of spatial and temporal correlations.The experimental work indicated a better decoding efficiency over the previous method at the rate of 70%.The work attained an energy efficiency of 50% improvement, at a compression value of 38.6% [14].An efficient resource allocation system was developed using autoencoders [15] for device-to-device communications.The approach was included with Hungarian algorithm, for reducing the data ambiguity in the data matrix.The experimental work achieved an accuracy of 83% and 90% in both training and validation, and the overall computational complexity was also found to be satisfied in the work, and that led to the minimum energy consumption [15].A hybrid algorithm was generated using autoencoder and the traditional WinRAR [16] for making an efficient compression technique, for both numerical and image data transmission.The work utilized the attention layer of autoencoder to minimize the reconstruction error.The performance of the hybrid algorithm was verified with the openly available oceanic data and found satisfied with a better compression ratio of 69% over the WinRAR and 48% over the multilayer autoencoders [16].An autoencoder-based machine learning technique [17] was proposed to improve the image transmission in the underwater IoT applications.The autoencoder method outperformed in underwater with its limited bandwidth.The work also overcomes the variable path loss in underwater scenario and provides a robust and efficient image transmission [17].A VAE-based data compression technique was incorporated with the traditional CNN and Restricted Boltzmann Machine [18] for compressing the numerical temperature sensor data.The experimental result indicated an average reconstruction error value of 0.0678 • C with 95.83% of reduced energy consumption over the traditional methods [18].Hence, it indicates that VAEs are widely preferred on wireless transmission for image compression applications over the numerical sensor data applications.
Summary
The energy efficiency methodologies of WSN involves several techniques like routing, clustering, and data aggregation processes.Nature inspired and metaheuristic optimization methods were widely used for making such energy efficient algorithms.However, those optimization algorithms may not be suitable for problems of WSN and customizing such optimization algorithms have become a complex part.Also, the computational cost and the requirement of peripheral devices improve the energy utilization of such optimization algorithms.In some applications, an uneven energy utilization can be observed, and it may result in sudden network failure.Similarly, optimization-based data aggregation systems have chances for missing the useful information generated by the sensors.Hence the machine learning-based approaches are introduced in the recent years to improve the energy efficiency of WSNs.Machine learning methodologies are designed to improve energy efficiency through anomaly detection, intelligent routing, cluster head selection, and data compression.It is achieved by leveraging adaptive learning and data-driven insights on WSN.Analyzing data and energy consumption patterns also improve the performance of WSN by predicting the energy shortages in advance.K-means clustering and fuzzy logic systems seem to be the popular algorithms that are incorporated in ML-based WSNs for optimizing the cluster head selection process.The neural network-based approaches improve the latency by observing the real-time conditions and data transmission patterns simultaneously.However, the ML algorithm might consume more energy than traditional optimization approaches, because of its nature on analyzing multiple data at the same time.
The proposed work aims to address the energy consumption issues of the previous methods, by using a data compression technique.The traditional optimization and MLbased algorithms are structured to analyze a huge amount of data for taking certain decisions, like routing path or cluster head selection.Therefore, the computational complexity of such models may take an additional consumption of energy for the operation of such complex algorithms.The proposed work addresses this issue by implementing an intelligent data compression technique using a popular ML technique called Variational Autoencoders.In traditional works, the huge sensor data were considered only for analysis; whereas in the proposed work, the huge sensor data is compressed directly, and it results in the minimal data transmission, to save the energy consumption on data transmission.VAEs were originally designed for compressing image data transmission, and it is customized in this work for compressing the numerical sensor data by adjusting their encoder and decoder properties.This adjustment allows the VAEs to observe numerical input features with an optimal compression and reconstruction accuracy.
Autoencoders vs. Variational Autoencoders
Data compression is the method widely used in applications where the dimensionality of the primary data must be reduced.The motive of such techniques is to share the same amount of information with minimum transmission bits.The autoencoders and variational autoencoders are the basic approaches implemented for data compression in machine learning-based applications.This approach transforms the data from higher to lower dimensional space through compression technique.Autoencoders can learn information efficiently from the unlabeled data through its encoder and decoder blocks.The encoder compresses the data from higher dimensional space to latent space, and the decoder is implemented to convert the latent space information back to higher dimensional space.However, the autoencoders have the limitation of generating valid information from the non-regularized input data.Variational autoencoders were developed to address this issue by improving its generative capability on the whole latent space created from the encoders.The encoders of VAE create output parameters with a predefined distribution for its every input created from the latent space.To regularize the latent space, VAEs are imposed with a constraint on the latent distribution, making it to provide a normal distribution [19].Figures 2 and 3 represent the architectural overview of autoencoder and the variational autoencoders.
address this issue by improving its generative capability on the whole latent space created from the encoders.The encoders of VAE create output parameters with a predefined distribution for its every input created from the latent space.To regularize the latent space, VAEs are imposed with a constraint on the latent distribution, making it to provide a normal distribution [19].Figures 2 and 3 represent the architectural overview of autoencoder and the variational autoencoders.
Architecture of Variational Autoencoders
VAEs are deep latent space generative models that exhibit excellent results on various applications like language models, protein design, and image generation.The VAEs are found to be one of the successful approaches among the other unsupervised learning techniques.The basic idea of VAE is to create a meaningful data distribution from the encoded information [20,21].In simple way, it can be descripted as: VAEs are utilized to generate a new data sampling from the given input information.For this, the VAEs are equipped with three major blocks called encoder, latent space and decoder.Encoder is the primary block that is used to compress the input information for making it suitable for the latent space.The latent space receives the compressed information from the encoder through the normal distribution with mean (µ) and variance (σ), and reduces the dimensionality of the received data by preserving the major and novel information mation from the non-regularized input data.Variational autoencoders were developed to address this issue by improving its generative capability on the whole latent space created from the encoders.The encoders of VAE create output parameters with a predefined distribution for its every input created from the latent space.To regularize the latent space, VAEs are imposed with a constraint on the latent distribution, making it to provide a normal distribution [19].Figures 2 and 3 represent the architectural overview of autoencoder and the variational autoencoders.
Architecture of Variational Autoencoders
VAEs are deep latent space generative models that exhibit excellent results on various applications like language models, protein design, and image generation.The VAEs are found to be one of the successful approaches among the other unsupervised learning techniques.The basic idea of VAE is to create a meaningful data distribution from the encoded information [20,21].In simple way, it can be descripted as: VAEs are utilized to generate a new data sampling from the given input information.For this, the VAEs are equipped with three major blocks called encoder, latent space and decoder.Encoder is the primary block that is used to compress the input information for making it suitable for the latent space.The latent space receives the compressed information from the encoder through the normal distribution with mean (µ) and variance (σ), and reduces the dimensionality of the received data by preserving the major and novel information
Architecture of Variational Autoencoders
VAEs are deep latent space generative models that exhibit excellent results on various applications like language models, protein design, and image generation.The VAEs are found to be one of the successful approaches among the other unsupervised learning techniques.The basic idea of VAE is to create a meaningful data distribution from the encoded information [20,21].In simple way, it can be descripted as: VAEs are utilized to generate a new data sampling from the given input information.For this, the VAEs are equipped with three major blocks called encoder, latent space and decoder.Encoder is the primary block that is used to compress the input information for making it suitable for the latent space.The latent space receives the compressed information from the encoder through the normal distribution with mean (µ) and variance (σ), and reduces the dimensionality of the received data by preserving the major and novel information available in the input.Decoder is the final block that reconstructs the information available in the latent space to its original form, same as of the input.
The Autoencoders (AEs) learn the features extracted from the compressed data structures of the input, and decompress the data structures again, to provide a valid output.In contrast, VAEs utilize the Bayesian model for extracting the features from the compressed data structures of the input to generate feature parameters through probability distribution of the given input.From this, the VAEs can create a new form of input data.Hence, the VAEs are represented as a generative architecture and AEs are represented as a reconstruction architecture.In VAEs, the actual input x = x N i=1 generates a random sample y = y N i=1 through discrete or continuous distribution variable.In high dimensional space, the output (y) provides a random vector from the latent space (z) generated from the encoder output e(x).
VAEs are included with a datapoint (x) as their input to their neural network block called the encoder, where its output is presented as a latent space (z).The weights and biases of the latent space (z) are adjusted with normal distribution parameters of mean (µ) and variance (σ).The latent space (z) is further connected as an input to the decoder block, where the neural network included in the decoder block provides an outcome as probability distribution of the given input.The Kullback-Leibler (KL) divergence is utilized to give an approximate distribution for the decoder d(z) with some e(x) as shown in Equation ( 1).Baye's rule is applied to Equation (1) for reducing the KL divergence as shown in Equation (2).
Since the KL divergence is expected to be shown with respect to z, the Equation ( 2) can be further presented as Equation ( 3) and the D KL is concluded as Equation ( 4) as it is always a positive one.
Evidence Lower Bound (ELBO) of VAEs is shown in Equation ( 4), and it is represented as the loss function of the neural network on its training process.The E[log d(z)] is presented as a reconstruction function, that is, the resultant of latent space (z).D KL [e(x)||d(z)] is used to find the similarity between the latent space (z) and its target distribution d(z).Therefore, there will always be two components on Equation (4), that makes the output similar to the input, by making latent space (z) distribution similar to the target distribution d(z) as much as possible.
VAEs for WSNs
In the proposed work, the VAEs are utilized for compressing WSN data, using a neural network architecture with the help of an encoder and decoder.The encoder is placed on the source to compress the generated data from the sensor nodes as a lower dimensional latent space, while the decoder is placed on the destination to reconstruct the received data into its original value.Therefore, the property of the encoder in VAE is modified in the proposed work with a fully connected layer, for making the model suitable for reading the numerical inputs from the dataset with reduced power consumption, and the ReLU activation function is included for improving the learning stability with the limited computational resources.It is achieved by preventing the overfitting issues on the learning process.Similarly, a well distributed latent space is required for reducing the reconstruction errors of VAE, and that is achieved by fine tuning the model parameters.The latent dimensionality and weights on the reconstruction and KL divergence loss are customized in this work, to make VAE suitable for the proposed application.The performance of the trained VAE can be improved by having a continuous optimization or fine-tuning process while implemented on the real time WSN architectures.This iterative approach improves the performance of VAE, based on the feedback received from the actual network.The energy utilization of the VAE can also be improved by this iterative approach, as it operates the essential data with minimal resources.The performance of the proposed model is also improved on diverse and variational data patterns, as the network is retrained regularly by varying the hyperparameters of VAE.The integration of VAE to WSN provides a better lifespan on WSNs, as it reduces the amount of data transmission through compression technique.The compression remains effective as VAE preserves the crucial information on the generated sensor data.Similarly, VAE improves the data processing ability of the WSNs that results in effective decision making and analysis on the data transmission process.Overall, the proposed work is found to be suitable for WSN applications that are implemented with limited resources.The algorithmic flow of VAE in WSN is descripted below in Algorithm 1.
Combine the reconstruction loss and the KL divergence loss to form the total loss: total_loss = reconstruction_loss + KL_divergence_loss 8: Optimization and iteration: Backpropagation is used to minimize the total loss and iterate over the dataset for multiple epochs, adjusting model parameters.9: Output Compressed representation (z) and reconstructed data (y)
Experimental Setup and Results
The performance of the proposed work is verified with the dataset collected from the Intel Berkeley Research Lab [22].The dataset contains temperature, light, humidity and voltage readings collected from 54 sensors that are placed in the lab for 38 days.Data was collected continuously for every 31 s from the lab with the help of a TinyOS platform.The missing values were normalized in the dataset through a mean average method, and the sensor values were regularized with Min-Max scaling function to ensure the uniformity among the connected sensors.The preprocessed dataset is further augmented to improve the training performance by increasing the sample sizes on the available dataset.The augmented dataset is divided into two sets with a ratio of 80% (40,000 samples) and 20% (10,000 samples) for the training and testing process in VAE integrated WSN architecture.
The simple workflow of the experimental analysis is shown in Figure 4.The performance of the proposed work is compared to that of the Compressed Sensing (CS) technique [23], Lightweight Temporal Compression (LTC) [24], and the Auto Encoder (AE) technique [25].Compressed sensing is a signal compressing technique that is basically used for non-adaptive linear measurements.It is included in WSN for minimizing the spatial and temporal correlations of the sensor data, and that can be reconstructed later based on the requirement.Implementing CS to WSN is quite simple than any other technique, as most of the sensor data are represented in sparse formats.CS approaches are familiar for its effectiveness on reconstruction of data from the minimum number of random linear Sensors 2024, 24, 5630 10 of 19 measurements.The performance of the CS can be improved further when it is implemented with convex optimization.Lightweight temporal compression is a time series sensor data compression technique used for reducing the transmission overhead.LTC stores only the changes on the transmitting data rather than storing them all together.This minimizes the amount of data transmitted between the source and destination, by preserving the major temporal trends and patterns of the sensor data.The encoding of LTC is simple, and that does not require any major computational facility.As the encoding is simple, the energy utilization of LTC is also minimal in nature.This makes the LTC well suited for several WSN applications.Autoencoder is an unsupervised learning approach for efficient data representation.AEs are best in reducing the reconstruction error, and that improves the compression efficiency.This makes AE suitable for complex WSNs.
later based on the requirement.Implementing CS to WSN is quite simple than an technique, as most of the sensor data are represented in sparse formats.CS appr are familiar for its effectiveness on reconstruction of data from the minimum num random linear measurements.The performance of the CS can be improved furthe it is implemented with convex optimization.Lightweight temporal compression is series sensor data compression technique used for reducing the transmission ov LTC stores only the changes on the transmitting data rather than storing them gether.This minimizes the amount of data transmitted between the source and d tion, by preserving the major temporal trends and patterns of the sensor data.T coding of LTC is simple, and that does not require any major computational faci the encoding is simple, the energy utilization of LTC is also minimal in natur makes the LTC well suited for several WSN applications.Autoencoder is an un vised learning approach for efficient data representation.AEs are best in reduc reconstruction error, and that improves the compression efficiency.This makes A able for complex WSNs.To evaluate the performance of the proposed work, the VAEs are finetuned WSN application with customized encoder and decoder layers.As the dataset u the work contains the information of 54 sensors, the input layer is structured w different neurons for gathering the data in an efficient way.The hidden layers in between the input and the latent space layer were reduced gradually for observ useful information from the given data.The neuron layers at the latent space a To evaluate the performance of the proposed work, the VAEs are finetuned for the WSN application with customized encoder and decoder layers.As the dataset used for the work contains the information of 54 sensors, the input layer is structured with 54 different neurons for gathering the data in an efficient way.The hidden layers included between the input and the latent space layer were reduced gradually for observing the useful information from the given data.The neuron layers at the latent space are customized dynamically with respect to the feedback received from the output layer.Table 1 represents the number of neurons in each layer.
MATLAB R2023a simulation is utilized in the work for evaluating the performance of the proposed concept with the existing one.The output of the pretrained VAEs is incorporated to the WSN architecture for transmitting the compressed information, for estimating its performance on the transmission.Similar estimation is done for the other existing techniques, to prove the betterment of the proposed work.The network parameters used for analyzing the WSN performance is presented in Table 2.
Evaluation Metrics
The experimental work aims to analyze the compression efficiency of the VAE and is also experimented to present its betterment on transmitting data to the destination with minimal energy requirement.Compression ratio, and reconstruction quality are the factors considered in the work, to estimate the performance of VAE over the existing techniques.
Compression ratio (C R ) defines the amount of original sensor data that has been compressed by the approach.A higher value of compression indicates its efficiency.Compression ratio can be descripted mathematically as follows.
C R =
Original data in bytes Compressed data in bytes Reconstruction quality R Q is used to represent the accuracy of the reconstruction of data from the given compressed data.Mean Square Error (MSE) is the primary metric used for estimating the reconstruction quality.A higher reconstruction quality gives a minimal loss information of the given input.
Energy consumption, delay and the network lifetime availability are the factors considered in the work for estimating the performance of VAE integrated WSN model.Energy consumption is calculated for the operation of the network in full load operation with respect to time.It represents the amount of energy required for an efficient operation, and that can be represented mathematically as follows.
Energy consumption(E
Delay is used to analyze the time taken for transmitting a data from the source to the destination, and is denoted in milliseconds.It includes compression and decompression time along with the transmission time, and is represented as follows.
Network lifetime is the parameter that can present the overall operation time of the WSN.It is directly related to the energy required for compression, transmission and the routing process.The below formula indicates the mathematical representation of the network lifetime.
Network li f etime(N L ) =
No. o f nodes × Given energy Avg.consumption per unit time × Active nodes in%
. Performance Analysis
The comparison chart of the compression ratio of the proposed VAE, in comparison to the existing methods is shown in Figure 5, and its average value is projected in Table 3. Figure 5 signifies that the compression ratio of VAE is comparatively higher than the three (AE, CS and LTC) existing methods.The maximum compression ratio of VAE reaches near 2.5, and its average compression ratio is 1.5572 which is better among all the existing methods considered.AE that attains an average compression ratio of 1.4111, provides a competitive compression ratio to the proposed VAE.CS algorithm provides the least average compression ratio of 1.2956, whereas the compression ratio by LTC is 1.3613.This analysis indicates that the amount of data transferred through VAE is comparatively less, than that of the other methods.Since the amount of data transferred though VAE based WSN is less, it can provide a better network lifetime than the other approaches.The performance of the VAE is found satisfactory, due to its probabilistic nature of encoding and decoding process.Similarly, the latent space regularization on the objective of VAE, makes the model learn the compact data representations at a high compression rate.Compression ratio is one of the primary analyses that is required for calculating the amount of data transferred in a WSN.However, data reconstruction rate needs to be considered for identifying an overall efficiency of a compression algorithm.Figure 6 indicates the reconstruction data and its error value of the analyzed methods.It compares the reconstruction data of all 10,000 original data samples with the reconstructed data, to find the reconstruction error.The average reconstruction rate of each model is shown in Table 4.It can be found that the reconstruction rate of VAE is high at 0.9902, which shows a better reconstruction rate of 0.0793 than the AE model, due to the involvement of Kullback-Leibler divergence in VAEs.KL helps in avoiding the overfitting issues, and the loss function of VAE reduces its reconstruction error.LTC shows a poor reconstruction rate of 0.4984 and CS provides a decent reconstruction rate of 0.7552.From this analysis, it is observed that VAE provides excellent compression and reconstruction rate than the comparative methods.The experimental work identifies that CS algorithm provides a low compression rate and the LTC algorithm provides a poor reconstruction rate.
it is observed that VAE provides excellent compression and reconstruction rate tha comparative methods.The experimental work identifies that CS algorithm provi low compression rate and the LTC algorithm provides a poor reconstruction rate.Figure 7 indicates the number of active sensor nodes available in the WSN architecture on every 100 s, in the overall simulation time of 1500 s.It can be discovered that the number of active nodes available in the VAE incorporated WSN is always higher than all the other methods.This has been attained as the number of retransmissions are less in VAE due to its betterment in reconstruction rate.The performance of AE comes in between VAE and CS, where all the active nodes are dead around 1300 s of simulation time It has also been observed that the number of active nodes of both AE and VAE are same up to 100 s, then a steady drop has been observed from 100 to 800 s and that leads to all node dead state before 1300 s.Similarly, all the sensor nodes of CS and LTC approaches went into dead state before 1200 s and 700 s respectively.It has also been observed that VAE exhibits significantly better performance, with a notable deviation up to 1000 simulation seconds compared to the other three methods.The residual energy availability of the sensor network for all the approaches has been shown in Figure 8.It can be deduced that the residual energy of VAE included sensor network is comparatively higher than that of the other approaches.It is achieved Figure 7 indicates the number of active sensor nodes available in the WSN architecture on every 100 s, in the overall simulation time of 1500 s.It can be discovered that the number of active nodes available in the VAE incorporated WSN is always higher than all the other methods.This has been attained as the number of retransmissions are less in VAE due to its betterment in reconstruction rate.The performance of AE comes in between VAE and CS, where all the active nodes are dead around 1300 s of simulation time.It has also been observed that the number of active nodes of both AE and VAE are same up to 100 s, then a steady drop has been observed from 100 to 800 s and that leads to all node dead state before 1300 s.Similarly, all the sensor nodes of CS and LTC approaches went into dead state before 1200 s and 700 s respectively.It has also been observed that VAE exhibits significantly better performance, with a notable deviation up to 1000 simulation seconds compared to the other three methods.
The residual energy availability of the sensor network for all the approaches has been shown in Figure 8.It can be deduced that the residual energy of VAE included sensor network is comparatively higher than that of the other approaches.It is achieved due to the better compression rate of VAE.Though the compression rate of AE is better than that of VAE, its poor decompression rate increases its total number of retransmissions, and that leads AE to perform lower than VAE in terms of residual energy.The performance of CS approach shows a steady energy drop from the beginning that leads to a complete network failure before 1200 s.The LTC indicates the poorest residual energy performance due to its poor compression rate.The poor compression rate makes the network to send huge amount of data and that allows the nodes to consume huge energy on its operation.up to 100 s, then a steady drop has been observed from 100 to 800 s and that leads to node dead state before 1300 s.Similarly, all the sensor nodes of CS and LTC approac went into dead state before 1200 s and 700 s respectively.It has also been observed VAE exhibits significantly better performance, with a notable deviation up to 1000 si lation seconds compared to the other three methods.The residual energy availability of the sensor network for all the approaches been shown in Figure 8.It can be deduced that the residual energy of VAE inclu sensor network is comparatively higher than that of the other approaches.It is achie due to the better compression rate of VAE.Though the compression rate of AE is be than that of VAE, its poor decompression rate increases its total number of retransm sions, and that leads AE to perform lower than VAE in terms of residual energy.performance of CS approach shows a steady energy drop from the beginning that le to a complete network failure before 1200 s.The LTC indicates the poorest residual ergy performance due to its poor compression rate.The poor compression rate makes network to send huge amount of data and that allows the nodes to consume huge ene on its operation.Figure 9 specifies the energy consumption by the nodes for transmitting 1 byte data.It can be determined that the AE approach consumes the least energy of 0.00 joules for transmitting 1 byte of data, whereas VAE consumes a slightly higher energy 0.00003 joules than AE, due to its superior data compression ratio.Hence, the t amount of data retransmission becomes lesser in VAE, and that enhances the netw lifetime.LTC consumes very large energy of 0.00320 joules, as its computational cos very poor among the other methods.CS is observed with an energy consumption 0.00267 joules for its operation.In general, the overall energy consumption of a W architecture tends to increase with the number of sensor nodes deployed.This is beca more sensor nodes generate more data, which can lead to network congestion.Netw congestion, in turn, can result in a higher drop rate and more retransmissions.Con quently, the energy consumption per byte of transmission can potentially increase du these factors.The specific energy consumption per byte provided for the current set o sensor nodes has been given in Figure 9 and may vary with the addition of more node It can be determined that the AE approach consumes the least energy of 0.00184 joules for transmitting 1 byte of data, whereas VAE consumes a slightly higher energy of 0.00003 joules than AE, due to its superior data compression ratio.Hence, the total amount of data retransmission becomes lesser in VAE, and that enhances the network lifetime.LTC consumes very large energy of 0.00320 joules, as its computational cost is very poor among the other methods.CS is observed with an energy consumption of 0.00267 joules for its operation.In general, the overall energy consumption of a WSN architecture tends to increase with the number of sensor nodes deployed.This is because more sensor nodes generate more data, which can lead to network congestion.Network congestion, in turn, can result in a higher drop rate and more retransmissions.Consequently, the energy consumption per byte of transmission can potentially increase due to these factors.The specific energy consumption per byte provided for the current set of 54 sensor nodes has been given in Figure 9 and may vary with the addition of more nodes.
more sensor nodes generate more data, which can lead to network congestion.Net congestion, in turn, can result in a higher drop rate and more retransmissions.C quently, the energy consumption per byte of transmission can potentially increase d these factors.The specific energy consumption per byte provided for the current set sensor nodes has been given in Figure 9 and may vary with the addition of more no The average time taken for data transmission and the network lifetime of the proposed WSN architecture with various compression technique are shown in Figures 10 and 11 respectively.It can be found that AE provides a minimum delay of 0.105 milliseconds for transferring 1 byte from source to destination.The delay of AE model is comparatively better than the VAE, as the compression rate is lower in AE.However, the better compression rate of VAE gives an overall improvement in the network lifetime that can be seen in Figure 11.The VAE attains a maximum network lifetime of 1491 s; whereas, in AE the network life is 1267 s, that is 224 s better than that of the AE.The transmission delay of both CS and LTC are slightly higher than that of the VAE, and their network lifetime is also comparatively lesser than that of the VAE.Moreover, the LTC shows the least network lifetime of 678 s.
Sensors 2024, 24, x FOR PEER REVIEW 1 The average time taken for data transmission and the network lifetime of th posed WSN architecture with various compression technique are shown in Figu and 11 respectively.It can be found that AE provides a minimum delay of 0.105 seconds for transferring 1 byte from source to destination.The delay of AE mo comparatively better than the VAE, as the compression rate is lower in AE.Howeve better compression rate of VAE gives an overall improvement in the network lifetim can be seen in Figure 11.The VAE attains a maximum network lifetime of 1491 s; w as, in AE the network life is 1267 s, that is 224 s better than that of the AE.The tran sion delay of both CS and LTC are slightly higher than that of the VAE, and their ne lifetime is also comparatively lesser than that of the VAE.Moreover, the LTC show least network lifetime of 678 s.
Discussion
The performance of the proposed work was verified in a common network that is shown in Table 2 with the standard ODV routing with LEACH cluster hea tion model.The performance of the proposed work can also be improved in te network lifetime, delay or energy consumption with an alternative routing or im cluster head selection approach.However, the performance of the proposed work affected with several factors like hardware limitations, signal interference and source availability on real-time deployment.Therefore, a careful consideration o
Discussion
The performance of the proposed work was verified in a common network setup that is shown in Table 2 with the standard ODV routing with LEACH cluster head selection model.The performance of the proposed work can also be improved in terms of network lifetime, delay or energy consumption with an alternative routing or improved cluster head selection approach.However, the performance of the proposed work can be affected with several factors like hardware limitations, signal interference and power source availability on real-time deployment.Therefore, a careful consideration of computational components, memory units, and power resources are required for a successful ML-based implementation.Also, the complexity of the ML algorithm, number of connected sensors and the amount of data to be processed require a powerful CPU, GPU and memory units.For implementing the proposed work, a multi-core CPU of 3.0 GHz or higher is required for handling the coordination between the connected components.Similarly, a GPU of 8-12 GB and a RAM of 16-32 GB are required for processing the huge data generated by the sensors in parallel to the execution of the VAE algorithm without any buffering.In such cases, power consumption by the compression algorithm would be a constraint, and that can be rectified by implementing an efficient batch processing technique along with a careful thermal management process.
Conclusions and Future Research Directions
Network lifetime is one of the primary constraints considered for implementing a successful WSN.Several techniques like routing, clustering, load balancing, and duty cycling are the most widely used methods for WSN lifetime improvement.The proposed work utilizes a data aggregation method for improving the network lifetime, where the variational autoencoders are considered.To prove the efficiency of the variational autoencoders, its performance on data compression and reconstruction was compared to that of several existing methods.This work utilizes the Intel Berkeley Research Lab dataset for its analysis, which was found to be satisfied with VAE on both compression and reconstruction.Reconstruction plays a significant role in the satisfaction of any compression technique to reach the actual sensor data at the destination.The VAE-based method was found to be satisfactory, with a better network lifetime than all the comparative methods.However, the delay and energy consumption for data transmission seem to be slightly higher than that of AE.AE attains a minimum delay and a better energy consumption due to its lesser computational cost.Although AE is better on delay and energy consumption, it cannot overtake VAE, as its reconstruction rate is marginally higher than that of AE.In the
Algorithm 1 .
Algorithmic flow of VAE in WSN 1: Input Sensor data (x) 2: VAE Architecture Design the encoder e(x) and decoder (y) neural networks for WSN applications Indicate the latent dimensionality of the VAE (z) 3: Encode the Sensor Data (x) Get the mean (µ) and log variance (σ) of the latent space (z) representation through the encoder e(x) (µ, σ) = e(x) 4: Sample from Latent Space (z) Sample the mean (µ) and log variance (σ) to obtain the latent representation (z) through a normal distribution z ~N(µ, σ), where σ = exp(0.5× logσ) 5: Decode Latent Representation Pass the latent representation (z) through the decoder d(z) to reconstruct the sensor data: y = d(z) 6: Loss Calculation Calculate the reconstruction loss from the original input x and the reconstructed data x_recon, and calculate the KL divergence loss to regularize the latent space distribution:
Figure 4 .
Figure 4. Experimental flow of the proposed work.
Figure 4 .
Figure 4. Experimental flow of the proposed work.
Figure 5 .
Figure 5.Comparison of the compression ratio of different methods.
Figure 5 .
Figure 5.Comparison of the compression ratio of different methods.
Figure 5 .
Figure 5.Comparison of the compression ratio of different methods.
Figure 6 .
Figure 6.Comparison of reconstructed data and error of different approaches.
Figure 7 .
Figure 7.Comparison of active nodes over simulation time.
Figure 6 .
Figure 6.Comparison of reconstructed data and error of different approaches.
Figure 7 .
Figure 7.Comparison of active nodes over simulation time.
Figure 7 .
Figure 7.Comparison of active nodes over simulation time.
Figure 8 .
Figure 8.Comparison of residual energy over simulation time.
Figure 8 .
Figure 8.Comparison of residual energy over simulation time.
Figure 9
Figure 9 specifies the energy consumption by the nodes for transmitting 1 byte of data.It can be determined that the AE approach consumes the least energy of 0.00184 joules for transmitting 1 byte of data, whereas VAE consumes a slightly higher energy of 0.00003 joules than AE, due to its superior data compression ratio.Hence, the total amount of data retransmission becomes lesser in VAE, and that enhances the network lifetime.LTC consumes very large energy of 0.00320 joules, as its computational cost is very poor among the other methods.CS is observed with an energy consumption of 0.00267 joules for its operation.In general, the overall energy consumption of a WSN architecture tends to increase with the number of sensor nodes deployed.This is because more sensor nodes generate more data, which can lead to network congestion.Network congestion, in turn, can result in a higher drop rate and more retransmissions.Consequently, the energy consumption per byte of transmission can potentially increase due to these factors.The specific energy consumption per byte provided for the current set of 54 sensor nodes has been given in Figure9and may vary with the addition of more nodes.
Figure 9 .
Figure 9. Energy consumption of different algorithms at per byte transmission.
Figure 9 .
Figure 9. Energy consumption of different algorithms at per byte transmission.
Figure 10 .
Figure 10.Average time taken for transferring 1 byte of data.
Figure 10 .
Figure 10.Average time taken for transferring 1 byte of data.
Figure 10 .
Figure 10.Average time taken for transferring 1 byte of data.
Figure 11 .
Figure 11.Network lifetime using different methods.
Figure 11 .
Figure 11.Network lifetime using different methods.
Table 1 .
Neuron count in each layer of the proposed VAE network.
Table 2 .
Simulation parameters of WSN.
Table 3 .
Average compression ratio of different methods.
Table 3 .
Average compression ratio of different methods.
Table 4 .
Average reconstruction rate of different methods.
Table 4 .
Average reconstruction rate of different methods.
Table 4 .
Average reconstruction rate of different methods. | 12,224.8 | 2024-08-30T00:00:00.000 | [
"Computer Science",
"Engineering",
"Environmental Science"
] |
Survey of Software-Implemented Soft Error Protection
: As soft errors are important design concerns in embedded systems, several schemes have been presented to protect embedded systems against them. Embedded systems can be protected by hardware redundancy; however, hardware-based protections cannot provide flexible protection due to hardware-only protection modifications. Further, they incur significant overheads in terms of area, performance, and power consumption. Therefore, hardware redundancy techniques are not appropriate for resource-constrained embedded systems. On the other hand, software-based protection techniques can be an attractive alternative to protect embedded systems, especially specific-purpose architectures. This manuscript categorizes and compares software-based redundancy techniques for general-purpose and specific-purpose processors, such as VLIW (Very Long Instruction Word) and CGRA (Coarse-Grained Reconfigurable Architectures).
Introduction
With technology scaling, the embedded processors' reliability against soft errors is becoming a critical design concern, especially in embedded systems [1]. Soft errors are transient faults in semiconductors caused by external radiations, such as alpha particles, neutrons, muons, and cosmic rays [2]. The soft error rate is constantly increasing [3] and threats to soft errors can no longer be ignored. For instance, a single soft error has stopped a billion-dollar automotive firm every month [4]. Further, the reliability of embedded systems is becoming more critical as embedded systems could be exploited in crucial and safety-critical applications, such as fiscal programs, mobile healthcare devices, and automotive systems, in the near future [5].
As soft errors are hardware-level transient faults in semiconductor devices, diverse hardware-based approaches have been proposed in order to protect systems against soft errors. One of the most straightforward techniques is hardening, that is, making hardware resistant to damage or system malfunctions caused by ionizing radiation. The amount of radiation can be affected by altitude, nuclear energy, and cosmic rays [6]. However, it is impossible to protect systems via hardware hardening perfectly; e.g., neutron-induced soft errors can pass through many meters of concrete [7]. Moreover, hardware hardening techniques also induce severe overheads in terms of area and power consumption.
In order to mitigate overheads, optimized hardware-based protection has been proposed. For memory systems, information redundancy techniques, such as error detection codes (e.g., parity code and Hamming code), have been proposed [8]. Information redundancy schemes detect or correct erroneous data bits by adding check bits to the data based on the coding theory [9]. On the other hand, modular redundancy (e.g., dual or triple modular redundancy) has been presented for non-memory system [10]. Modular redundancy schemes exploit additional modules to detect or correct data mismatch by comparing results between original and replicated modules.
However, it is not surprising that even optimized hardware-based protection techniques still incur significant overheads in terms of hardware costs and power consumption. For instance, the access latency can be larger than the tripled one of unprotected architectures if the level 1 data cache is protected by an error correction code [11]. Even though hardware-based modular redundancy techniques can execute the same operation in different architectures to minimize the performance overhead, they incur severe overheads in terms of hardware area and power consumption [12].
Hardware-based protection techniques are not appropriate for resource-constrained embedded systems due to overheads in terms of hardware area and power consumption. Further, hardware-based schemes cannot provide knobs to trade reliability for performance as they are applied at the manufacturing stage [13]. In order to mitigate overheads and provide comparable reliability, several software-based techniques have been presented. The origin of software-based protection techniques is primitive. N-version programming [14] independently generates N functionally equivalent programs and compares their results. Then, it can detect soft errors or software bugs if their results are not identical. However, software engineers always put in considerable effort, as they need to implement the same program in different ways. Thus, there is a necessity to protect embedded systems against soft errors via automated software-based techniques.
In this manuscript, we have categorized software-level protection techniques against soft errors based on the hardware characteristics. Processors can be classified into two major categories such as general-purpose processors and special-purpose processors. As generalpurpose processors have no particular target application domain, they can be used for servers, laptops, and tablets. Software-level protection schemes for these processors should provide the comparable fault coverage regardless of ISAs (instruction set architectures). On the other hand, special-purpose processors are used for accelerating kernel parts of programs as co-processors [15]. As these processors can vary depending on their purpose, existing software-based protection schemes do not work in an efficient manner. Thus, various protection schemes have been presented for special-purpose processors considering hardware characteristics.
Oh et al. [16] proposed EDDI (Error Detection by Duplicated Instructions), which duplicates instructions on different registers or memory and inserts comparison and validation at the store or branch operations of the compilation stage. EDDI can detect most soft errors without any hardware modification and additional area overhead. Oh et al. [17] also proposed CFCSS (Control Flow Checking by Software Signature), which monitors the control flow of programs by using assigned signatures in order to protect uncovered parts of EDDI (i.e., control flow violation). Moreover, Reis et al. [18] proposed SWIFT (SoftWare-Implemented Fault Tolerance), adding the optimization techniques to the combination of EDDI and CFCSS. The early stage of software-based duplication and checking techniques, such as EDDI, CFCSS, and SWIFT, can only detect transient faults. These in-thread instruction replication sachems incur massive overheads in terms of performance and power consumption even with several optimization schemes [19,20].
As instruction duplication and control flow checking can only detect soft errors, Reis et al. [21] proposed a software-based error correction technique, SWIFT-R (SWIFT-Recovery). SWIFT-R is a purely software-implemented TMR (triple modular redundancy) with majority voting before critical instructions (e.g., store and branch) and provides nearperfect fault coverage against soft errors. In order to protect only the vital and vulnerable parts of programs instead of all the instructions, Feng et al. [22] proposed a selective instruction duplication scheme by exploiting a vulnerability analysis. Khudia et al. [4] proposed an enhanced approach based on memory profiling in order to apply selective schemes on resource-constrained embedded systems. Profiling-based selective protection schemes provide fault coverage against soft errors comparable to complete instruction duplication, not considering profiling information at the compilation stage.
Software-based redundant multi-threading schemes [23][24][25] have been presented in order to mitigate the performance overheads from purely software-implemented protections. They execute the same operations on the leading and trailing threads and detect erroneous data by comparing results. However, they also suffer from performance overheads due to frequent synchronization and memory accesses [26,27]. In order to reduce the performance overheads from inter-thread synchronization, several optimization schemes have been presented for software-level redundant multi-threading schemes [26,27].
However, previous software-based techniques do not consider the characteristics of hardware architectures at all. They can be applied to any kind of processor, such as generalpurpose and special-purpose ones, but software-based techniques are not optimized for each hardware. Thus, the optimized protection techniques for special-purpose hardware, such as CGRA (Coarse-Grained Reconfigurable Architecture), VLIW (Very Long Instruction Words), and GPGPU (General-Purpose Computing on Graphics Processing Units), are required for emerging markets. In order to overcome the limitations of software-only approaches, techniques for minimal hardware modification with software protection have been presented. They can also perform complex design space exploration in terms of hardware area, costs, performance, power consumption, and reliability depending on the demand of each application.
The rest of the paper is organized as follows: First, Section 2 presents software-only protection techniques such as instruction duplication, control flow checking and softwareimplemented error correction schemes. Next, software-based protection techniques that consider hardware characteristics are summarized in Section 3. Finally, Sections 4 and 5 suggest future research directions of software-implemented fault-tolerant techniques and conclude this paper.
Purely Software-Implemented Fault-Tolerant Techniques
Oh et al. [16] proposed a simple software-based fault-tolerant technique, EDDI, to detect soft errors without additional hardware modification as described in Table 1. In EDDI, all the instructions are replicated and the comparison instructions are inserted during the compilation stage by using additional resources such as registers and memory. This simple idea can detect most soft errors without any hardware support, but it can incur severe performance overheads due to the expensive duplication and comparison processes. Therefore, in order to minimize performance overhead caused, by comparison, EDDI inserts the comparison instructions right before the store, branch, and jump instructions.
A basic block is defined as the portion of source code with only one entry point and one exit point, i.e., a branch-free sequence of instructions. A storeless basic block never contains the store operation except for the last operation of the basic block. The last operation of a storeless basic block can be a store, branch, or jump operation. In EDDI, the comparison instructions should be inserted just before the last operation of storeless basic blocks. For example, let us assume that the last operation of a storeless basic block is a store operation. Soft errors do not affect the final results unless corrupted data are stored in the memory by the last store operation; thus, the comparison instruction should be placed just before the store operation, rather than before all the instructions, to minimize the performance overhead. Figure 1b shows the example scenario of EDDI compared with an original code (Figure 1a). In the original code (Figure 1a), the first instruction (1: load r2, (r3)) is a load operation bringing data to r2 from memory address r3. The second instruction (2: add r1, r2, r3) stores the addition between the data stored in r2 and r3 to r1. The last instruction (3: store r1, (r3)) stores r1 data to memory address r3. As shown in Figure 1b, the fourth instruction (4: add r1', r2', r3') is the duplicate of the add instruction. The second instruction (2: load r2', (r3'+offset)) and the eighth instruction (8: store r1', (r3'+offset)) are duplicates of the load and store instruction. It is important to add an offset to the memory operation in order to store data in the memory separately. Moreover, the fifth instruction (5: bne r1, r1', gotoError) and the sixth instruction (6: bne r3, r3', gotoError) are comparison instructions before the store operation in order to detect soft errors. If the input registers (r1 and r3) of the store instruction are different from their copies (i.e., r1' r3'), EDDI can detect soft errors. The ratio of correct output is smaller than no protection due to tooconservative error detection Only detection, not correction SWIFT-R [21] Intertwining three copies of a program and adding majority voting before critical instructions Correcting soft errors, not just detecting them Performance overhead due to instruction triplication Shoestring [22] Symptom-based fault detection + software-based instruction duplication Low performance overhead by selective duplication Fault coverage of selective protection is not validated Profile-based solution [4] Value profiling for generating software symptoms Low performance overhead by selective duplication Memory profiling can be performed at the compilation stage Experiments were performed in an in-order processor, not in an out-of-order one Multi-core, multithread can change memory profiling methods Compared to the original instruction stream (three instructions), EDDI (eight instructions) requires five more instructions, including the duplicate and comparison instructions. Thus, it incurs significant overheads in terms of runtime and power. Moreover, EDDI duplicates all the memory instructions, which can incur severe performance overheads. Further, EDDI can only use half of the registers and memory as they need to hold the replicated data for comparison. However, duplicated instructions do not have to be followed by the very master instructions unless instruction scheduling affects the final results. Thus, the performance of instruction duplication can be improved by exploiting instruction-level parallelism. Furthermore, instruction duplication can detect most soft errors as it replicates all the instructions of a program. However, it cannot detect soft errors on the control flow of a program, e.g., EDDI cannot catch a branch incorrectly taken due to soft errors.
Oh et al. [17] proposed a signature monitoring technique, CFCSS, which monitors the control flow of a program using an assigned signature for uncovered parts of EDDI. In CFCSS, the signature is assigned to each basic block to detect soft errors in the control flow. Figure 2 shows an example of how CFCSS works without and with soft errors. V i , G i , S i , and D i are basic block identifier code, runtime signature, assigned signature for each basic block and pre-calculated difference, respectively. When a program is compiled, the unique signatures S i are assigned to basic blocks. The pre-calculated differences D i are also calculated using the XOR operation between connected basic blocks at the compilation stage. Finally, the runtime signature G i is calculated as the XOR result between the source signature and pre-calculated difference when a program runs. Let us assume that the original destination basic block from V 1 is V 2 if there is no soft error in the control flow. As shown in Figure 2a, the unique signature of the basic block V 1 , S 1 , is assigned to 0001, and the unique signature of the correct destination basic block (V 2 ), S 2 , is 0010. Thus, the pre-calculated difference D 2 at the compilation time is 0011, which is the XOR result between S 1 (0001) and S 2 (0010). Moreover, the assigned signatures S 3 and S 4 are 0100 and 1000, respectively. If the basic block V 4 comes from V 3 , the pre-calculated difference D 4 is 1100 (0100 XOR 1000). Thus, the runtime signature (G i ) and destination signature (S i ) should be always exactly the same if there is no soft error in the program flow as shown in Figure 2a.
Let us assume that the destination from V 1 is changed to the basic block V 4 by transient faults. The runtime signature of the basic block V 4 , G 4 , is calculated as 1101, which is the XOR result between S 1 (0001) and D 4 (1100). As G 4 (1101) is not the same as S 4 (1000), soft errors can be detected by the CFCSS mechanism, as shown in Figure 2b. The CFCSS does not need to modify hardware architectures to detect soft errors in the control flow, as software engineers can allocate unique signatures and runtime signatures to basic blocks by adding codes at the compilation time. However, control flow checking by code addition can incur significant performance overheads. Let us assume that the average number of instructions for each basic block is from 7 to 8 [28]. As we need to add signatures and comparison codes to detect soft errors, we need to add 1 or 2 instructions for every eight instructions at least.
Reis et al. [18] proposed SWIFT, which adds several optimization techniques in combination with EDDI [16] and CFCSS [17]. As the store operation is duplicated using memory offset in EDDI, EDDI can incur overheads in terms of power and performance due to the expensive memory operation. SWIFT eliminates the copy of the store operation shown in Figure Figure 1c, as the memory is protected by error correction codes or other protection techniques in common processors. Instruction duplication and signature-based control flow checking can detect almost 90% of soft errors without any hardware modification.
As SWIFT can only detect soft errors, Reis et al. [21] proposed a software-based recovery technique, SWIFT-R. SWIFT-R triplicates the instructions instead of duplication as in SWIFT. SWIFT only detects soft errors by comparison between the outputs of the original and duplicated instructions. If their results are different, soft errors can be detected. On the other hand, SWIFT-R can correct a soft error by majority voting, as shown in Figure 1d. Even though soft errors corrupt one module, the other two modules still have correct values. Thus, SWIFT-R can be used for safety-critical systems that need near-perfect reliability.
These instruction duplication schemes can protect hardware against soft errors in a simple manner. However, they incur colossal performance overhead as they do not prioritize basic blocks or instructions for duplication. In order to protect only safetycritical or vulnerable parts of applications, Feng et al. [22] proposed Shoestring, a selective instruction duplication scheme, by exploiting a vulnerability analysis. Shoestring has fault tolerance comparable to full instruction duplication, which does not consider profiling information at the compilation stage. Khudia et al. [4] proposed an enhanced Shoestring by adding memory profiling to apply resource-constrained embedded systems.
Software-Based Fault-Tolerant Techniques Considering Hardware
Purely software-implemented fault-tolerant techniques can protect hardware without considering hardware characteristics. First, pure software protection can incur severe performance overhead and miss vulnerable cases. In order to improve reliability with comparable area overheads, hybrid fault-tolerant techniques have been presented. Second, previous methods can be applicable regardless of processors, but they can be ineffective for special-purpose processors. In modern embedded systems, many kinds of co-processors, such as VLIW (Very Long Instruction Word) [29], CGRA (Coarse-Grained Reconfigurable Architectures) [30], and GPGPU (General-Purpose computing on Graphics Processing Units) [31], are exploited in order to maximize performance. Thus, optimized softwarebased approaches have been presented for special-purpose architectures.
Firstly, software-based techniques have been proposed with minimal hardware modification to effectively protect embedded systems against soft errors. Reis et al. [32] proposed CRAFT (CompileR-Assisted Fault Tolerance), which is composed of hybrid hardware/software redundancy techniques as shown in Figure 1d. In this technique, a checking store buffer (CSB) and a load value queue (LVQ) based on SWIFT are added to reduce the number of duplicated store and load instructions and enhance fault coverage; the CSB is a normal store buffer that validates store operations before commit entries. Thus, every store operation can be validated by comparing original stored data and replicated ones. Moreover, the LVQ performs a comparison between initially loaded data and duplicated loaded ones by using bypasses. Thus, hardware modification has less flexibility than a purely software-based approach, even though its performance is better than software-only fault-tolerant techniques. Therefore, the trade-off among area, reliability, performance, power, and flexibility to implement selective protections is more critical.
Secondly, protection techniques for special-purpose hardware, such as CGRA, VLIW, and GPGPU, are required. Special-purpose architectures accelerate the kernel parts of a program, e.g., simple loop repetition [33]. They can be used as co-processors or accelerators for maximization, and they are drawing significant attention in embedded systems such as signal processing and multimedia computing. However, research on unique architectures has focused on performance improvement, such as parallelization of computation [34] and scheduling algorithms [35], rather than on improving their reliability against soft errors.
As the usage of special-purpose processors is being broadened to critical applications, such as fiscal applications, weather forecasting systems, and ubiquitous medical systems, their reliability is becoming a crucial challenge [36]. Lee et al. [37] and Ko et al. [38] proposed an instruction duplication scheme by exploiting unused slots in VLIW and CGRA architectures with minimal hardware modification. However, they still induced performance overheads even though the purpose of the co-processor and accelerator was performance improvement. Thus, the trade-off relationship between performance and reliability in specific hardware is an essential concern.
Discussion
Based on our survey report, there is a necessity for validation of the fault coverage of software-based fault-tolerant techniques against soft errors. As described in Section 2, the duplication or triplication of all instructions without considering the priority of instructions incurs significant overheads in terms of performance and power consumption. Thus, several selective replications with profiling have been proposed in order to reduce performance overheads. Their performance is much better than full duplication as they just duplicate the subset of the full instructions of a program. However, the primary concern of selective protection is to guarantee fault coverage comparable to full protection.
The fault coverage of selective replication has been validated by statistical fault injection [39]. Statistical fault injection injects several faults into microarchitectural components and calculates the fault coverage based on the probabilistic theory. Statistical fault injection needs to inject a lower number of faults to achieve a given confidence and error interval than traditional exhaustive fault injection campaigns. In [22], a single bit-flip fault injection into the register file was implemented to validate their selective protection techniques. As soft errors in the register file can be propagated to other microarchitectural components frequently, fault injection into the register file can effectively show the fault coverage of the entire system. However, statistical fault injection (SFI) still has three main drawbacks, sampling, availability, and accuracy. For instance, single-bit flips on the register file can provide the fault coverage of the register file against single-bit soft errors. However, it cannot guarantee the fault coverage of other architectures against multi-bit soft errors. This is due to the fact statistical fault injection assumes that the fault model follows the normal distribution, but we cannot ensure whether it really does. Thus, SFI based on the probabilistic theory cannot show the exact fault coverage of selective protections. Moreover, statistical fault injection also has an availability problem as it requires a detailed register transfer level (RTL) model for more accurate modeling. Furthermore, it takes lots of time to inject faults even though RTL models become available. Lastly, SFI cannot provide precise fault coverage against soft errors as it is challenging to mimic realistic soft errors by intentional fault injection campaigns [40].
Therefore, the validation of software-based protection schemes has to choose between accuracy and performance. In order to select accurate fault coverage analysis, fault injection is not enough, as the soft error is caused by external radiation. Therefore, we have to exploit neutron or electron beam testing to analyze the soft error rate [41]. To the best of our knowledge, there are no research works to compare the fault coverage of various softwarelevel protection schemes. However, beam testing is challenging and time-consuming as it requires expensive equipment and repetitive experiments.
In order to estimate the fault coverage in an efficient manner, alternative fault coverage measurement or estimation will be required to overcome the limitations of conventional fault injection campaigns. Ko et al. [42] estimates the vulnerability of cache memory with and without protection schemes based on the microarchitectural behaviors in order to find better protections in terms of reliability and performance. However, there have been no research works to estimate the fault coverage of software-level schemes based on microarchitectural analysis to the best of our knowledge.
Conclusions
In this section, we conclude this paper and present the future research directions of software-based fault-tolerant techniques against soft errors. Soft errors, or transient faults, are becoming a significant design challenge with aggressive technology scaling. In order to eliminate area overheads from hardware-based fault-tolerant techniques, several software-based approaches have been proposed. In this paper, we have demonstrated the development of software-based fault-tolerant techniques against soft errors. In addition, instruction duplication and control flow checking by assigning signatures to basic blocks have been proposed. However, they suffer from performance overheads, as they duplicate all the instructions in a program. Thus, profiling-based selective protection techniques have been proposed to minimize overheads in terms of performance and power consumption.
These pure software schemes do not consider hardware characteristics such as target processors and hardware modification. Firstly, the performance of software-based techniques can be improved by minimal hardware modification, such as using additional memory buffers. Secondly, these techniques can enhance the reliability against soft errors regardless of processors, but they are not optimized for special-purpose processors such as VLIW, CGRA, and GPGPU. Thus, optimized software-based techniques for specialpurpose processors have been proposed, e.g., instruction duplication using NOPs on VLIW architectures. Thus, system designers can maximize the effectiveness of software-based fault-tolerant techniques by considering hardware matters. | 5,479.6 | 2022-02-03T00:00:00.000 | [
"Computer Science",
"Engineering"
] |
The blast relief sandwich panel fixing under the explosion energy action
. This article is devoted to the assessment of the efficiency of using wall sandwich panels with mineral wool core, sheathing made of galvanized steel with a polymer coating, used as blast-relief panels. The article presents the developed seating unit for the wall sandwich panel at the moment of the explosion energy influence. As a result of the experiments carried out, when an excess pressure of no more than 3.0 kPa in the room is reached, the safety shut-off devices ensure the discharge of the displaced element, which avoids damage to the main elements of the frame. According to the results of 2 tests, the actual value of the overpressure for opening the displaced element is 2.7 kPa, which allows the discharge of the displaced element to be ensured. In the course of the study, the expediency of using blast-relief panels(BRP) in the form of wall sandwich panels was substantiated, and this technical solution was implemented at the facility with the possibility of a deflagration explosion
Introduction
At present, the requirements for ensuring resistance against explosions, for the explosion safety of existing and explosive transport, energy and industrial facilities are significantly tightened. This happened due to the need to ensure an increased level of safety at industrialhazardous facilities to service personnel and technological equipment in case of emergency.
Oil refining facilities and facilities used in the production of explosive substances, chemicals, pipelines, gas stations, thermal power plants, boiler houses, workshops for the preparation and transportation of coal dust, are classified as explosive.
The relevance of the research topic is ensured due to the emerging emergency explosions of gas-air, steam-air, dust-air mixtures at industrial explosive objects for various purposes, as a result of which human casualties and material damage occur.
At the moment, the problem of uncontrolled combustion of gas-air, steam-air, dust-air mixtures is given considerable attention worldwide due to its relevance, since it is associated with great material damage and leads to human casualties.
Analysis of accidents in buildings at explosive industries showed that glazing is an effective anti-explosive device. However, in some cases, during explosions inside the premises, despite the fulfilment of regulatory requirements, the destruction of the main structures, particularly the wall fence, occurred. In addition to the destruction of the glazing, there is a complete and partial separation of the sashes from the window spans, and an example is shown in Figure 1. For the development of design solutions for the protection of buildings from explosions, it is first necessary to assess the explosiveness of a specific production process located in the building to further establish the magnitude and nature of the loads acting on the enclosing structures when using specific elements of blast-relief panels.
This indicates a need for further development of methods to ensure against explosion resistance of premises, based on the use of blast-relief panels.
To date, the reasons that led to the explosion of combustible mixtures inside the building have been analyzed. Methods for determining the explosive loads perceived by the enclosing structures during an explosion have been developed. A method for establishing the required area of safety structures and an installation method for explosive buildings have been developed. A review of domestic regulatory literature showed the absence of documents that would allow for the calculation of sandwich panels. The only exceptions are recommendations [1], which are optional. They do not take into account all variants of fracture mechanisms, particularly, shear fracture, compression of the middle layer, shear strength under long-term loading. [2,4,12,13] However, in the scientific literature, one can find works devoted to the search for an optimal calculation method for both a sandwich panel and the nodes of their interface with other structural elements. For example, O.A. Tusnina described in her works [5,6,7] the method of calculating the conjugation of a Z-shaped run with a sandwich panel. Mircea Georgescu [8] and Marcin Kujawa [9] are doing the same research on this issue. Kahina Sad Saoud [10,11] solves the problem of loss of stability in compressed skins.
Baryshev G.K. [14] devotes a new general experimental method for studying the anisotropy of conducting materials of various functional purposes. The difference between the presented method and the previously known one is in the high rate of anisotropy assessment, ensuring the possibility of anisotropy assessment of the properties of materials by the volume of the sample or product under investigation during their manufacture or operation. The procedure for measuring the anisotropy of electrophysical properties and the results of the study of some samples are presented.
Vedishcheva I.S. [15] presents numerical research results to the influence of heat conducting inclusions on thermo-technical properties of vertical and horizontal sandwich panels. The numerical analysis is carried out using software ANSYS. Based on the numerical analysis results, the regression equations for calculating minimal values of temperature on an internal surface of a vertical sandwich panel are easy to obtain. The analysis of the thermal field of the "sandwich panel -metal frame" [16][17][18] system shown that the hygiene requirements do not comply. The proposed solution allows the reduction of the influence of heat conducting inclusions on thermo-technical properties.
Premises of categories A and B for explosion and fire hazard, by the set of rules SP 4.13130.2013 "Limiting the spread of fire on protection objects", should be equipped with external blast-relief panels (BRP).
According to the Recommendations for the calculation of parameters of easily resettable structures for explosive and fire hazardous premises of industrial facilities. VNIIPO, 2015 wall panels can be used as displaced BRP.
Blast-relief displaceable panels based on three-layer wall panels for civil and industrial buildings (hereinafter -BRPP, blast-relief panels based on three-layer wall panels), performing the function of anti-explosion safety structures, designed to reduce the excess pressure arising from internal explosions of steam-gas-dust-air combustible mixtures in buildings and structures.
The principle of operation of the BRPP is as follows -when the overpressure from the explosion is applied to the enclosing structures, the safety shut-off devices that secure the BRP panels are destroyed, they are displaced outside the building, and the pressure is released. The panels are protected from scattering by safety cables, by which they are fixed to supporting structures. Each BRP panel is attached to the supporting structures with at least two safety cables. Blast-relief panels are designed for response pressure depending on the category of the room, as well as wind and operational loads.
For industrial buildings, following SP 56.13330.2011 «Industrial buildings», the area of blast-relief panels should be determined by calculation. In the absence of design data, the area of blast-relief panels should be at least 0.05 2 per 1 3 of the volume of a room of category A and at least 0.03 2 for rooms of category B.
The actuation pressure should be in the range of 2.0 to 3.85 kPa and not less than 3.5 wind pressure plus the pressure required to displace the BRP. Each BRP panel must be fixed with at least four safety locking devices (SLD). The operating load of the SLD is selected individually for each project and is in the range of 0.5-2.0 kN.
The object of the research is the seating units of blast-relief panels made of sandwich panels.
The subject is the destruction of units from the impact on the wall sandwich panel of the force of the overpressure of the explosion with its displacement outward without using an additional source of energy.
The aim of the work is to develop and justify the attachment points for wall sandwich panels under the influence of air-gas mixtures.
The following tasks were solved: 1. development of assemblies for easily dumped structures made of sandwich panels under the influence of explosion energy; 2. testing with a wall sandwich panel under the influence of explosion energy; 3. implementation of the proposed technical solution at the facility with the possibility of a deflagration explosion.
Materials and Methods
The panel was manufactured on 03/06/2019 on an automatic flow line with dimensions of 1550 • 1200 mm with a mineral wool core with a thickness of 200 mm, with a sheathing of galvanized steel with a Polyester polymer coating. Fig. 3. The safety substructure Figure 3 also shows the safety substructure, the components of which are a reinforcing sleeve, a bracket, a safety cable, a 5.5 • 32 self-tapping screw, an easy-to-release sandwich panel, a reinforcing washer, an M8 washer, a grover washer, an M8 nut and an M8 threaded stud with a length corresponding for the thickness of the sandwich panel.
The test specimen is a displaceable BRP in the form of a three-layer wall metal panel with dimensions (1550 • 1200) mm filled with mineral wool 200 mm thick (Figure 4), installed in the discharge opening, fixed to the opening with the help of safety locking devices, manufactured according to TU 25.11.23-004-65536585-2019 «Structures (curtain walls) made of three-layer metal panels with mineral wool insulation». According to the requirements of MI-001.01.06.2017 "Test procedure for blast-relief panels " [18], two BRP samples were tested.
The general view of the structure is shown in the figure 4. The principle of operation of this BRP is based on the destruction of nodes from the impact on the wall panel of the force of the overpressure of the explosion with its displacement outward without using an additional source of energy. The test of the presented sample was carried out under the following environmental parameters: ambient temperature -6.0℃; atmospheric pressure -100.2 kПа; relative humidity -59 %.
After mounting the sample, the amount of combustible gas required to create a stoichiometric concentration was supplied to the explosion chamber. Concentration control was carried out using a gas analyzer. After the formation of the required concentration of the gas-air mixture in the explosion chamber, the gas supply was stopped.
No later than 30 s. after stopping the gas supply, the gas-air mixture was ignited. During the test, following the requirements of clause 7.5 of GOST R 56289-2014 [19], the following were registered: change of overpressure in time inside the explosion chamber using overpressure sensors; the process of releasing the discharge hole of the explosive chamber from the displaceable element of the BRP; the nature of the destruction of the sample. Following the requirements of clause 7.6 of GOST R 56289-2014 [19], the procedure for determining the overpressure for opening the BRP: analysis of video footage of the high-speed shooting, which determines the time elapsed from the moment of ignition of the gas-air mixture inside the explosion chamber to the beginning of opening the discharge opening analysis of the graph showing the dependence of overpressure on time inside the explosion chamber, according to which the overpressure of opening the BRP is determined, corresponding to the start time of opening the relief opening, set by video footage.
Testing of samples of displaceable BRPs made of sandwich panels with a safety shut-off device of the SLD type, manufactured following TU 25.11.23-004-65536585-2019 «Structures (curtain walls) made of three-layer metal panels with mineral wool insulation», confirms the possibility of clearing the outlet opening of the building as a result of excessive pressure due to internal deflagration explosion of the gas-air mixture.
Safety shut-off devices must ensure the discharge of the displaced element, which will avoid damage to the main elements of the frame when an overpressure of no more than 3.0 kPa in the room is reached. According to the results of 2 tests, the actual value of the overpressure for opening the displaced element is -∆ . = 2.7 kPa, which allows the discharge of the displaced element to be ensured.
Results
Testing of samples of displaceable easily ejected structures made of sandwich panels with a safety shut-off device of the SLD type, manufactured following TU 25.11.23-004-65536585-2019 «Structures (curtain walls) made of three-layer metal panels with mineral wool insulation», confirms the possibility of clearing the discharge opening of a building as a result of exposure to excess pressure due to an internal deflagration explosion of a gas vapor-air mixture.
The test results are shown in Table 1. Blast relief panels must have safety locking devices in the form of latches, destructible fastening elements or other structures that release the swing leaf or a displaced element when it is subjected to excessive pressure of a certain value. Safety shut-off devices must ensure the discharge of the displaced element, which will avoid damage to the main elements of the frame when an overpressure of no more than 3.0 kPa in the room is reached. According to the results of 2 tests, the actual value of the overpressure for opening the displaced element is -∆ . = 2.7 kPa, which allows the discharge of the displaced element to be ensured.
Discussions
The resettable BRP of explosive rooms is known according to patent № 119780 dated 04/27/2012, publ. 27.08.2012 (author-holder VL Stilba, class MPKE04N9 / 00). This resettable BRP for explosive areas contains a wall panel, a resettable blast relief sandwich panel connected to the building frame using support brackets made of a corner metal profile through destructible attachment points. Each bracket has a groove in the places where the parts of the destructible seating unit are installed.
Each destructible seating unit contains a base sleeve, which is located inside the hole of a blast relief sandwich panel, and a destructible attachment element connected to the base sleeve using a pin and a spacer sleeve mounted on the said pin. The spacer sleeve is made with an annular protrusion and is installed with the possibility of excluding the occurrence of contact between the stud and the bracket, the spacer sleeves are made of caprolon, and fluoroplastic discs with a calibrated thickness are used as destructible elements, fixed on the studs by means of a threaded connection.
The technical result provided by this utility model under US Pat. No. 119780, consists of increasing the structure's efficiency as a whole with different pressure fluctuations inside the room, the reliability of the structure at normal pressure, and improving the performance. The disadvantage of this technical solution is as follows. The technical solution lies in the fact that a special support bracket made of a corner metal profile is attached to the building frame, to which the sandwich panel is attached by means of a destructible seating unit. To do this, it is necessary to drill holes in the sandwich panel for the grooves on this bracket, and this does not happen in the factory but directly during the installation of the panel at the construction site so that the holes in the panel coincide with the grooves of the bracket previously fixed on the building frame. To do this, the sandwich panel should be lifted to the appropriate floor, the holes should be marked for the corresponding grooves, then the panel must be lowered, after the corresponding holes need to be drilled, and after the panel raised again for fastening. That means that the process of mounting the panel is complicated. Also, for the installation of such a structure, two workers are required -from the outside of the panel and the inside, since the destructible fastener is fixed simultaneously both from the outside with the appropriate fastener and from the inside by the destructible unit onto the support bracket. Also, the destructible attachment point of this design, consisting of a destructible element, a spacer sleeve and a stud, must be mounted inside the support bracket, which is a metal trihedron, which significantly complicates the installation process, since it is possible to get to the place of attachment inside such a bracket is difficult enough.
Conclusions
The study results contribute to the existing knowledge of the efficiency of using wall sandwich panels with mineral wool core, sheathing made of galvanized steel with a Polyester polymer coating, used as blast-relief panels.
The main results are: safety shut-off devices, when an overpressure of no more than 3.0 kPa in the room is reached, must ensure the discharge of the displaced element, which will avoid damage to the main elements of the frame; according to the results of 2 tests, the actual value of the overpressure for opening the displaced element is -∆ . = 2.7 kPa, which allows the discharge of the displaced element to be ensured. | 3,801 | 2021-01-01T00:00:00.000 | [
"Engineering",
"Materials Science"
] |
Experimental Study on Vortex-Induced Vibration Coupling Wake Interference of Multi-Riser Groups with Sensitive Spacing
The “riser group—fluid between risers” is taken as the carrier, and the experiment on vortex-induced vibration of tandem riser groups coupling interference effect under sensitive spacing is performed. The least-square method is used to linearly fit the reduced velocity and main frequency, and the rule of Strouhal numbers is analyzed. Each mode is separated based on the mode decomposition theory, and the mode conversion mechanism is also explored. The concept of “interference efficiency” is introduced to study the dynamic characteristics and response evolutions of different riser groups. The results show that the wake shielding effect widely exists in tandem riser groups, and the interference effect of midstream and downstream risers on their upstream risers is significantly lower than that of upstream risers on midstream and downstream risers. The trajectories of midstream and downstream risers lag behind their upstream risers due to multiple shadowing effects, the vibration frequency range of downstream riser is widened and the dominant frequency is extremely unstable. Compared with the isolated riser, wake interference suppresses the vibration displacement of the midstream and downstream risers in the in-line direction, and enhances the displacement of upstream and midstream risers in the cross-flow direction. The interference effect of the fluid between risers at low velocities is stronger than that at higher velocities, and the cross-flow displacements of upstream risers are always in the interference enhancement region. It is urgent to pay attention to the cross-flow displacement of upstream and midstream risers in tandem riser groups considering the safety design.
Introduction
Complex fluid-structure occurs in marine risers under waves and currents. The instability of the structure produces severe vibrations and accelerates fatigue damage, endangering the service life of the riser (Guo and Lou, 2008). A large number of researchers have described the vortex-induced vibration (VIV) of the isolated riser. However, marine risers are not arranged only in isolation, but also in a variety of layout forms, such as, "string", "column" and "group". The wake of the riser acts on the other one which causes the flow separation and vortex shedding when outflow goes through the riser group so that the vibration pattern and dynamic responses become different from those of general VIV, which is called "wake-induced vibration (WIV)" (Huera-Huarte and Gharib, 2011a). Risers in the riser group system are coupled to each other due to the influence of wake and gap flow, and the dynamic responses of VIV are superimposed (He and Low, 2014;Xu et al., 2018a).
At present, the wake interference effect is studied based on numerical simulation, experimental research and empirical model. For the interference of tandem double risers, Mysa et al. (2016) studied the coupled dynamics mechanism of an isolated cylinder and a pair of tandem rigid cylinders; Derakhshandeh et al. (2014) compared the efficiency of VIV power obtained by downstream cylinders with different arrangements; Tu et al. (2015) studied the fluid-induced vibration of tandem cylinders with spacings of 2.5D−8D under the action of plane shear flow based on the finite element method; Zhao et al. (2016) studied the vibration on small cylinders caused by the large cylindrical wake with different cylindrical ratios; Lin et al. (2013) analyzed the vibration displacement, frequency and relative equilibrium position of tandem cylinders; Chung (2017) studied the vibration characteristics of a rigid cylinder and found the trajectory "8" existed only in tandem.
Researchers have conducted experimental studies based on the simplest arrangement of the riser groups. Among them, Assi et al. (2006) carried out two cylinders' interference tests with spacings of 2D−5.6D based on flow visualization technology, and observed a significant "galloping" phenomenon; Huera-Huarte and Gharib (2011b) studied the dynamic responses of two cylinders in a side-by-side arrangement with the spacings of 2D−5D under the low mode, and they analyzed the dynamic responses of two tandem risers with spacings of 4D−8D which immersed in a uniform flow partially. Particle image velocimetry (PIV) was used to visualize the wake for tandem cylinders with spacings of 2D−4D, and different response mechanisms were determined by Huera-Huarte et al. (2016): VIV, WIV, and a combination of both. Armin et al. (2018) established the optimal distance between two offshore structures by an experimental investigation on VIV of two rigid cylinders in tandem. Xu et al. performed flow-induced vibration (FIV) tests on two kinds of double flexible long cylinders for spacings of 4D−16D in tandem (Xu et al., 2018b) and sideby-side cylinders with spacings of 3D−8D (Xu et al., 2018c). They focused on FIV of the two systems from the strain, displacement, main frequency and the average drag coefficient. Besides, Xu et al. (2019) analyzed the fluid forces of the cylinder in tandem arrangement to illustrate the mechanism of interaction, and a series of experimental tests were carried out to investigate the FIV of two side-by-side flexible cylinders with a high aspect ratio (Han et al., 2018). Huang and Herfjord (2013) found that the upstream cylinder was less affected by the downstream cylinder when the spacing was larger than 3D. Exploring complex cylinder group systems is the research hotspot in recent years. Chen et al. (2018) studied the relaxation of VIV of a three-cylinder-system in tandem at low Reynolds numbers; Ding et al. (2015) simulated the VIV of 1, 2, 3, and 4 cylinders in tandem under uniform flow; Zhang et al. (2018) conducted a numerical simulation of four staggered cylinders and found that the interference effect of tandem cylinders was greater than that of side-by-side arrangement. Furthermore, Gao et al. (2019) found that the incident angle had a significant influence on the downstream cylinder.
Researchers have extensively discussed the basic arrangement-double risers, but the FIV of more than two risers is limited. Since multi-riser structures are commonly adopted in engineering, the fluid-structure coupling mechanism between risers is relatively complex, and studies show that it is inappropriate to infer the FIV behavior of riser groups from dynamic responses of the two-riser group (Wang et al., 2019). FIV and fatigue failure are prone to happen in multiple riser groups arranged in tandem, and collision may occur due to wake interaction. The interference spacings between 3.5D and 4.5D are more sensitive for the riser group (Armin et al., 2018;Assi et al., 2010), and investigation of the VIV test and vibration mechanism for riser groups at sensitive spacing is unprecedented. Therefore, the dynamic characteristics and responses of several riser groups under sensitive spacing by changing the flow velocity and the number of risers are explored in this paper.
Experimental facility
The experiment was carried out in the wave-current combined flume in the Engineering Hydrodynamics Laboratory of Ocean University of China. The water flume is with a maximum flow velocity of 1 m/s and a maximum water depth of 1.0 m. The water depth was 0.8 m, the velocity interval was 0.05−1 m/s, and the flow velocity changed from 0.1 m/s to 0.6 m/s. The experimental facility was placed in the water flume at a distance of 22 m from the flow generating system to ensure uniform flow. The experimental facility comprised supports, a top tension system, riser models, signal measurement and acquisition system, etc, and it is shown in Fig. 1.
Design of riser models
Transparent polymethyl methacrylate pipes with the wall thickness being 1 mm were selected as the riser models, and a high degree of consistency in the mechanical properties of the polymethyl methacrylate pipes are required. A vertical posture was adopted and 40% of the length was immersed in the uniform flow field (Huera-Huarte and Bearman, 2009). Through multiple free decay tests in still water, we obtained the normalized damping ratio ζ, as well as the riser' s natural frequency in the water f 1 , and the main parameters are shown in Table 1.
Arrangement of sensors
The Doppler current profiler was placed at 2.0 m upstream of the riser to avoid the influence of the vortex caused by it. The top tension system was formed by the force applying device, fixed pulley, steel wire rope, force guiding rods, fixing plate, and the AXT-S-100 external digital tension meter. The same top tension was adopted for each riser with a sensitivity between 1.5 and 3.0 mV/V. Fiber Bragg grating (FBG) sensors were used, and six grating measuring points were engraved on each string of optical fibers according to the preliminary estimation of the number of high-order modes excited by the riser. Measuring points were arranged at 90° (CF 1 , IL 1 , CF 2 , IL 2 ) on the surface of the riser, and CF 1 , CF 2 and IL 1 , IL 2 were on opposite sides to measure the vibration of the riser along the CF and IL direction respectively. There were four strings of optical fiber and each riser model was placed with 24 measuring points, and from top to bottom are G1−G6, as shown in Fig. 2.
Design of experimental cases
The isolated riser tests under different velocities and top tensions were carried out before the experiment. The dynamic response of the riser predicted by the numerical model was compared with the experimental results, and vibration responses of the isolated riser under different parameters were studied (Wang et al., 2021), and the dynamic responses of experimental and numerical results agreed well, which verifies the feasibility of the experiment process control system and accuracy of the test.
Afterward, two, three, and five plexiglass risers with the same mechanical properties were used in riser groups. All risers were arranged in tandem at spacings of 4D. Risers are identified as Risers #2-1 and #2-2 in the two-riser group; Risers #3-1, #3-2 and #3-3 in the three-riser group; Riser #5-1, Riser #5-2, Riser #5-3, Riser #5-4 and Riser #5-5 in the five-riser group from upstream to downstream, and the isolated riser is identified as IR, as shown in Fig. 3c. The specific experimental layout is shown in Fig. 3 and experimental cases are shown in Table 2.
Frequency analysis
It is usually dominated by a frequency when a structure vibrates, and the dominant frequency can reflect the main vibration characteristics. Fig. 4 shows the dimensionless dominant frequencies (f dy /f 1 , f dx /f 1 ) of the isolated riser versus reduced velocity, where f dy and f dx are the dominant frequencies in the CF and IL directions. The representative values of Strouhal number of the isolated riser in CF and IL directions are 0.185 and 0.370, which is consistent with previous research findings (Chen et al., 2018;Ding et al., 2015;Zhang et al., 2018). Figs. 5−7 show variations of dimensionless dominant frequencies of two-, three-and five-riser groups versus reduced velocity, Strauhal numbers (St) are fitted, and ratios of IL and CF dominant frequencies are given. It is known that the isolated riser's St is 0.185, the dominant frequency variation trend of Riser #2-1 in the tworiser system (Fig. 5) is similar to that of the isolated riser, and St is larger than that of Riser #2-2, with St 2-1 =0.161 and St 2-2 =0.143. The dominant frequency of Riser #2-1 is the same as that of Riser #2-2 when reduced velocity U r ≤8.42, but the dominant frequency of Riser #2-2 decreases abruptly when U r =9.26, which is caused by the sudden strengthening of the influence of wake shielding effect on the vibration frequency of the structure when the incoming flow velocity increases to a certain value. In addition, the dominant frequency ratio of Riser #2-2 of IL and CF directions is unstable, whereas the dominant frequency ratio of Riser #2-1 is the same as that of the isolated riser, with small fluctuations around 2.
In the three-riser system (Fig. 6), the dominant frequency quencies of Risers #3-1, #3-2 and #3-2 are the same when U r ≤6.73, but when U r =7.58, the dominant frequencies of Riser #3-3 first drop suddenly, and then the dominant frequencies of Riser #3-2 also drop. The dominant frequencies of IL and CF in Risers #3-2 and #3-3 are similar, and the ratios fluctuated around f dx /f dy =1. The "beat phenomena" occurred in the downstream risers, and wake interference is particularly critical for downstream riser vibration, especially at high flow velocities in riser groups. Downstream risers vibrate in a low mode due to the multiple fluids and the strong shielding effect of the upstream riser on downstream risers (Xu et al., 2021a). The dispersion of vibration frequency is large, and the corresponding frequency energy participation increases. As a result, energy transfer occurs in the crossflow and in-line directions, which further leads to the occurrence of "frequency overlap" (Tang, 2011).
In the five-riser system (Fig. 7), the trend of the dominant frequency of Riser #5-1 is similar to that of the isolated riser. St corresponding to the riser from the upstream to the downstream decreases first then increases, and the intermediate riser is the smallest, with values: St 5-1 =0.175, St 5-2 =0.167, St 5-3 =0.140, St 5-4 =0.147, St 5-5 =0.167. The dominant frequencies of Risers #5-4 and #5-5 are different from those of other riser groups when U r =5.89. The dimensionless dominant frequency rises sharply, and the dominant frequency is restored when U r =8.42, U r =9.26, respectively. Analysis shows that the dominant frequency ratios of Risers #5-1 and #5-2 are similar to those of the isolated riser. The dominant frequency ratios of Risers #5-3 and #5-4 are close to 2:1 in U r =[3.36, 5.05]. The dominant frequency ratio is generally smaller than f dx /f dy =1, that is, the dominant frequency in the CF direction is larger than that in the IL direction at some velocities. And this characteristic is the most evident for Riser #5-5, where the dominant frequency is extremely unstable.
To further investigate the frequency responses of the multi-riser group, Fig. 8 shows the power spectral density of the five-riser group at the measuring point G4 versus reduced velocity. At the same time, Fig. 9 shows time-frequency (G4) in the CF direction. The dominant frequency of the five-riser group decreases from upstream to downstream. The vibration of the upstream and midstream risers increased interference to the downstream risers, destroying the formation and separation of the wake vortex, and multiple interference frequencies are superimposed on the midstream and downstream risers, so that the vibration frequency distribution area becomes wider, and this feature is particularly prominent in the IL direction. In the CF direction, the frequency response weakens from upstream to downstream, and as the flow velocity increases, the dominant frequencies of the midstream and downstream risers appear in sequence. Fig. 10 summarizes St and gives the root mean square. The trends of St are different. The two-and three-riser groups are all in a downward trend, which fully shows that the upstream riser wake has a significant wake shielding effect on the downstream riser, and the vortex of the upstream riser falls off on the downstream riser, which changes the vortex shedding direction and significantly inhibits the VIV frequency of the downstream riser. The dominant frequency and trend of Riser #1 are the closest to those of the isolated riser, but they are both lower than those of the isolated riser. There is an interference feedback effect, which suppresses the frequency of the upstream riser, but its influence is significantly smaller than the wake shielding effect of the upstream riser on the midstream and downstream risers. In the tandem riser group, the vibration of the downstream riser is the superposition of the WIV of the upstream riser and its own VIV, and this is not a simple linear superposition. An interesting phenomenon occurs in the five-riser group: St 5-5 is higher than those of the midstream risers. This is because the shear layers reattachment happens as Riser #5-5 is placed sufficiently far from the first one (Xu et al., 2021b). The reattachment of the shear layer leads to the increase of Riser #5-5's frequency response. In the five-riser group, multiple superimposed wake vortices act on the midand downstream risers, causing vibration modes to change, in particular, the response of the downstream risers can no longer be predicted by VIV rule.
Displacements versus reduced velocity
Figs. 11−13 show dimensionless displacement amplitudes versus the reduced velocity of riser groups at z=0.425L. For the two-riser group, in the CF direction, the dimensionless displacement of the two-riser group exceeds that of the isolated riser at most reduced velocities, and the wake interference and its feedback effect both cause the increase of the CF displacement; IL displacements of the upstream Riser #2-1 exceed that of the downstream Riser #2-2 except for the case of U r =3.36, but the wake shielding effect becomes stronger as the reduced velocity increases. The displacement amplitude is suppressed compared with the isolated riser. For the three-riser group, the dimensionless displacements of Risers #3-1 and #3-2 both exceed that of the isolated riser, and the displacement and variation trend of Riser #3-1 are similar to those of the isolated riser. Risers #3-2 and #3-3 have sudden rise and fall when U r =5.89−8.42, but the two are completely different: the WIV of Riser #3-1 and the wake interference feedback effect of Riser #3-3 both act on the midstream Riser #3-2, and it is positively superimposed with its own VIV effect, which is intuitively manifested in the riser displacement response. The dimensionless displacement amplitude of midstream Riser #3-2 fluctuates up and down around 0.8 when U r >6.73, which completely exceeds the displacement amplitude of the isolated riser, and it is comparable to the upstream Riser #3-1. The downstream Riser #3-3 has a sharp drop in amplitude, which is lower than that of the isolated riser, and the amplitude is WANG Yu et al. China Ocean Eng., 2022, Vol. 36, No. 3, P. 333-347 339 lower than that of the upstream Riser #3-1 and midstream Riser #3-2, which is due to the wake of the upstream Riser #3-1 and midstream Riser #3-2, and VIV of Riser #3-3 itself, and the effect is reversely superimposed, resulting in the opposite phenomenon to the midstream Riser #3-2. For the five-riser group, the displacement variation trends are the same in two directions, and the root mean square displacement of the riser from upstream to downstream decreases sequentially, and at the higher reduced velocity, the displacements of midstream Risers #5-2 and #5-3 are very close. In the CF direction, only the upstream Riser #5-1 exceeds the displacement of the isolated riser, which is quite different from other groups. In the IL direction, it is similar to the two-and three-riser groups, the amplitudes of Risers #5-2, #5-3, #5-4, and #5-5 are all smaller than that of Riser #5-1 due to the wake shielding effect. The vibration displacements of the midstream and downstream risers are suppressed compared with those of the isolated riser.
The root mean square of the displacements along with the reduced velocity of the isolated riser, two-, three-and five-riser groups are summarized in Fig. 14. From upstream to downstream, the vortex of the upstream riser falls on its downstream riser, which changes the direction of vortex shedding. The root mean square displacements of the threeriser group in both directions show a downward trend, meaning that the amplitude suppression of the downstream riser is significant due to the wake shielding effect. The wake interference effect has different influences on the displacement of the tandem-arranged riser group in the CF and IL directions. In the IL direction, the VIV displacements of the midstream and downstream risers are suppressed; in the CF direction, the vibration amplitude of the two-riser group and the upstream and midstream risers are all promoted.
Displacements along the axial direction
Figs. 15−17 show the dimensionless displacement responses from upstream to downstream of the two-, three-, five-riser groups in the CF direction at U r =8.42, respectively. It is observed that the first and second mode dimensionless displacement weights of risers are reduced respectively in the three riser groups. Values and variations of displacements along the axial direction of the upstream Risers #2-1 and #3-1 are considerably varied, among which displacements of the middle four measuring points are much larger and the amplitude is closer to each other. This corresponds to the significant second mode phenomenon from the envelope diagrams of the displacement. At the same time, the displacement-time curves of the three measuring points that far from the water surface in Risers #2-1, #3-1 and #5-1 show different degrees of "double-peak" morphology, which is due to the transition of the first mode to the second. However, displacements of the middle two measuring points in Risers #3-2 and #3-3 are larger than those of the other measuring points. The first mode is mainly observed, and there are only a few second-mode on the displacement envelope diagrams. In the previous section, it has been found that the wake interference makes the dominant frequencies of Risers #3-2 and #3-3 unobvious. The complex vibration frequencies cause amplitudes of Risers #3-2 and #3-3 to be no longer single and displacement-time curves to appear several peaks, but they still exhibit regular vibrations with clear cycles.
In the five-riser group, all the risers show that the first mode dominants vibration at U r =8.42, and the second modes of Risers #5-1, #5-2 and #5-3 can be observed in the envelope diagrams. The first mode gradually decreases from upstream to downstream, the same as that of the second mode. The first-order mode weight of the downstream riser decreases the most dramatically, and the displacement is much smaller than that of the upstream riser. Similarly, the "double peak" shape in the displacement-time curve of the upstream riser is not as regular as the upstream riser of the two-, three-riser groups. The waveforms of the midstream riser and downstream riser begin to become irregular but still present in a periodic manner, and mutual interference factors increase as the number of risers increases. Riser #5-3 is interfered by the wake of two upstream risers and also fed back by its two downstream risers. The displacements of Riser #5-3 exceed that of Riser #5-2, and the shape variation of Riser #5-3 is different from that of others. The displacement of Riser #5-1 at z=0.425L becomes smaller, while the displacement amplitude of the riser under the water surface is larger. Because the position of larger amplitude is close to the dominant mode center, and the position of smaller amplitude corresponds to the intersection of adjacent mode. The velocity through the downstream riser is reduced due to the wake shielding effect, in turn leading to a decrease in the displacement amplitude of the downstream riser. Whereas the magnitude of the decrease is not linear, and the downstream riser is reduced much more than the midstream riser. Figs. 18 and 19 show the displacement response of the five-riser group at U r =10.10, which shows obvious standing waves in the CF direction caused by the dominant characteristics of VIV single-mode. The difference is that Riser #5-1 shows a slight characteristic of transformation from standing wave to traveling wave, and there is a certain trend of mode transformation in Risers #5-2 and #5-3, showing the charac-teristic of the gradual evolution from standing wave to traveling wave (Ma et al., 2019), as shown in Fig. 18. Downstream risers show strong standing wave characteristics, and the vibration intensity of Riser #5-5 is relatively weak compared with others. In the IL direction, Riser #5-1 is in the process of intense mode transformation, and so is Riser #5-2, but its intensity is weaker than that of Riser #5-1. Moreover, as the traveling wave direction is always from the power input to the power output area, it can be understood that the riser vibration is transmitted from high energy area to the low. The actual velocity near downstream decreases obviously due to the repeated interference of shielding effect, and all show standing wave characteristics. Fig. 20 shows displacement trajectories versus the WANG Yu et al. China Ocean Eng., 2022, Vol. 36, No. 3, P. 333-347 343 reduced velocity of the isolated riser and riser groups. All risers have small displacement trajectories at low velocities. The trajectories of the upstream riser in two-and three-riser groups at U r =3.36 first appear as "8-shaped", and the trajectories deviate from the original shape to present "lip-shaped" and "crescent-shaped" when the reduced velocity increases. The two lobes of trajectories point to the downstream at U r ≥ 6.73, and the feature is particularly prominent in the range of 4.20<U r <7.58. Risers have less reaction to the upstream riser, so the upstream riser vibration trajectory is similar to that of the isolated riser, together with a relatively regular motion trajectory. The "8-shaped" trajectories can be observed in Riser #3-2 at 3.36<U r <5.89. For the five-riser group, only the upstream riser presents a regular "8-shape" at U r =6.73 and 7.58. After U r >8.42, the "8-shape" of the upstream riser in the five-riser group deviates from the standard shape, which is different from the isolated riser and upstream riser in other riser groups. From Fig. 20, the vibration amplitudes between adjacent risers are significantly different in the five-riser group, which is consistent with the results of the displacement response. In addition, the vibration trajectory amplitudes of downstream risers (#5-2, #5-3, #5-4, #5-5) always lag behind its upstream adjacent riser in the five-riser group except for the upstream Riser #5-1.
Interference efficiency
The concept of "interference efficiency" (η) (Liu et al., 2020) is introduced to further quantify the adjacent interference, which is defined as the ratio of the difference between RMS displacement of riser group and the isolated riser to RMS displacement of the isolated riser. Figs. 21−23 show the interference efficiency, in which η>0 indicates that the displacement response of the riser group is enhanced compared with that of the isolated riser, which is the interference enhancement region (yellow); η<0 indicates that it is suppressed, which is the interference suppression region (blue). The displacement interference efficiencies of most riser groups in two directions are above 100% at U r ≤3.36, and the vibration displacement increases greatly with the reduced velocity, which indicates that the interference effect of fluid between risers is stronger at low velocities than that at high, so the interference effect of wake and clearance flow in low velocities cannot be ignored.
In the CF direction, similar trends emerge in the interference efficiencies of the upstream risers in the three riser groups: the interference efficiency decreases and tends to be stable. For the two-riser group, the riser group is in the displacement enhancement region to a large extent, which is opposite in the IL direction, and the weakened displacement area is widely distributed. For the three-riser group, in the CF direction, the interference effect enhances the rolling up of the separated shear layers on both sides of the midstream and upstream risers, causing them to produce strong vortex shedding, and the trajectory is inclined to the upstream direction. Both Risers #3-1 and #3-2 are in the interference enhancement region. However, in the IL direction, the displacement is suppressed, and the wake shielding effect is significantly stronger than that in the CF direction, which is consistent with the conclusion in Section 3.2. For the fiveriser group, the rule is obviously different from others. The maximum interference efficiency appears at low reduced velocity with Riser #5-1, and the interference efficiency gradually decreases. The displacement responses of risers are in the suppression region except for Riser #5-1, and the interference efficiencies of Risers #5-4 and #5-5 are relatively WANG Yu et al. China Ocean Eng., 2022, Vol. 36, No. 3, P. 333-347 345 stable.
Conclusions
(1) The dominant frequency, dimensionless displacement, and variation trends of the upstream riser in the tandem riser group are close to those of the isolated riser. The wake shielding effect is remarkable, and the midstream and downstream risers have interference feedback to its upstream riser, which suppresses the CF dominant frequency of the upstream riser, but enhances the IL displacement. The interference effect of midstream and downstream risers on their upstream risers is significantly lower than that of upstream risers on midstream and downstream risers, regardless of the vibration frequency and displacement response.
(2) The vibrations of midstream and downstream risers are the nonlinear superposition of WIV of upstream riser and its own VIV, and the uncertainty of wake and gap flow leads to the contingency of the riser vibration cancellation or enhancement. Repeated superimposed wake vortices act on the midstream and downstream risers of the five-riser group, resulting in significant variations in their vibration modes, and vibration trajectories lag behind those of their adjacent upstream risers. In particular, the vibration frequency distribution range of downstream risers is widened and the dominant frequency is extremely unstable.
(3) The wake interference effect suppresses the VIV displacement of midstream and downstream risers in the IL direction compared with the displacement of the isolated riser; and promotes the vibration amplitude in upstream and midstream of two-and three-riser groups in the CF direction. The first-order mode weight dominates vibration, but the upstream and midstream risers in the five-riser group show strong mode transformation characteristics. Owing to the multiple wake interference effect, the actual velocity of the downstream riser is reduced, and no mode transition characteristics are observed in CF and IL directions, all of which show standing wave characteristics.
(4) The interference effect of fluid between risers on adjacent risers at low velocities is stronger than that at high velocities, so the interference effect of wake feedback effect and clearance flow at low velocities cannot be ignored. The CF displacements of upstream risers are all in the interference enhancement region. The CF displacement of upstream and midstream risers in tandem riser groups needs to be paid more attention considering the structural design and cost control of the riser group.
Right and permissions
Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. | 7,127.4 | 2022-06-01T00:00:00.000 | [
"Chemistry",
"Engineering"
] |
Topological phase in plasma physics
Recent discoveries have demonstrated that matter can be distinguished on the basis of topological considerations, giving rise to the concept of topological phase. Introduced originally in condensed matter physics, the physics of topological phase can also be fruitfully applied to plasmas. Here, the theory of topological phase is introduced, including a discussion of Berry phase, Berry connection, Berry curvature, and Chern number. One of the clear physical manifestations of topological phase is the bulk-boundary correspondence, the existence of localized unidirectional modes at the interface between topologically distinct phases. These concepts are illustrated through examples, including the simple magnetized cold plasma. An outlook is provided for future theoretical developments and possible applications.
Introduction
The aim of this article is to introduce the concepts and physics of topological phase in the context of plasma physics. The application of topological phase in plasmas is in a fledgling state, although this exciting subject overlaps with active areas of research in other fields of physics.
Broadly speaking, topological phase refers to the notion that a bulk system can be characterized by an integer-valued topological invariant. More precisely, the topological invariant describes a global property of an eigenfunction in wave vector space. This type of topology has a more abstract nature than, for instance, the standard topological property of the number of holes of an object in physical space. An important feature of topological invariants is that they are constrained by topological quantization and are generally not altered under smooth deformations, and so their physical consequences may be robust against perturbations.
A clear physical manifestation of the topological phase arises when two topologically distinct materials are adjacent. The bulk-boundary correspondence principle states that within a common bandgap at the interface between the two materials, a spatially localized mode exists, referred to as an edge state, or topological wave. These edge states have attracted interest because of their topological robustness and potential for unidirectional, backscatter-resistant propagation.
The first glimpses of topological phase trace back to the quantization of the Hall conductance in condensed matter systems in the integer quantum Hall Effect (Klitzing et al. 1980;Laughlin 1981;Thouless et al. 1982;Avron et al. 1983;Simon 1983;Niu et al. 1985). The conductance of a sample was experimentally measured to occur in integer multiples of e 2 /h, where e is the elementary charge and h is Planck's constant. Eventually it was realized that this integer multiple corresponded to a topological invariant called the Chern number that described the sample bulk, with corresponding electron edge states that allowed conduction.
Later it was realized that similar topological phases could be found in photonic crystals . This discovery reflects the principle that topological phase is not inherently dependent on quantum mechanics but is a property of waves. The periodic metamaterial structure of a photonic crystal gives rise to Bloch states and Bloch bands analogous to those in condensed matter systems. This field of topological photonics may offer novel disorder-robust routes to controlling light (Lu et al. 2014;Ma et al. 2015;Ozawa et al. 2019).
Topology in condensed matter and photonic systems are studied in systems with an underlying periodic lattice structure. Some mechanical and acoustic systems in which topological phases and edge states have been explored are also based on periodic lattices (Peano et al. 2015;Yang et al. 2015;He et al. 2016;Nash et al. 2015;Huber 2016).
In contrast, plasmas and fluids are typically described mathematically as a smooth continuum, coarse-grained over the length scale of individual particles. This distinction gives rise to a very different structure of the wave vector space. When there is a periodic lattice, the wave vector space is also periodic and can be limited to the first Brillouin zone. In an infinite continuum medium, the wave vector space extends to infinity. An important breakthrough was that of Delplace et al. (2017), who demonstrated that a model in geophysical fluid dynamics can be understood through topological phase and bulk-boundary correspondence. Other topological phenomena in fluid and continuum electromagnetic media have also been discovered (Silveirinha 2015;Perrot et al. 2019;Souslov et al. 2019;Marciani & Delplace 2020).
The rich wave physics of plasma makes it likely they can host a variety of topological effects. Some recent studies have begun to scratch the surface. For instance, topological properties of a magnetized cold plasma have been studied Parker et al. 2020b;Fu & Qin 2020). The Alfvén continuum may also be topological in the presence of magnetic shear, leading to a new interpretation of the reversed-shear Alfvén eigenmode as a topological edge wave (Parker et al. 2020a). This work also found non-trivial topology in the whistler band within Hall Magnetohydrodynamics. Yet a systematic study for how topological phase manifests in plasmas and an understanding of the physical consequences and applications are at their inception.
The purpose of this paper is to provide an accessible introduction to these concepts and their applications, without requiring any background in condensed matter physics or differential geometry. The emphasis is on continuum models with application to plasma physics or geophysical or astrophysical fluids. For more complete and thorough treatment of topological physics, other reviews may be consulted (e.g., Hasan & Kane (2010); Ozawa et al. (2019); Bernevig & Hughes (2013); Asbóth et al. (2016)).
We review in section 2 some essential mathematical background of Berry phase and Chern numbers. In section 3, we first discuss the shallow-water model for its analytical simplicity, then consider the topological characterization of a magnetized cold plasma and describe a topological wave that may be found at the boundary of a magnetized plasma and vacuum. In section 4, we discuss some important relationships between topology and discrete symmetries. We provide an outlook in section 5.
Mathematical background
In this section we review the mathematical background for topological phase.
Discrete Berry Phase
A Berry phase describes phase evolution of a complex vector as it changes around a closed loop (Berry 1984;Hannay 1985;Berry & Hannay 1988). The Berry phase probes the underlying geometric structure. A non-zero Berry phase is analogous to the situation of a vector not returning to its original direction when it undergoes parallel transport around a loop on a curved surface. A standard example for where a Berry phase arises is the adiabatic evolution of a quantum mechanical wavefunction. Berry or geometrical phases have also found numerous applications in plasma physics (Littlejohn 1988;Liu & Qin 2011Brizard & de Guillebon 2012;Rax & Gueroult 2019;Burby & Qin 2013). To discuss Berry phase in a general way, our setting is a Hilbert space, and we use bra-ket notation, where the Hermitian product of two vectors |u and |v is denoted by u|v . If a and b are constants, then au|bv = a * b u|v , and an asterisk denotes complex conjugation.
As is often the case, one can first gain intuition in a discrete setting. Suppose we have N unit vectors, |u 1 , . . . , |u N , as depicted in figure 1(a). The Berry phase of this sequence of vectors is defined as γ = −Im ln u 1 |u 2 u 2 |u 3 · · · u N |u 1 .
(2.1) γ is the Berry phase around a closed loop formed by the discrete sequence. For a complex number z = |z|e iϕ , Im ln z = Im(ln |z| + iϕ) = ϕ, so the Im ln(·) operation yields the complex phase and discards the magnitude. The product of the N inner products of the vectors has some complex phase, and the negative of that phase is the Berry phase. Since different branch choices of the complex logarithm leads to non-uniqueness of the phase up to integer multiples of 2π, the Berry phase is defined modulo 2π. Typically, when working with complex unit vectors, their overall phase is arbitrary such that any physical result does not depend on the phase. The Berry phase is constructed such that it is invariant to these phases. To see this, consider a gauge transformation induced by phase factors β j , where a new set of N vectors is defined |u j → e −iβj |u j . (2. 2) The Berry phase computed from the transformed vectors is exactly γ because all of the individual phases cancel out. The Berry phase is said to be invariant to the gauge transformation, or gauge invariant. The gauge invariance of Berry phase suggests it may be connected to a physically observable phenomenon.
Continuous Formulation of Berry Phase
Let us take the continuum limit of the Berry phase. We start from the expression which is equivalent to (2.1) modulo 2π. We suppose j is an index that parameterizes some property, and we let j pass to the continuous parameter s and |u j → |u(s) as shown in figure 1. An additional constraint is that we impose that |u(s) be continuous and differentiable.
In the continuum limit, the intuitive notion is to let u j |u j+1 → u(s)|u(s + ds) , but we immediately replace this by setting (2.4) where |u ( In the continuum limit of (2.3) and taking the sum to an integral, we obtain where the integral is over the closed loop. An important property is that u(s)|u (s) is pure imaginary, which follows from differentiating u(s)|u(s) = 1 with respect to s. Thus, equivalent to (2.7) is γ = i ds u(s)|u (s) . (2.8)
Berry Connection
Thus far, we have merely dealt with a parameterized loop of unit vectors, with vectors defined only on that loop. Now, suppose there is a two-dimensional (2D) parameter space, with coordinates denoted by k = (k x , k y ) as in figure 2. While this parameter space can be completely general, we will primarily be concerned with the situation where the parameters are wave vectors in Fourier space. Furthermore, we assume one can define vectors |u(k) which exist within some neighbourhood of c, not just c itself. Along the path c, we can write |u(s) → |u(k(s)) , and express where a sum over repeated indices is implied. The Berry phase can be written (2.10) We define which is called the Berry connection or Berry potential. The terminology 'connection' comes from differential geometry, whereas the term 'potential' arises from an analogy with the vector potential of electromagnetism. The Berry connection is pure real, as can be seen by taking the gradient of u | u = 1 with respect to k. Let us consider how the Berry connection and Berry phase transform under a gauge transformation. Similar to the discrete case, define a gauge transformation to construct a new set of unit vectors differing from the original by a phase where the phase β(k) is real and differentiable. Using (2.11), the Berry connection transforms as and therefore the Berry connection is not gauge invariant. Because the factor e −iβ(k) must be single-valued, the Berry phase is gauge invariant modulo 2π.
Berry Curvature
Define the Berry curvature (2.14) The curvature encodes information about the local geometric structure. The curl applies in a 3D (or 2D restriction thereof) setting. One can formulate the curvature and other concepts here in higher dimensions using differential forms, but we have no need for that machinery at the moment. For a 2D parameter space (k x , k y ), there is only one component of the Berry curvature: The Berry curvature is gauge invariant. This fact follows from (2.13) and that the curl of a gradient vanishes. Thus there is a suggestive analogy with the magnetic field. The Berry connection A is analogous to the vector potential, and is not invariant under a gauge transformation. The Berry curvature F is analogous to the magnetic field, and is invariant under a gauge transformation.
Chern Theorem
A simple version of the Chern theorem states that the integral of the Berry curvature over a closed 2D manifold is for some integer C. Here, C is called the Chern number of the surface. It is a topological invariant associated with the manifold of states |u(k) defined on the surface. The Chern number is a property of the collection of complex vectors over the surface, not just the surface itself. As a topological invariant, the Chern number provides a topological quantization.
That the Chern number must be an integer can be understood intuitively as follows. Consider again figure 2. Let A 1 be the Berry connection constructed with a gauge such that it is smooth on S 1 , and similarly for A 2 on S 2 . The Chern number is given by Since gauge invariance requires the Berry phases γ 1 and γ 2 be equal modulo 2π, the Chern number must be an integer. When the Chern number is non-zero, one cannot construct a smooth, continuous gauge for |u(k) over the entire closed surface. A related concept is the hairy ball theorem, which states that due to the topology of the sphere, any vector field on the sphere must have singularities or vanishing points. While there is as yet no direct physical interpretation of the Chern number in continuum systems, the physical interpretation of the Chern number in photonic crystals has been advanced recently; it has been shown the photonic Chern number is related to the thermal fluctuation-induced angular momentum Silveirinha (2019a,b).
The Chern theorem relates geometry and topology. This is analogous to the Gauss-Bonnet theorem, which relates an integral of a local geometric quantity, the Gaussian curvature, to a global topological quantity, the Euler characteristic. Here, the Berry curvature is a local geometric quantity, whereas the Chern number is a global topological property. The analogy is not perfect, however, as an important distinction is that Gaussian curvature reflects a property of the base manifold while the Berry curvature reflects a property of a vector field on the base manifold.
Alternative form of the Berry Curvature
Given some unit vector as a function of two parameters k = (k x , k y ), (2.14) provides a formula for the local Berry curvature F (k). This standard form depends on derivatives of the vectors at different parameter values, which poses difficulties for numerical computations because great care is required to ensure a smooth gauge. An alternative form for the Berry curvature which is often useful can be given under the conditions that the parameterized vector arises from a non-degenerate Hermitian eigenvalue problem. The alternative form is manifestly gauge invariant.
Consider the eigenvalue problem where H is a Hermitian N × N matrix, which acts as an effective Hamiltonian. Thus the ω n are real. Here we assume that there is no degeneracy, so that all N eigenvalues are distinct. A discussion of the degenerate case can be found in (Bernevig & Hughes 2013). Let {|n }, n = 1, . . . , N be an orthonormal eigenbasis. The Hamiltonian depends on k, and therefore so do the eigenvalues and eigenvectors. From (2.15), the Berry curvature corresponding to eigenvector |n is Act on (2.22) from the left with m|. For n = m, and assuming non-degenerate eigenvalues, we obtain Consider the m = n term in the sum. We have previously seen that when |n is a unit vector, n| ∂n ∂ki is purely imaginary. Therefore, ∂n ∂kx |n n| ∂n ∂ky is real and does not contribute to the sum. Using (2.23) for the remaining terms, we obtain ( 2.25) This can also be written in the usual form without the explicit imaginary part: This form of the Berry curvature is manifestly gauge invariant, because any phase on the eigenvectors from a gauge transformation cancels out. This form can be useful in practice, particularly for numerical computations. The original form of the Berry curvature is not manifestly gauge invariant. It contains derivatives of the eigenfunctions. In contrast, (2.26) places the derivative on the Hamiltonian rather than on the eigenfunction and eliminates issues of needing to numerically constrain to a smooth gauge.
Bulk-Boundary Correspondence
One of the most important reasons for the widespread interest in topological phases is the bulk-boundary correspondence, which states that the bulk properties and edge properties of systems are connected. While our discussion so far has been purely an abstract, mathematical discussion, we now turn to the physical manifestations of topological phase. As already mentioned, the abstract unit vectors |u(k) discussed previously can represent the eigenfunctions of a Hamiltonian, with dependence on wave vector k. By use of a Fourier transform to k space, one is implicitly considering an infinite material, or that finite-size systems are sufficiently large. Chern numbers can be computed for each band in the bulk.
The bulk-boundary correspondence principle states that when two materials with differing topological phases and a common gapped spectrum are brought next to each other, modes localized to the interface and crossing the gap must appear at the interface (Hasan & Kane 2010). The bandgap Chern number for one material is C gap,1 = n<ngap C (1) n , summed over all bands below the bandgap in the first material. Similarly, for the second material the gap Chern number is C gap,2 = n<ngap C (2) n . If C gap,1 − C gap,2 = 0, propagating surface modes are present in the gap. The standard heuristic argument for why modes at the interface must appear is that for a gapped spectrum, the Chern number cannot change across the interface unless the gap closes somewhere at the interface. Closing the gap is accomplished by the surface mode. Moreover, the difference in Chern number dictates the number and direction of the propagating surface modes Hassani Gangaraj et al. (2017).
While the conventional understanding just given is often assumed to hold, it is typically proven only for specific model systems (Silveirinha 2019a). Additionally, in some cases of continuous-media systems, the bulk-boundary correspondence principle has been found to not apply straightforwardly (Hassani Gangaraj & Monticone 2020). Tauber et al. (2020) found that the number of edge modes can be boundary-condition dependent, and restoration of the correspondence between Chern numbers and number of edge modes requires a more generalized accounting of possible ghost edge modes.
Compactness
The Chern theorem of (2.16) holds for a closed manifold (a manifold without boundary that is compact). In condensed matter systems or photonic crystals that have an underlying periodic lattice, the wave vector space of the first Brillouin zone is also periodic, topologically equivalent to a torus, and compact. The Chern theorem can therefore be applied directly.
However, in continuum models that are typically used in plasmas or fluid dynamics, non-compact wave vector manifolds arise naturally. The wave vector space extends to infinity; |k| = ∞ can be thought of as the boundary. It is therefore important to delve at least a little into the issue of compactness to understand whether and how the Chern theorem is applicable. To be fully precise here, we distinguish between a Chern number, which is an integer-valued topological invariant, and the integral of the Berry curvature. For a compact manifold, the Chern theorem guarantees these two values are equal. For a non-compact manifold, that is not necessarily the case, and in fact one may find noninteger results for the integral of the Berry curvature. The effects of non-compactness are subtle, and may or may not cause difficulties in any given problem.
For example, one of the frequency bands in the cold plasma model discussed in section 3.2 has a non-integer integral of the Berry curvature, although the other bands have integer values (Parker et al. 2020b). Moreover, in the shallow-water model discussed in section 3.1, all frequency bands result in integer-valued Berry curvature integrals. Interpretation in terms of the bulk-boundary correspondence is unclear when non-integer values are present.
There are various ways of dealing with the lack of compactness in continuum models (Silveirinha 2015;Tauber et al. 2019;Souslov et al. 2019). If the problem stems from infinite wave vectors, one method is to introduce a regularization at small scales that enables compactification. For example, if the behaviour is regularized to decay sufficiently rapidly at large wave vectors, the infinite k-plane can be mapped onto the Riemann sphere, which is a compact manifold and enables the Chern theorem to apply. Physically, such a regularization can be justified because the continuum model ceases to be valid at the microscopic scale of the interparticle spacing and the discreteness of the plasma becomes apparent. Regularization based on plasma discreteness for the cold plasma model was used by Parker et al. (2020b).
Instead of regularizing based on some physically motivated reason, one might try to tackle the lack of compactness directly. For non-compact manifolds, the index theorems relating an analytical index and topological index can be generalized, and there are additional boundary terms in the index formula (Eguchi et al. 1980). The boundary data arising from infinite wave vectors can be responsible for the non-integer integral of the Berry curvature.
Examples
The concepts described in the previous section are illustrated with specific examples. The first example, in section 3.1, comes from the shallow-water equations of geophysical fluid dynamics (Delplace et al. 2017). This example, although not directly related to plasma physics, is discussed in detail for its analytic transparency, minimal complexity, and clear physical manifestation of the bulk-boundary correspondence principle. The mathematical framework of wave analysis is the same as commonly used in plasma physics: linearized equations of motion and Fourier analysis. This example also serves to highlight the interdisciplinary nature of these topological ideas. In section 3.2, we discuss topology of a magnetized cold plasma and describe a topological surface wave between plasma and vacuum.
Shallow-water equations and equatorial waves
Following Delplace et al. (2017), the non-dimensionalized, linearized fluid equations of motion of the shallow-water system are where u x and u y are the fluid velocities and η is the perturbation about the mean height.
The f -plane model is used here, which is a local model of a rotating sphere using a constant value for the Coriolis parameter f at a particular latitude, and x and y are the coordinates on the tangent plane. The sign of f changes across the equator from the northern to southern hemisphere. To facilitate analysis, the f -plane is taken to be infinite and homogeneous. Note that f appears in a manner similar to the cyclotron frequency of charged particles moving in a magnetic field. Following standard Fourier analysis, we treat all perturbation quantities as having dependence e i(kxx+kyy−ωt) . The linearized system can then be written as the eigenvalue equation where the frequency ω is the eigenvalue, and (3.4) The effective Hamiltonian H is Hermitian. The eigenvalues are ω ± = ± k 2 + f 2 and ω 0 = 0, where k 2 = k 2 x + k 2 y . These modes are the Poincaré waves and a degenerate zero-frequency Rossby wave. The non-normalized eigenfunctions are (3.5) The three frequency bands are shown in figure 3. Using the concepts developed in section 2, we are now in a position to calculate the Berry connection, Berry curvature, and Chern number of each band. We show the computation in detail for the ω + band; the other two bands are analogous. The standard inner product is used.
First we compute the Berry connection for this band. An equivalent expression to (2.11) for a non-normalized eigenfunction is It is convenient to express ∇ k in polar coordinates, where k x = k cos ϕ and k y = k sin ϕ. Thus, (3.7) and Thek component of ψ + | ∇ k ψ + is real and hence does not contribute to A + . We obtain The Berry curvature is (3.10) The Chern number of this band is Topological quantization has emerged: the Chern number can only take on integer values. The breaking of time-reversal symmetry by the rotation of the Earth results in a topologically non-trivial bulk fluid in the f -plane model of the shallow-water system. One can similarly show that the Chern numbers for the other bands are C 0 = 0 and C − = − sign(f ). The Chern numbers are indicated in figure 3. This example offers a clear demonstration of the bulk-boundary correspondence principle. The direct implication is that if f in (3.1) is a function of y rather than constant, then there must be a unidirectional wave localized to the spatial region around f = 0 that spans the frequency gap. Because the change in Chern number across such an interface is C + (f > 0) − C + (f < 0) = 2, there are two localized waves.
The more physical case of interest is an actual spherical surface without the Cartesian approximation. The Coriolis parameter f changes sign across the equator. Hence, the equator forms an interface dividing the topologically distinct northern and southern hemispheres. In fact, the two expected waves guaranteed by the bulk-boundary correspondence principle are the well-known equatorially trapped modes, the Kelvin wave and the Yanai wave (Delplace et al. 2017). The dispersion relation for both the Kelvin and Yanai wave is monotonic, indicating group velocities of unidirectional, eastward travelling waves.
Despite the fact that the Cartesian f -plane neglects spherical curvature, which is an order-unity effect, analysis of the f -plane has yielded the key topological insight that the northern and southern hemisphere are topologically distinct. Kelvin waves have been clearly observed in the spectrum of fluctuations in the Earth's atmosphere (Wheeler & Kiladis 1999). In simulations, Delplace et al. (2017) found that equatorially trapped Kelvin waves lying in the frequency gap experienced reduced scattering against static perturbations compared with modes not in the frequency gap, a signature of topological protection.
Although the infinite k-plane is not compact, the behaviour at infinite k has not in this case spoiled the result of finding an integer Chern number by integrating the Berry curvature. The compactness issue was handled in an alternate way by Delplace et al. (2017), who considered a 2D compact surface, a sphere, within the 3D parameter space (k x , k y , f ). The Berry curvature within the 3D parameter space is that of a monopole at the origin, and hence any closed surface containing the origin will yield the same Chern number. This calculation can be reconciled with the one presented above by considering a cylinder centred at the origin of finite height in f and very large radius in the (k x , k y )plane. The Berry flux through the side of the cylinder vanishes, and the flux through one end of the cylinder is equal to the flux through the infinite k-plane at constant f above. Yet another way of dealing with compactness is through the addition of odd viscosity (Souslov et al. 2019;Tauber et al. 2019).
Magnetized cold plasma and the gaseous plasmon polariton
In this section, we examine a simple magnetized cold plasma and show that it can host topological phases along with related interface modes. The magnetic field breaks time-reversal symmetry.
Consider an infinite, homogeneous, ion-electron plasma. When considering highfrequency electromagnetic waves, it is appropriate to treat the ions as a fixed neutralizing background and only consider electron motion. The mathematical description of a cold plasma consists the electron equation of motion and Maxwell's equations: where v is the electron velocity, E the electric field, B 0 = B 0ẑ the background magnetic field, B the perturbation magnetic field, n e the background electron density, m e the electron mass, c the speed of light, and 0 the permittivity of free space. We consider a fixed k z parallel to the background magnetic field and choose a twodimensional parameter space (k x , k y ). After proper non-dimensionalization and Fourier analysis, one obtains the Hermitian eigenvalue problem ω |ψ = H |ψ , where H is a 9 × 9 matrix and |ψ = [v, E, B]. Figure 4 shows the four positive-frequency bands. Non-trivial topology is found in multiple bands, as indicated by the non-zero Chern numbers (Parker et al. 2020b;Fu & Qin 2020). Unlike the shallow-water example, here the straightforward integration of the Berry curvature yields a non-integer result for one of the bands. As discussed in section 2.7, this stems from a lack of compactness. To obtain the integer Chern numbers shown in figure 4, a large-wavenumber cutoff of the plasma response was introduced to regularize the small-scale behaviour, motivated by the physical fact that the continuum description breaks down at the scales of the interparticle spacing.
When the topologically non-trivial plasma is placed next to the trivial vacuum, bulkboundary correspondence suggests the existence of modes at the interface. One can consider semi-infinite planar system, where the plasma and vacuum each occupies half of the space . A more physically realizable system is a confined cylindrical plasma with a radially decreasing density, transitioning to a low-density vacuum-like region. Parker et al. (2020b) investigated this system and demonstrated the existence of topological boundary waves. An important component of that study was accounting for a finite width of the density interface. A gaseous plasma cannot sustain a discontinuous density interface with vacuum, and the interface width is typically limited by classical Figure 4. Spectrum of a magnetized, homogeneous cold plasma as a function of ky (kx set to zero, but the system is isotropic in the xy-plane), where only electron motion is retained. The two cases show (a) kz < k * z and (b) kz > k * z , where k * z is a critical point at which a topological transition occurs. The Chern numbers of the positive-frequency bands are shown (Parker et al. 2020b). or turbulent diffusion processes. A discontinuous step in density serves as a good first approximation but is quantitatively limited. Because the width of the density interface may be comparable in size to the wavelength of the wave, a quantitative treatment is necessary to accurately determine whether the wave can exist. Figure 5 shows the surface mode at the plasma-vacuum interface. This mode is the gaseous plasmon polariton (GPP), named for its similarity to surface plasmon polaritons occurring at the surface of metals. The spectrum of the inhomogeneous plasma was computed by solving the differential eigenvalue equation in radius. In the figure, the dispersion relation of the GPP is unidirectional and crosses the bandgap. In (Parker et al. 2020b), a typo led to the GPP being described as "undirectional" rather than the correct "unidirectional." The GPP can exist in planar as well as cylindrical geometries.
This study also showed that the GPP can be realized in plasma regimes achievable in laboratory experiments. The parameters used by Parker et al. (2020b) were directly motivated by the plasma parameters of the Large Plasma Device (Gekelman et al. 2016). In this case, a peak plasma density of n = 4 × 10 11 m −3 , magnetic field B = 0.1 T, and density scale length of L n ≈ 5 cm were used, and the GPP was calculated to have a frequency of ∼ 2 GHz. Hence, the GPP offers a window into the experimental study of topological phenomena in plasma systems.
Discrete symmetries and topology
There is a profound relation between symmetry and topology. In this context, discrete symmetries such as parity and time play a crucial role. In recent literature, PT symmetry analysis has been discussed (Bender 2007;Qin et al. 2019). Here, we discuss the consequences of discrete symmetries on the topology of the system.
Parity P refers to the inversion of one or more spatial dimensions, and time reversal is denoted by T . Mathematically, when acting on the state vector of a linear system, P is a linear, unitary operator with P 2 = 1. The action of parity is here defined as reversing the sign of x and then applying a unitary operator V .
In quantum mechanics, time reversal requires complex conjugation of the wavefunction. Complex conjugation does not inherently enter in the context of classical physics described in terms of real variables. However, in the Fourier domain, one can draw a connection to complex conjugation by using the reality condition, which is related to particle-hole conjugation in quantum contexts. From this perspective, for a linear system, time reversal T is an antilinear operator with T 2 = 1. Antilinear means T c |ψ = c * T |ψ where c is a complex constant. The action of time reversal is here defined as mapping t → −t, applying complex conjugation by using the reality condition, and then applying a unitary operator U .
Let H k be the matrix differential operator corresponding to the linear problem, which depends on the spatial derivatives, written in terms ofk j = −i∂/∂x j . For an infinite, homogeneous system, an eigenmode with wave vector k and eigenfrequency ω has the form |φ = e i(k·x−ωt) |ψ , (4.1) where |ψ is just a constant vector that has no space or time dependence, such that In this expression, H(k) is simply H k wherek has been replaced by the algebraic quantity k, and H(k) is a matrix with no differential operators. Hence, this leads to the conventional Fourier-space eigenvalue formulation, A consequence of a parity symmetric system [H, P] = 0 is that given one eigenmode |φ , P |φ is also an eigenmode with the same frequency ω. The proof is simple: In the last equality, we have used that if P flips the sign of one or more components of x, then one can equally well think of it as flipping the sign of the corresponding components of k. Therefore, P |φ is indeed an eigenmode; it has wave vector Pk, frequency ω, and components V |ψ . We can also consider the consequence of the system being symmetric under time reversal. A consequence of [H, T ] = 0 is that T |φ is an eigenmode with frequency ω * . To see this, note (4.6) Using our convention for the action of T , we find where the notation |ψ * means the complex conjugate of the components is taken. Hence, T |φ has wave vector −k, frequency ω * , and components U |ψ * . Parity symmetry has direct implications for the Berry connection. We assume a nondegenerate situation where |φ and P |φ can be labelled as part of the same eigenmdode branch. Here, suppose P represents full inversion symmetry with Pk = −k. From (4.5), we have To be more precise, one can slightly generalize (4.8) with a possibly k-dependent phase factor, which amounts to a gauge transformation as discussed in section 2.2. From A(k) = i ψ(k) | ∇ k ψ(k) , we observe that up to a gauge transformation, where † denotes the Hermitian adjoint. Full inversion symmetry then implies the Berry curvature F(k) = ∇ k × A is even, (4.12) Time-reversal symmetry can be analysed following a similar approach. From (4.7), we have |ψ(−k) = U |ψ(k) * up to a gauge transformation. Using this result in (4.9), we obtain (4.14) Because the Berry connection is real, we may take the complex conjugate without changing the result, leading to A(−k) = i ψ(k) | ∇ k ψ(k) . Recalling the Chern number C = (2π) −1 dk F (k), we see that invariance under T implies a vanishing Chern number. Moreover, invariance under both full inversion and time-reversal symmetry implies the Berry curvature itself vanishes.
Discussion
We have introduced topological band theory in the context of plasmas. One clear physical manifestation of non-trivial topological phase is the presence of modes occurring at the interface between topologically distinct materials, such as a magnetized plasma and vacuum. Topological physics, along with many generalizations and extensions not presented here, have been systematically studied and applied in condensed matter and photonics as well as other fields of physics. For instance, topological classifications beyond the Chern number exist, such as the Z 2 invariant of topological insulators (Kane & Mele 2005a,b).
Various important effects in plasmas can take one beyond the simple topological band theory discussed in this article. Topological physics is most well understood in the case of Hermitian Hamiltonians. In contrast, a non-Hermitian Hamiltonian can occur, for instance, when a system experiences gain and/or loss. In plasmas or fluids, non-Hermiticity might also arise from the presence of flow shear or a density gradient. In recent years there has been a significant effort to generalize topological band theory to non-Hermitian Hamiltonians (Esaki et al. 2011;Hu & Hughes 2011;Leykam et al. 2017;Shen et al. 2018;Gong et al. 2018;Kunst et al. 2018;Martinez Alvarez et al. 2018). A natural jumping off point is the space of PT -symmetric Hamiltonians, which can under certain circumstances give real spectra like a Hermitian Hamiltonian. In the general case with complex eigenvalues and exceptional points, topological classification, topological protection, and the relation to bulk-boundary correspondence are still not fully settled, although much progress has been made in specific problems. Understanding non-Hermitian topological effects in plasmas and fluids is an open area.
Nonlinearity is another important feature of plasmas and fluid systems. The theory in terms of an effective Hamiltonian and frequency bands is based on a linearization around equilibrium, an assumption that may have limited validity in many situations. Effects from nonlinearity have been studied in topological photonics (Lumer et al. 2013;Leykam & Chong 2016;Smirnova et al. 2020). In plasmas, the interplay between topology and nonlinearity is ripe for exploration.
Further investigations will deepen our understanding of the physics of topological phase in plasmas and uncover the behaviour of topological modes in plasmas. Significant theoretical development is needed to unravel the topological nature of the diversity of plasmas at different parameter regimes and scales. Laboratory investigations are within reach to probe experimental consequences and uses of topological physics in plasmas. Potential applications of this emerging area include the ability to predict new interface modes using the bulk-boundary correspondence. The presence of these modes in some circumstances might be used to provide diagnostic information on plasma parameters, or in other situations might provide new means of exerting control over plasmas. Topological plasma waves may also be robust to perturbations. | 8,884.4 | 2020-09-13T00:00:00.000 | [
"Physics"
] |
Structural HealthMonitoring Using High-Frequency Electromechanical Impedance Signatures
An overview of recent advances in electromechanical impedance(EMI-) based structural health monitoring is presented in this paper. The basic principle of the EMI method is to use high-frequency excitation to sense the local area of a structure. Changes in impedance indicate changes in the structure, which in turn indicate that damages appear. An accurate EMI model based on the method of reverberation-ray matrix is introduced to correlate changes in the signatures to physical parameters of structures for damage detection. Comparison with other numerical results and experimental data validates the present model. A brief remark of the feasibility of implementing the EMI method is considered and the effects of some physical parameters on EMI technique are also discussed.
Introduction
Over the last decades, structural health monitoring (SHM) has been recognized as a useful tool for improving the safety and reliability of structures and to thereby reduce their operational cost [1].Many SHM techniques thus have been developed in the literature [2][3][4] to quantify and locate the damages in the structures, based on either the global or the local interrogation of the structures [5].Although these SHM methods have their specific advantages for detecting damages in the structures, the existent drawbacks may limit their applications on some aspects.For example, in global dynamic techniques, it is well known that the structure is subjected to low-frequency excitations and only the first few mode shapes and their corresponding natural frequencies can be accurately extracted.Because localized damages find it hard to alter global parameters such as natural frequency, curvature mode shape, and mode shape data, only large damages can be detected.Meanwhile, signals obtained using these methods are more prone to contamination by ambient vibration noise at low frequencies less than 100 Hz particularly [5].Other typical local techniques, such as ultrasonic techniques, acoustic emission, and impact echo testing, require expensive and sophisticated hardware as well as well-trained professional operators [6].
On the other hand, electromechanical impedance (EMI) based structural health monitoring has shown promising successes in monitoring and finding minor changes in structural integrity [5][6][7][8][9].A key aspect of EMI method is the use of PZT patches as collocated sensors and actuators.To apply PZT as an actuator-sensor simultaneously, a PZT patch bonded to a structure is driven by a fixed alternating electric field.A surface charge is generated in response to an applied mechanical stress (direct effect), and conversely, a mechanical strain is produced in response to an applied electric field (converse effect).The electromechanical impedance defined as the ratio of the applied voltage and the resulting current can then be measured by a commercially available impedance analyzer.Although structural mechanical impedance related to structural properties such as stiffness and damping is difficult to obtain at first hand, the measured electrical impedance is directly related to mechanical impedance of the monitored structure and is also affected by the presence of structural damages.Thus, by observation of the electromechanical impedance of the PZT patch, one can obtain the information about the damage of the monitored structure [10].In general, the EMI signature is extracted at high frequencies (typically 10-500 kHz) [11].At such frequencies, the wavelength of the excitation is very small and is therefore sensitive enough to detect minor changes in structural integrity.Many experimental investigations [5,[12][13][14][15][16][17][18][19] have shown the specific advantages of EMI technique over the conventional nondestructive evaluation methods.Sun et al. [12] first used EMI technique to examine a lab-sized truss structure.Ayres et al. [13] presented this qualitative impedance-based health monitoring method in real-time damage evaluation of civil infrastructures such as bridge joints.Soh et al. [14] studied the performance of smart piezoceramic patches in health monitoring of a reinforced concrete bridge at various stages during the loading process.Park et al. [15][16][17] demonstrated the capability and the effectiveness of this technology to detect damages of compositereinforced concrete walls, a 1/4-scale bridge element, and a pipe joint, respectively.Bhalla and Soh [5] discussed the feasibility of employing impedance signatures in monitoring the conditions of RC structures subjected to base vibration.Bois et al. [18,19] detect a single delamination in a laminated composite plate via the EMI signatures of a piezoelectric transducer cemented onto the structure.These experimental researches indicate that the collection and processing of electromechanical impedance signatures are very easy to implement via an Agilent 4294A impedance analyzer and the EMI technique is highly sensitive to detect minor changes in structural integrity using measured data.However, an ideal robust damage detection scheme cannot only identify damages at a very early stage but also provide some estimate of the extent or severity of the damage and even locate the damage within the sensor resolution being used [20].Thus, appropriate tools of simulation are necessary for monitoring system adapted to monitored structures.
The overview of the impedance method up to 2003 was previously summarized in [21].The paper aims to give an updated overview of the recent advances in the EMI-based structural health monitoring.The basic principle of the EMI technique is first reviewed in Section 2. The recent developed approach, which integrates an accurate EMI model, in which both inertia effect of the PZT patch and the bonding property of adhesive are taken into consideration, with a stable high-frequency structural dynamics analysis method, the method of reverberation-ray matrix, is described in Section 3. Based on various sources in literature, Section 4 presents a discussion on the proper selection of parameters associated with the EMI-technique.Some recent applications of the EMI-based SHM method to complex configurations are noticed in Section 5.The paper ends with a brief summary.
Conventional EMI Models
Liang et al. [22] addressed that both approaches including a static approach and a dynamic finite element approach have some drawbacks in analyzing the dynamic response of active material systems and the impedance modeling technique is more suitable to reflect the physical essence of an active system.A simple 1-D model is then constructed to describe the interaction between a PZT patch and its host structure as shown in Figure 1.The PZT patch is bonded perfectly to the surface of the structure using a high-strength adhesive to ensure a better mechanical interaction and is assumed as a thin bar undergoing axial vibration in response to applied alternating voltage.A single-degree-of-freedom system is then considered as shown in Figure 2, in which one end of the PZT bar is fixed and the other end is connected to the host structure.According to this model, the constitutive relation of the PZT patch may be expressed as follows [22]: where S 1 is strain, T 1 the stress, s E 11 the complex compliance at zero electric field, d 31 the piezoelectric constant, and D 3 the electric displacement; ε T 33 = ε T 33 (1 − δi) is the complex dielectric constant and δ is the dielectric loss factor.By solving the equation for the PZT bar connected to the external mechanical point impedance of the structure, the following expression of electrical admittance (inverse of impedance) in frequency domain can be obtained [23]: where Y is the electrical admittance, Z p and Z s are the mechanical impedances of the PZT and the structure, respectively, E p and a are the complex Young's modulus and the geometric constant of the PZT patch, respectively, and ω is the circular frequency.It should be noted that although (2) is derived from a single-degree-of-freedom system, it is still applicable for 2D or very complex structures [16].
Although a good match between the predicted solutions by 1-D impedance model [22,23] and the experimental results was achieved, Zhou et al. [24] pointed out that the mechanical impedance coupling in different coordinate directions should be considered for two-dimensional structures and the cross impedance of the host structure has an impact on the transducer dynamics.With due derivation, the analytical expression of electrical admittance was then obtained based on two-dimensional impedance model [25]: where κ = ω ρ(1 − ν 2 )/E p , ν is Poisson's ratio; h p , w p and l p are height, width, and length of the PZT wafer, respectively, and where A denotes κ cos(κl p ), B denotes κ cos(κw p ), Z xx and Z yy are direct impedance, Z xy and Z yx are cross impedance of the host structure, respectively, and Z axx and Z ay y are mechanical impedance of PZT patch in x and y directions, respectively.
Although the analytical derivations of above equations based on 2-D model are accurate themselves, the experimental difficulties limit their direct application for extraction of the host structure's mechanical impedance [26].Thus, an effective mechanical impedance model [26,27] was developed for improving the existing models, in which the mechanical interaction between the PZT patch and the host structure is not restricted at the PZT end points and it extends all over the finite sized PZT patch [26].The finally obtained expression of electrical impedance is similar to that based on the classical one-dimensional model.
In the classical impedance model, a key problem is to obtain the analytical expression of the mechanical impedance Z s , which is defined as Z s = F/ ẋ.(The impedance is determined by calculating the structural dynamic response, ẋ, corresponding to an arbitrary force F at the driven point of the transducer [22].)For some simple structures, such as axial rods [28][29][30], beams [29][30][31], circular rings [32,33], thin plates [24,34,35], and shells [36], the analytical expression of the electromechanical impedance can be obtained readily based on the impedance modeling approach.However, when damages are induced in structures resulting in possibly inhomogeneity of material properties, analytical formulation is very difficult to be derived.For example, although Zagrai and Giurgiutiu [34] formulated analytical solutions based on EMI spectrum and mechanical response of a circular plate, when a damage is induced into the plate, the assumption for axis-symmetric axial and flexural vibration of circular plates is untenable and the analytical solutions does not hold for damage detection in the plates.
In order to obtain damage information by using changes in electromechanical impedance signature, it is necessary to establish improved correlation between EMI signature and changes in structural integrity.The finite element method (FEM) seems to be an alternative for the purpose [6,11,30,[37][38][39][40].However, FEM is usually subjected to an inherent disadvantage that a large number of finite elements and hence a large number of nodes should be involved for accurately predicting high-frequency response of a structure.As the finite element model becomes finer, the associated mass and stiffness matrices will increase in size and thus requirements on storage and computing time become critical.Other methods such as spectral element method [10] and Ritz method [35] have been applied to quantitatively identify structural damages.But, there are still certain difficulties associated with high-frequency analysis that limit their applications in quantitative analysis of impedance-based health monitoring.The transfer matrix method (TMM) is very powerful to analyze a structure consisting of many members (including damaged members) because the number of resultant simultaneous equations can be greatly reduced.However, significant numerical difficulty at high-frequency limits its application if computation is completely executed on a computer [41].
Moreover, it was assumed in the classical impedance model that the force transmission is just at two ends of PZT patch while the intermediate bonding layer was completely ignored based on pin force model.However, in the experiment of Soh et al. [14] and Giurgiutiu and Zagrai [29], it was found that the bonding between patch and host structure may be damaged.When disbonding occurs, the signature obtained from patch was distorted.Actually, it has been recognized by many researchers [40,[42][43][44][45] that the imperfect bonding of PZT patch influences the output EMI signatures significantly and should be investigated carefully.
Due to the complexity of PZT patch-adhesive-host structure coupled structural system and the difficulty of dynamic analysis in the high-frequency range as mentioned above, most existent analytical models of EMI technique fail to correlate changes in the signatures to physical parameters of structures and could not provide further information about the nature of damage.In order to develop a more accurate model to improve sensitivity of impedance signature to damages in structures, two key issues should be dealt with, one is to seek for an appropriate modeling to simulate the behavior of the PZT patch-adhesive-host structure coupled structural system, and the other is to find a powerful highfrequency dynamic analysis technique.
Accurate EMI Models Based on MRRM
In some existent EMI model [26,27,42], the inertial term of PZT patch was neglected and the mechanical impedance of host structure was assumed to be a constant at all points of the patch attachment.However, because high-frequency electric field with typical propagation wave length comparable to the length of actuator is applied, The inertia effect of actuator should be considered [46,47].Furthermore, since the strain/stress transfer between PZT patches and host structures is physically implemented through bonding layers, a more accurate model for improving sensitivity of Advances in Civil Engineering signature to damages by modulating the property of bonding layers should be developed.A classic shear lag solution was employed by Crawley and Luis [48] and Tong and Luo [49,50] to analyze piezoelectric actuators as elements of intelligent structures.Bhalla and Soh [42] extended this method to develop an electromechanical impedance model of adhesively bonded piezo-transducers under quasistatic equilibrium and a good match between the predicted solutions and the measured data was observed.Under the consideration of both the inertia effect of actuator and the properties of the adhesive, Yan et al. [51][52][53][54][55][56], developed an accurate EMI model for detecting damages in classical rods [51], Mindlin-Herrmann rods [52], straight beams [54][55][56] and framed structures [53].By taking an Euler-Bernoulli beam adhesively and symmetrically bonded with two PZT patches as an example, we illustrate this EMI model in the following.
As shown in Figure 3, a pair of PZT patches is bonded symmetrically and adhesively onto the top and bottom surfaces of a nonhomogeneous beam and is driven by a fixed alternating electric field out of phase.The equation of motion of the PZT patch, which is assumed to be in a state of 1D axial strain [46,47], can be written out as where u is the axial displacement, ρ and E are the mass density and Young's modulus, and h is the thickness (the subscript p signifies the PZT patch).τ is the interfacial shear stress between the PZT patch (beam) and the adhesive and varies along the bonding length, and t is the time variable.On the other hand, the bond layer is in the state of pure shear based on the shear lag model [48]: where G is the shear rigidity of the bonding layer, and u s and w are the axial displacement and the transverse deflection of beam, respectively.The subscripts s and a correspond to the host beam and bonding layer, respectively.For an Euler-Bernoulli beam, we then can get the following relations: where M and Q are the bending moment and shear force, respectively, and I and A are the moment of area and the cross sectional area, respectively.With due derivation, we can obtain the solution of transverse deformation as follows: in which a i and d i (i = 1, 2, 3) are undetermined constants, and β i (i = 1, 2, 3) are defined in [55].For an arbitrary beam segment LM without bonded PZT patches, the well-known solution is expressed as where k LM = [(ρA) LM ω 2 /(E s I) LM ] 1/4 .Then, the method of reverberation-ray matrix (MRRM), which was originally proposed by Pao et al. [57][58][59] to study the transient response of a plane truss consisting of elastic members and then developed by Pao and Chen [60, 61] and Chen's research group [62,63] for high-frequency dynamic analysis, is extended to investigate dynamics of the smart structure system.In MRRM, the first step is to establish a global scattering relation as follows: where Q is source vector, d = [(d 0 ) T , (d 1 ) T , . . ., (d N−1 ) T , (d N ) T ] T is the global vector associated with departing waves, and a = [(a 0 ) T , (a 1 ) T , . .., (a N−1 ) T , (a N ) T ] T is the global vector associated with arriving waves [57][58][59][60][61][62][63].Then, according to unique physical reality of the smart structures, we can get the total phase relations: where P is the total phase shift matrix [57][58][59][60][61][62][63] and d and d contain the same elements but are sequenced in different orders.The two vectors d and d can be related through a permutation matrix U as where U is a square matrix which contains one unit element in each row as well as one unit element in each column.From ( 10), (11), and ( 12), we obtain where R is called the reverberation-ray matrix [57][58][59][60][61][62][63].It is then obtained that Hence, all undetermined constants in ( 8) and ( 9) can be solved from (14).Note that the phase matrix P does not contain exponential functions with large positive indices and hence the numerical instability usually encountered in the conventional transfer matrix method (TMM) can be avoided.This is a crucial point for proper application of MRRM in high-frequency dynamic analysis of structures.Finally, the electric admittance (or electric impedance) of single PZT patch can be obtained as follows: The detailed derivation can be found in [55] and omitted here for brevity.Numerical results and experimental measurements have validated the effectiveness and precision of the present accurate EMI model.As observed in Figure 4, the two curves obtained by TMM and RMM, respectively, can hardly be distinguished in the low-frequency range less than about 13 kHz.However, in the high frequency range ( f > 13 kHz), numerical instability appears for TMM, in contrast to the well-performed MRRM.The experimental results are further compared with analytical prediction of the present model in Figure 5 in the frequency range of 19-33 kHz.It is obvious that most experimentally observed peaks of impedance signatures related to prominent resonance frequencies can be predicted well using the analytical model.Furthermore, the present model can detect the damages in the beams (see Figure 6) and can locate the damages integrated with the curvature mode shape method [64] (see Figure 7).In Figures 6 and 7, D means effective uniform damage magnitude through certain beam segment [65].The effects of interfacial properties are also investigated as shown in Figure 8 (Γ is the shear lag parameter [48,55]).Due to imperfect bonding, the impedance signatures change significantly.Furthermore, the accurate EMI model has been extended to Mindlin-Herrmann rods [52], Timoshenko beams [54], cracked continuous beams [56], and framed structures [53], and some significative research results have been obtained for structural health monitoring.
Determination of Parameters
In EMI technique, it is very important to select available PZT patches for structural health monitoring.Because one side of the PZT patch is to be bonded onto the monitored structure, the electrode of this side should be wrapped to the other side of the patch [5].The size of the PZT should make the PZT transducers small enough not to be intrusive; that is, they do not significantly affect the dynamic properties of the host structures [66].Thus, it is found that PZT patches of size ranging from 5 to 15 mm and thickness from 0.1 to 0.3 mm are best suitable for detecting damages in most structures such as steel and RC structures.
As mentioned in the previous section, the specific advantage of the EMI method over the other SHM techniques Advances in Civil Engineering is its high sensitivity to incipient damages.Thus, it is necessary for the wavelength of excitation to be smaller than the characteristic length of the damage to be detected [67].In general, the electrical impedance is measured at high frequencies in the range of 30-400 kHz [20].Under this high-frequency range, the wavelength of the excitation is small and sensitive enough to detect minor changes in the structural integrity.In EMI method, a frequency range containing 20-30 peaks seems suitable to choose, because a higher density of modes implies that there contains more structural information about the condition of a structure [12].A frequency range higher than 200 kHz is found to be favorable in localizing the sensing, while frequencies range lower than 70 kHz covers a larger sensing area.Peairs et al. [68] remarked that the frequency ranges are usually selected by trial and error, which often involves inducing a removable amount of simulated damage.Their investigation for frequency range selection indicated that the ranges with the sensors/actuators resonances are better for monitoring with the impedance-based method.Due to the high frequency of excitation used in EMI technique, the monitoring range of effective sensitivity of the PZT transducer is limited to its near vicinity [67].Based on the knowledge acquired through various case studies, it has been estimated that the sensing area of a single Advances in Civil Engineering PZT can vary anywhere from 0.4 m (sensing radius) on composite structures to 2 m on simple metal beams [20].This localized nature of the sensing region provides an advantage in that the impedance sensor is less sensitive to boundary condition changes or any operational vibrations, which usually affect lower-order global modes.On the other hand, this characteristic of limited sensing range usually demands an active sensing network system for real world applications [69][70][71][72][73].
In real life, practical structures are constantly subjected to some form of external action such as external loading and temperature change.The experimental and statistical investigation showed that the EM admittance signature obtained for a constantly loaded structure is different from that obtained when damages are present in the structure and the susceptance signature is a better indicator than the conductance signature for detection damages in the structures [74].
Although regular piezoelectric patches have been found to be unsuitable for damage detection at cryogenic temperatures through a series of experiments and an alternative type of transducer based on smart materials should be sought [75], the EMI technique can still be used to actively monitor the damages in the structures, even with the presence of significant temperature variation in the normal temperature range (25 Actually, almost all available transducers are small PZT patches in the EMI method, but some special sensors/actuators such as piezoceramic inertial actuators [76], piezoelectric stack transducers [77], and cement-based piezoelectric ceramic composites [78] are employed to satisfy practical demands or match to the host structures for structural health monitoring.Furthermore, the conventional EMI approach that consists of running wires between the local sensors and a data acquisition system will no longer be trivial.The cost associated with management and maintenance of such a system can be very high.Thus, an impedance-based wireless sensor node for structural health monitoring was developed by Mascarenas et al. [79] for the first time. Although EMI method is very sensitive to minor damages in the structures and the EM signature change can be observed visually, it is necessary to employ statistical techniques to quantify it.It is wellknown that many types of nonparametric indices such as root mean square deviation (RMSD), mean absolute percentage deviation (MAPD), covariance (Cov), and correlation coefficient (CC) have been considered to quantify changes in the EMI admittance signatures [80].Among these nonparametric indices, RMSD seems to be the most suitable damage index to characterize structural damages [80] and has been employed by many researchers for structural health monitoring [72,74,[81][82][83][84].Furthermore, a hybrid technique integrating neural network features with the impedance method has been proposed for somewhat quantitative damage analysis [85].In this damage identification scheme, the impedance-based method detects and locates structural damage and provides damage indication in a green/red light form with the use of the modified RMSD firstly, and then the neural networks are used to estimate the severity of structural damage.
A masonry wall under step loading was investigated by using EMI method [15].Five PZT patches are employed on one side of the wall.Four PZT patches are bonded in the corners and an additional PZT in the center.The multiple cracks of the wall appear with the loading increasing.It can be seen that EMI measurements are very sensitive to the presence of damage and from the observations and the damage metric charts the location of the damage can be approximately predicted.
Lim et al. [90] employed a new method for structural identification and damage detection using smart piezoelectric transducers.In this method, the mechanical impedance can be derived using 1-D and 2-D EMI coupling equations.The feasibility of damage detection was well demonstrated through the application on various laboratory-sized engineering structures such as an aluminum beam, an aluminum truss, and a concrete cube.
The experimental investigation for a concrete beam and a concrete slab by Tseng [73] showed that the PZT wafers were able to detect cracks on the surface as well as in depth.When the PZT patches are too far or too close to the damage, the wafers appear not capable of detecting the Advances in Civil Engineering damage successfully.In addition, using RMSD index, this technique can give a good indication of the severity and location of the damage even when it is in the early stage.Similarly, Giurgiutiu et al. [91] applied piezoelectric wafer active sensors to aging aircraft structures to monitor the onset and progress of structural damage such as fatigue cracks and corrosion.
Pohl et al. [92] implemented an experimental and theoretical investigation to show the effectiveness of the impedance method in monitoring carbon fiber reinforced polymer (CFRP) composites.Damage, which was introduced by the low-speed impact, was detected by changes in the impedance signatures.The other type damages in CFRPs such as fiber fracture and delamination can also be identified by utilizing electrical impedance tomography [93].
The feasibility of the EMI sensing technique for strength gain monitoring of early-age concrete was also presented by Shin and Oh [94].The experimental results showed that the EMI signature is sensitive to the strength development of early-age concrete and the RMSD value has also a strong correlation with the amount of the strength development of early-age concrete.
Due to the high-frequency excitation, the EMI-based health monitoring technique is very sensitive to minor defects in a structure and not affected by any far-field changes.The method has been successfully applied to various structures ranging from aerospace [29,95] to civil structures [1,7,14,15,94] and is ideal for tracking and online monitoring of damages in various structures
Summary
The overview of the development and applications of the electro-mechanical impedance-based structural health monitoring is presented in the paper.Although EMI method is very sensitive to incipient damages in the structures, it has been primarily developed only for qualitative health monitoring and fails to correlate changes in the signatures to physical parameters of structures.In order to develop an ideal robust damage detection scheme by using piezoelectric signatures, an analytical model for simulating the smart structural system is necessary for monitoring system.First, some conventional EMI models and their applications are discussed and an accurate EMI model based on MRRM is further suggested by authors.Comparison with the other numerical results and experimental data validates the present EMI model.The effects of PZT size, excitation frequency range, sensing range of PZT patch; and external action on EMI structural health monitoring technique are then remarked; the most part of discussions may also be found in other references.Finally, the feasibility of implementing the EMI method to detect damages in various lab-sized structures is demonstrated.In the future research, we should pay more attention on the testing of real structures under practical conditions rather than laboratory tests.Moreover, appropriate high-frequency structural theories shall be developed to adapt to the frequency range used in the EMItechnique, which is much higher than that implied in the conventional structural theories.
Figure 1 :Figure 2 :
Figure 1: The sketch of a PZT patch bonded onto a damaged structure.
Figure 3 :
Figure 3: Nonhomogeneous beam with adhesively bonded PZT patches and local coordinates.
Figure 5 :
Figure 5: Experimental and analytical impedance spectra for a steel beam.
Figure 8 :
Figure 8: EM admittance signatures for various interfacial conditions. | 6,448.4 | 2010-03-07T00:00:00.000 | [
"Engineering"
] |
Gap acceptance behavior of drivers at uncontrolled T-intersections under mixed traffic conditions
Explicit traffic control measures are absent in uncontrolled intersections which make them susceptible to frequent conflicts and resulting collisions between vehicles. In developing countries like India, drivers at such intersections do not yield to higher priority movements which cause more crashes between vehicles. The objective of this study is to analyze and model the gap acceptance behavior of minor street drivers at uncontrolled T-intersections considering their aggressive nature. Three intersections in the northeast region of India have been selected as the case study area. Preliminary analysis of the data revealed that drivers behave aggressively, not because they have to wait for a long time at the stop line, but because of their lack of respect for traffic rules. Binary logit models are developed for minor road right turning vehicles which show that gap acceptance behavior is influenced by gap duration, clearing time and aggressive nature of drivers. The equations obtained were used to estimate the critical gaps for aggressive and non-aggressive drivers. Critical gaps are also calculated using an existing method called clearing behavior approach. It is also shown that the estimation of critical gap is more realistic if clearing time and aggressive behavior of drivers are considered.
Introduction
Intersections can be broadly classified into two categories based on traffic control measures-(1) signalized intersections (intersections controlled by traffic signals) and (2) unsignalized intersections; the latter are again classified into (a) uncontrolled intersections, (b) stop sign controlled intersections, (c) yield sign controlled intersection and (d) roundabout. In India, the majority of intersections are uncontrolled. The stop signs are observed at the minor approaches in some intersections. But, in many cases, drivers do not stop or slow down and yield the right of way to the major road traffic. As a result, the major road vehicles are bound to slow down or sometimes even stop to avoid a collision. In these non-standard circumstances, movements at these types of intersections are uncontrolled, so these forms of intersections are also considered as uncontrolled intersections in India.
Gap acceptance is usually considered at junctions where a minor street intersects a major street. If a minor street vehicle has just arrived at the junction, it may clear the intersection while rolling; otherwise, it starts the movement from rest. Drivers intending to perform simple crossing or merging maneuvers are presented with a lag and a series of gaps between vehicles in a conflicting traffic movement. The pattern of arrivals of the major street vehicles creates time gaps of different values. A gap (Fig. 1) between two vehicles is the distance between the rear bumper of the first vehicle and the front bumper of the following vehicle and is usually measured in seconds [1]. Lag (Fig. 2) is defined as the time interval between the arrivals of vehicles at a stop line of minor road and the arrival of the first vehicle at the upstream side of the conflict zone [2]. An important parameter related to gap acceptance behavior is the 'critical gap' which is the minimum acceptable gap to a driver intending to cross a conflicting stream. In this study, the definition used for the critical gap is the gap size that is equally likely to be accepted or rejected by the driver. In other words, the gap duration corresponding to the 50th percentile of the gap acceptance probability distribution is considered as critical gap [3,4].
Critical gap estimation becomes complex in heterogeneous traffic condition. Traffic characteristics under mixed traffic situation vary widely regarding speed, maneuverability, effective dimensions and response to the presence of other vehicles in the traffic stream. Vehicles such as two-wheelers often squeeze through the minimum possible gap and try to clear the intersection in a zigzag manner. A single gap in the major traffic stream may be accepted by more than one vehicle moving one after another even though it is not large enough to let more than one vehicle to clear the intersection. As a result, the major road vehicles are sometimes forced to stop to let the minor road vehicles to clear the intersection. The combined effect of all these issues makes it tough to estimate the critical gap. These situations necessitate a re-look into the factors that influence the gap acceptance behavior at uncontrolled intersections where priority rules are often neglected.
This study is focused on developing logistic regression models suitable for uncontrolled intersections in developing countries like India. The response variable is the gap acceptance or rejection of a right turning vehicle from a minor road (left-hand drive rule followed in India), and the independent variables considered are gap duration, type of interval accepted by the minor street vehicle's driver (gap or lag), forced entry of the minor street vehicles and clearing time (CT). Additionally, the values of the critical gap are estimated using clearing behavior approach [5] and compared with those obtained by logit model.
Literature review
Several methods have been developed by researchers during the past decades on gap acceptance and most of these methods assumed the drivers to be consistent. Moreover, those studies have been done under homogeneous traffic conditions. Various methodologies that have been developed so far can be broadly classified as shown in Fig. 3. A brief literature review of the past relevant studies is presented in the subsequent paragraphs. The review is grouped into studies focussing on probabilistic approach, and analysis conducted under mixed traffic condition.
The probabilistic approach takes into account the fact that the gap acceptance behavior depends not only on intersection characteristics, vehicular characteristics, opposing flow, type of control, but also on qualitative Maze [6] modeled the gap acceptance behavior using a logit model which closely approximates the probit model. Madanat et al. [7] proposed queuing delay as a new parameter describing the elapsed time between joining the queue and arriving at the intersection stop bar. Stop bar delay have also been included in the proposed gap acceptance logit models. Brilon et al. [8] gave a comparison of lag, Harder, Raff, Ashworth, logit and probit method, Hewitt, maximum likelihood procedure and Siegloch methods of critical gap estimation. Gattis and Low [9] compared Siegloch, Greenshields, Raff, acceptance curve, and logit methods to derive critical lag and gap values. Zohdy et al. [10] analyzed the effects of wait time and rain intensity on drivers' gap acceptance behavior. They used logit models to study the gap acceptance behavior. The logit models developed revealed that the acceptable gap duration decreases as a function of driver's wait time at the intersection and increases as the rain intensity increases. Devarasetty et al. [11] made an effort to model gap acceptance behavior of drivers by logistic regression using various traffic and geometric characteristics. A binary logit model using all gap and lag data was developed, and the gap acceptance behavior was found to be influenced by a gap or lag, and two separate models for gap and lag were developed. Serag [12] used a gap/lag acceptance binary logit model considering the aggressive behavior of drivers as a factor which influences the probability of acceptance of a gap or lag. Kaisy and Abbany [13] had also investigated the aggressive behavior of minor street drivers at priority unsignalized intersections. A behavioral model is formulated which is incorporated into a simulation framework to estimate the delay and conflict measures at unsignalized intersections. Liu et al. [14] considered a fourlegged intersection to investigate the factors affecting through stream vehicles' preemptive/yielding decisions when it comes across another vehicle on the conflicting through stream. Among all the parameters found to be significant, the difference in approach speed between the conflicting straight moving vehicles is found to be the most influencing parameter affecting driver's preemptive/yielding decisions.
Ashalatha and Chandra [5] has developed an alternate procedure for estimation of critical gap known as 'clearing behavior approach (CBA)' which can be used for Indian road condition. Amin and Maurya [15] calculated the critical gap using logit model along with others methods and compared them. Sangole et al. [16] used an adaptive neuro-fuzzy interface system (ANFIS) approach to model the gap acceptance behavior of two-wheelers at uncontrolled intersections. Patil and Sangole [17] studied the behavior of twowheelers at limited priority uncontrolled T-intersections using various approaches along with logit method. The critical gap values estimated for young drivers was significantly less compared to middle and old age drivers.
The literature review [12][13][14] revealed that very few studies are available which considers the aggressive [5,[15][16][17], but the aggressive behavior of drivers has not been specifically considered yet. The present study focuses on the effect of aggressive driving behavior on critical gap at uncontrolled intersections. The critical gap thus obtained may be used to estimate the capacity of such intersection more realistically.
Study of selected intersections
Three uncontrolled T-intersections, viz. two in Silchar city (named as A and B) and the third in Guwahati (named as C) are selected as the case study area. The geometrical features and traffic composition of the intersections A, B and C during peak hours (10:00 am-12:00 noon) are shown in Fig. 4a-c, respectively. The movements EW (east to west), SE (south to east), etc. are shown along with peak hour traffic volumes in parenthesis. The number of vehicles is converted into passenger car unit (PCU) values to account for the heterogeneity of the traffic. The minor roads at all the intersections are of width 3.5 m. The major road at intersection A is two-lane undivided, whereas, at intersections B and C, it is four-lane divided. All approaches of each intersection have sufficient sight distance and are on level ground. No side friction, such as vehicle parking and bus stops, is observed at intersections A and C at the time of data collection. However, on-street parking was seen on the major road of intersection B. As a result, the effective carriageway width of the major road at intersection B is reduced from 7 to 5 m. The upstream and downstream intersections are sufficiently away from the study intersections.
The traffic scenario at the selected uncontrolled intersections is found to be very complex. So, a new understanding of the situation is deemed necessary. After careful observation, the following strategies have been adopted for modeling the gap acceptance behavior under mixed traffic condition using a logit model.
Consideration of clearing time in logit model under mixed traffic condition
The minor road vehicles at the selected intersections are found to clear the intersection in an unusual manner. The time required to clear the intersection area is varying over a wide range of values. Thus, the value of gap accepted will depend on the time needed in clearing the intersection. The concept of the clearing phenomenon of the minor street driver has been adopted from Ashalata and Chandra [5]. The influence area in an uncontrolled intersection is termed as influence area for gap acceptance (INAFOGA) which has a rectangular shape. A detailed description of the INAFOGA is given in Sect. 4. A right turning vehicle from the minor street waits at position A marked in Fig. 5. To clear the intersection safely, it should accept a gap/lag which gives enough time for its back bumper to cross the point P [5]. However, it has been observed in our case study area that the minor street vehicle chooses a gap or lag if the time interval is large enough for it just to cross the INAFOGA. So, the vehicle is considered to have cleared the intersection if the back bumper just reaches the green line of the INAFOGA from position A.
3.2 Gaps need to be measured from the back bumper of the leading vehicle to the front bumper of the following vehicle The speed of major road traffic has been found to drop to about 20 km/h when the traffic volume becomes very high. At such low speed, the difference between the values of the Therefore, gaps have been measured from the back bumper of the leading vehicle to the front bumper of the following vehicle which is more realistic than taking headway as a gap, irrespective of the speed of vehicles.
Consideration of forced entry and ideal entry separately
A minor street vehicle is considered to have made a forced entry into the intersection area when it forces the major road vehicles to slow down or sometimes even come to a complete stop to clear the intersection (Fig. 7). However, clearing the intersection without interrupting the flow of major road vehicles is taken to be an ideal entry. Under mixed traffic scenario, forced entry is quite a common phenomenon. As a result, these two types of entries have been considered separately in this study to calculate the percentage of aggressive drivers at these intersections.
Data collection and extraction
Videographic survey was carried out for data collection. Data were collected in the month of September and October 2016. Video recording was done during peak hours (10:00 am-12:00 noon). The video camera was so placed that all movements of the vehicles could be recorded. The available modes at those intersections were twowheelers, auto rickshaws, and four-wheelers. Cycle-rickshaws and heavy vehicles were rarely observed at the minor approaches of those intersections, and hence were not considered in the analysis. After the video shooting of the uncontrolled T-intersections, extraction of relevant decision variables was carried out based on the concept of 'INAFOGA' as given by Ashalatha and Chandra in their theory of gap acceptance under mixed traffic conditions in India [5]. The video data collected from the field was played in a video player named as KM Player capable of running videos at a frame rate of 25 frames per second. The time frames extracted from survey video were then compiled and entered into an MS Excel spreadsheet and the following decision variables were calculated:
Preliminary data analysis
Data are extracted from the video, and a set of 1414 observations have been recorded for all the selected study area. Out of these, the accepted gap/lag data are used to understand the aggressive behavior of the minor street drivers and a statistical summary is presented in Table 1.
The primary statistics obtained from Table 1 are as follows: (a) The percentage of two-wheelers at intersection A was 54%, whereas intersection B had 58% two-wheelers and intersection C had 56% four-wheelers. (b) The percentage of vehicles showing aggressive behavior is found to be quite high (Table 1). 24% two-wheelers at intersection A, 22% two-wheelers at intersection B and 18% four-wheelers at intersection C are found to have shown aggressive behavior. A new parameter 'forced entry (F)' is introduced to address the aggressive behavior of the minor street drivers. (c) The percentage of aggressive drivers forcing themselves through in the first available gap (i.e., lag) at intersections A, B, and C are 73%, 53% and 31%, respectively. (d) The percentage of aggressive drivers who had to reject three or more than three gaps (which includes the lag) at intersection A, B and C are 4%, 23%, and 22%, respectively.
Based on the statistics mentioned above, the following conclusions (1-4) are drawn: (1) Only the vehicle categories with higher proportion have been selected for each intersection; i.e., twowheelers at intersections A and intersection B and four-wheelers at intersection C. (2) No direct relation between aggressive behavior and the number of rejected gaps is evident from the data as the maximum forced entry occurs with zero rejected gap (i.e., lag) at all the intersections. It can be said that the minor street drivers behave aggressively not because they have to wait for a long time, but because of their lack of respect for traffic rules. (3) A significant amount of vehicles (37%-75%) are found to be entering the intersection forcibly or ideally at the first available gap, i.e., lag, so, a separate parameter 'gap/lag (I GL )' is taken which indicates whether the driver has accepted a gap or lag. (4) The percentage of aggressive drivers accepting 'lag' is the highest at intersection A. This suggests that a vast number of the minor road drivers clear the intersection area as soon as they reach the intersection. The vehicles approaching from the minor road pay less attention to the major road traffic and do not wait for a suitable gap to clear the intersection safely. Thus, if we compare these three intersections, the major road gets the least priority at intersection A (73%) and the highest priority at intersection C (31%).
The gap acceptance behavior of two-wheelers (intersections A and B) and four-wheelers (intersection C) at forced and ideal entry situations are graphically shown in Fig. 9.
The cumulative percentage of gap acceptance of aggressive and non-aggressive drivers is plotted with respect to gap duration. All the aggressive drivers are found to have accepted a gap less than or equal to 6 s, whereas non-aggressive drivers accept gaps as high as 11 s. Additionally, it is evident from the graph that for a given gap, a higher percentage of aggressive drivers accept the gap than the non-aggressive drivers. It indicates that the aggressive behavior of drivers affects their gap acceptance decision. Based on the results obtained by preliminary analysis of the data and field observations, the following utility explanatory variables are considered in this study to address the traffic condition prevalent in Indian roads ( Table 2).
Distribution of gaps
Gap acceptance data of two-wheelers (for intersections A and B) and four-wheelers (for intersection C) are tried to fit into a normal distribution, lognormal distribution, gamma distribution, Dagum distribution and Dagum (4p) distributions separately for each intersection. Kolmogorov-Smirnov test (K-S test) was performed on the gap acceptance data to measure the goodness of fit of these distributions. The K-S test statistic of fitting these distributions is presented in Table 3. The critical value at 95% confidence level for each intersection is also given in Table 3. The critical value depends on the sample size which is provided in the parenthesis along with the critical values in the last column of Table 3.
As may be seen, at 95% confidence interval, Dagum distribution has the lowest K-S test statistic for twowheelers, whereas Dagum (4p) distribution has the lowest K-S test statistic for four-wheelers. Moreover, all the K-S values for Dagum and Dagum (4p) distributions are quite lower than the critical values. Thus, it is concluded that the gaps accepted by two-wheelers follow Dagum distribution, whereas, in the case of four-wheelers, it is Dagum (4p) distribution.
Gap acceptance model
A driver approaching an uncontrolled intersection through the minor road observes a lag and numerous gaps in the major roadway. The driver evaluates the lag/gap on the major road and makes a choice whether to accept or reject it. This decision to accept/reject a gap varies from driver to driver, and it is considered to be random. Moreover, binary explanatory variables such as type of interval accepted by the driver (gap or lag), aggressive or non-aggressive maneuvers, which are used to address the driver characteristics can be incorporated into the logit model. Logistic regression is used to formulate the model based on such discrete choice behavior phenomenon which is explained in the subsequent paragraphs.
Model structure
To find out a sufficient gap in the major road traffic, minor street drivers need to choose between the two alternatives, i.e., 'i' and 'j', where i means accepting the gap for crossing or merging maneuver and j means rejecting the gap.
A driver waiting to make a maneuver has a utility for accepting or rejecting a given gap. If the driver accepts a gap, he/she can avoid any further delay at the intersection, whereas rejecting the gap will increase safety because taking a short gap can be risky. The total utility (U) is considered as an additive combination of a deterministic term (i.e., observed utility (V)) and a random term (i.e., unobserved utility (e)) [18]. A simple utility function for accepting and rejecting a gap is given by Eqs. (1) and (2), respectively: where U i is the total utility for accepting a gap and U j the total utility for rejecting a gap. The deterministic component (V i ) is the observed utility, which is a function of different variables (X ik /X jk ) that affect gap/lag acceptance. This utility function can be expressed as Eqs. (3) and (4): where a; b 1 ; b 2 ; . . .; b k are unknown parameters to be estimated; X ik is the kth attribute in case of acceptance; X jk is the kth attribute in case of rejection; and k is the number of attributes.
Model estimation
As discussed in the preliminary data analysis section, twowheelers from intersections A and B and four-wheelers for intersection C have been considered for gap acceptance modeling. Totally, 162 observations for two-wheelers at intersection A, 292 for two-wheelers at intersection B, and 304 for four-wheelers at intersection C are recorded. Then, 80% of these observations are randomly selected to develop the model, and the rest has been kept for model validation. Logistic regression is carried out by using SHAZAM to obtain the gap acceptance models. The binary variable I GL , indicating whether a gap or lag has been accepted, was not found to be significant, thus not included in the models. Gap acceptance models are also developed considering gap duration and clearing time. Forced entry into the intersection is not considered in these models, which mean that all the minor street drivers clearing the intersections are deemed to behave alike. The statistical results of the most significant models are reported in Tables 4 and 5. Log-likelihood function, McFadden R 2 values, percentage of right predictions and Chi-squared statistics are also shown in the tables.
The models in Table 4 show that the gap acceptance probability increases with an increase in the gap duration 'G' and a decrease in the clearing time (T c ). It is so because accepting a larger gap is easier which increases the probability of gap acceptance. The likelihood of accepting a gap increases with a decrease in clearing time because it becomes easier for drivers to take smaller gaps. The tstatistic values show that the weight of 'G' is more than that of 'T c ' at all the intersections. Given values of 'G' and 'T c ', the positive sign of the coefficient of forced entry 'F' shows that aggressive drivers have a larger probability of accepting a gap as compared to non-aggressive drivers.
The models in Table 5 are developed considering gap duration and clearing time only. McFadden R 2 values and percentage of right predictions are found to be lesser than the corresponding values in Table 4.
Model validation
The models are validated using 20% randomly selected data from complete collected data for all the selected locations. Selections of the 20% random data are different for different intersections. The 20% data are taken for The probability values derived from the models were rounded to 0 or 1 to compare with the actual observation. It is assumed that, if the probability of accepting a gap is less than 0.5, the gap is rejected, and it is designated as 0.
Similarly, if the probability is found to be greater than or equal to 0.5, the gap is accepted, and it is identified as 1.
Type I error, type II error, sensitivity and specificity are also calculated for each of the prediction models. Type I error is said to have occurred when the null hypothesis is rejected, but it is, in fact, true. Type II error occurs when a null hypothesis is accepted, but it is, in fact, false. Sensitivity (one minus type II error) represents the ability of a model to identify correctly whether a gap is accepted, whereas specificity (one minus type I error) shows the ability of a model to identify correctly whether a gap is rejected. The prediction success table for the three intersections is presented in Tables 6 and 7. The values of sensitivity and specificity are above 80% in all the models which indicates that the models perform reasonably well in predicting whether a gap would be accepted or rejected.
Estimation of critical gap
The critical gap is computed by setting the probability of accepting a time interval to 0.5 from the given equations (Tables 4,5). The values of critical gap obtained by various procedures are shown in Table 8.
It is found that the average value of clearing time of vehicles at intersections A, B and C are 2.55 s (twowheelers), 2.05 s (two-wheelers) and 3.75 s (four-wheelers), respectively. The critical gap values are estimated for each intersection considering the average values of clearing time. The critical gaps are estimated using the equation set I for aggressive and non-aggressive drivers. Critical gap values were also estimated using equation set II in which aggressive behavior of drivers is not considered. The estimated critical gaps are shown in Table 9.
Clearing behavior approach has proven to give satisfactory results in mixed traffic conditions so far [5,15]. The clearing time curve (1-F ct , where F ct is the cumulative frequency distribution curve for clearing time) and the corresponding gap acceptance cumulative frequency curve (F a ) intersect at a point which indicates a situation when clearing time is just equal to the gap accepted. The time axis coordinate of the intersection point gives the value of critical gap. Figure 10 shows the critical gap estimation by clearing behavior approach for the selected vehicle categories in the study areas. The values are presented in Table 9.
It is observed from Table 9 that the values of critical gap in column A is less than column B while using the equation set I. That is because aggressive drivers attempt to clear the intersection by taking a gap which might force the major road vehicles to either slow down or even come to a complete stop. A non-aggressive driver under similar circumstances would have waited for a larger gap to clear the intersection safely. As a result, the critical gap of aggressive drivers is found to be smaller than that of nonaggressive drivers. Another observation is that the critical gap values obtained by equation set I for non-aggressive drivers is greater by 4.44%-14.61% as compared to those given by equation set II. These values are also found to be greater by 1.62% to 5.40% than the values obtained by the clearing behavior approach. The values obtained by equation set II are found to be the lowest among the three methods. The results suggest that the clearing behavior approach gives higher values of critical gap than the logit method if the aggressive behavior is not taken into consideration. This observation is consistent with the studies under mixed traffic conditions [5,15]. However, incorporating aggressive behavior helps to visualize the actual scenario because the critical gaps can be obtained for aggressive and nonaggressive drivers separately.
Another observation is that the value of critical gap achieved by any approach for two-wheelers is lower in intersection B as compared to intersection A. A possible reason for this is the side friction on the major road which reduces the speed of vehicles. Hence, smaller gaps are accepted by minor street drivers at this intersection.
Summary and conclusion
In this paper, gap acceptance behavior analyses of twowheelers and four-wheelers at uncontrolled T-intersections are presented. The videographic survey was carried out at three uncontrolled intersections with the help of video camera-two in Silchar, and one in Guwahati. The purpose was to model gap acceptance behavior of drivers and to find the critical gaps which are widely used in the intersection operational analysis and capacity estimates. Erratic maneuvers in the intersection area and aggressive driving are two common behavior of drivers observed at these intersections. Preliminary analysis of the data revealed that the gap accepted by two-wheelers follow Dagum distribution, whereas, in the case of four-wheelers, it follows Dagum (4p) distribution. It was also concluded by analyzing the data that drivers behave aggressively because of their lack of respect for traffic rules, rather than due to drivers losing his patience because of unavailability of a suitable gap.
Binary logit models were developed for two-wheelers at intersections A and B and four-wheelers at intersection C, to predict the probability of accepting or rejecting a given gap or lag. The manner in which a driver clears the intersection is not consistent at these intersections, thus affecting the value of critical gap. Apart from considering the gap duration which is an obvious factor, the variables considered in the models are clearing time and aggressive nature of drivers (forced entry). The variable, 'forced entry' of minor street vehicles, which had not been introduced in previous studies under mixed traffic condition, was found to be significant in the models. The model analyzes yielded critical gap in the range of 2.93-4.79 s for non-aggressive drivers, whereas the values are in the range of 2.02-2.40 s for aggressive drivers. The critical gaps were also obtained using logit model without considering the aggressive behavior of drivers. The values were in the range of 2.80-4.09 s. Clearing behavior approach was also used to determine the values of critical gap at these intersections. It is found that the results obtained by the proposed method help in differentiating between aggressive and non-aggressive drivers at an uncontrolled intersection.
The data extraction procedures and the analysis presented in this study can be implemented at uncontrolled intersections in countries where mixed traffic condition exists. Moreover, the methodology adopted in this study addresses the aggressive behavior of drivers. Considering the scarcity of studies on the aggressive behavior of drivers, this approach can be a valuable reference for similar studies at uncontrolled intersections where rules of priority are often neglected. Further studies are underway to analyze how the speed and type of oncoming vehicles affect a driver's decision-making. In this study, only minor street right turning movement at T-intersections has been considered; the procedure can be extended to analyze the gap acceptance behavior of major street right turning vehicles as well. Studies on four-legged intersections and effect of other parameters such as geometric features, side friction, driver's characteristics can be taken into account to gain further understanding of traffic behavior at uncontrolled intersections.
Open Access This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http:// creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. | 7,121.8 | 2018-06-01T00:00:00.000 | [
"Engineering",
"Environmental Science"
] |
Gas Chromatography–Mass Spectrometry-Based Analyses of Fecal Short-Chain Fatty Acids (SCFAs): A Summary Review and Own Experience
The gut microbiome, crucial to human health, changes with age and disease, and influences metabolic profiles. Gut bacteria produce short-chain fatty acids (SCFAs), essential for maintaining homeostasis and modulating inflammation. Dysbiosis, commonly due to poor diet or lifestyle, disrupts the integrity of the intestinal barrier and may contribute to conditions such as obesity, diabetes, and non-alcoholic fatty liver disease (NAFLD). Analytical methods such as gas chromatography–mass spectrometry (GC/MS) are vital for SCFA analysis, with various preparation and storage techniques improving the accuracy. Advances in these methods have improved the reliability and sensitivity of SCFA quantification, which is crucial for the identification of disease biomarkers. Evidence from GC/MS-based studies has revealed that accurate SCFA quantification requires meticulous sample preparation and handling. The process begins with the extraction of SCFAs from biological samples using methods such as direct solvent extraction or solid-phase microextraction (SPME), both of which require optimization for maximum recovery. Derivatization, which chemically modifies SCFAs to enhance volatility and detectability, is a crucial step, typically involving esterification or silylation. Following this, the cleanup process removes impurities that might interfere with the analysis. Although recent advances in GC/MS technology have significantly improved SCFA-detection sensitivity and specificity, proper sample storage, with acid preservatives and the avoidance of repeated thawing, is essential for maintaining SCFA integrity.
Introduction
Multi-omics is a method of analysis that allows for the combining and analyzing of data obtained from two or more omics methods (e.g., metagenomics, metabolomics, or transcriptomics) to search for and understand the mechanisms of biological processes leading to the development of metabolic diseases in humans [1].The central tenet is that multi-omics data may help us track related molecular changes at different biological levels with genetic variants [2].A large amount of data received allows for better interpretation and visualization of the results obtained from the same biological sample [3].The data may also be used to look for relationships between the host and its inner microbiome, the composition of which changes with age.The development of metabolic diseases also leads to a change in the composition of the microbiota, which translates into changes in its metabolomic profile.Continuous development of analytical methods allows for the determination of an increasing number of metabolites produced by bacteria, the impact of which on the functioning of the human body has not been fully determined yet.Gut bacteria are the largest group of micro-organisms living in the human gastrointestinal tract.The gut microbiome (GM) contains about 10 15 microbial cells and over 22 million microbial genes, both of which exceed the number of cells and genes in a human [4].Such a large number of genes allows bacteria to produce a wide range of metabolites with various biological activities that perform very important roles, ranging from the synthesis of vitamin K and group B vitamins, short-chain fatty acids, amino acids (AAs) and secondary bile acids to anti-inflammatory mediators and many more.An analysis of human gut bacteria for B vitamin biosynthesis pathways showed that 40 to 65% of all bacteria were capable of synthesizing all eight B vitamins [5].The intestinal microbiome can also synthesize phenylalanine and a tyrosine derivative, i.e., dopamine, which may be converted into norepinephrine and epinephrine.The role of the microbiome is crucial in maintaining the human body in homeostasis due to the production of signaling metabolites.In addition, gut bacteria secrete mucins that prevent the colonization of the gut lumen by harmful bacteria which may produce hazardous compounds [6].The depletion of gut microbiome may result from various factors, such as an unhealthy, Western-style diet, full of processed food rich in carbohydrates and high amounts of fat, lack of movement caused by a sedentary lifestyle, or antibiotic intake which contributes to the occurrence of dysbiosis, characterized by an abnormal change in the composition of gut microbiota on the intestinal surface caused by reduced beneficial bacterial species and increased gut permeability.Various materials may be used for testing: blood, plasma, saliva, cerebrospinal fluid, tissues and urine, with stool being one of the least studied [7].Stool consists of undigested food remains, water, live and dead bacteria, as well as small and large particles resulting from the digestion of food by enzymes and bacteria.These compounds are then absorbed through the gastrointestinal tract (GIT), where, as it turns out, they play a key role in the proper functioning of the human body.These compounds are widely known as stool metabolome, the analysis of which may provide important information about its composition, although it is different in each of us.This is crucial for searching for biomarkers of diseases and for trying to understand the origin of conditions.The stool is easily available and has great potential as a diagnostic material [8], having an added value not only in the diagnosis of intestinal and rectal diseases.Conversely, feces are a heterogeneous and complex material containing different macro-and microcompounds found among undigested food remains.The variety of food consumed by humans affects the composition and levels of these compounds.Therefore, stool can be a challenging material for analysis [7].Changes in the levels of individual metabolites do not necessarily correlate with the severity of the disease, so further research and the search for potential biomarkers are necessary.This is why this review is focused on showing the most current information about the methods of the analysis of short-chain fatty acids by gas chromatography (GC) coupled with mass spectrometry (MS).
The Role of Short-Chain Fatty Acids in the Human Body
Short-chain fatty acids (SCFAs) constitute a group of metabolites that is very often measured in the search for potential biomarkers.SCFAs are the largest group of metabolites produced by intestinal bacteria in the process of anaerobic fermentation.Intestinal colonization begins soon after birth, and its course is influenced by environmental factors such as the mode of delivery, feeding, or the use of antibiotics [9].Research has indicated significant differences in the composition of the microbiota of newborns compared to adults, and its diversity and role have been found to increase most intensively during the first years of life [10].During the first two years of life, three stages of SCFA profile change may be distinguished.The early phase is characterized by low levels of acetic acid and high levels of succinic acid.The intermediate phase is characterized by high levels of lactic and formic acid, while a high concentration of propionate and butyrate occurs in the late phase [9].The delay or formation of a different microflora composition in infants is associated with obesity [11].The loss of Bifidobacterium bacteria, which is the most abundant gut bacteria until weaning, was observed to be associated with decreased autoimmune activity and the possible development of allergic disease.The reduction of other early-life bacteria such as Faecalibacterium, Lachnospira, Veillonella and Rothia, and the resultant intestinal microbial dysbiosis, have been associated with a higher risk of developing asthma [12,13] and the development of type 1 diabetes, which was correlated with lower amounts of genes for carbohydrate fermentation and SCFA production [14].After solid food introduction, the gut microbiota starts to develop at a faster pace and begins to resemble the microbiome of an adult person, but still the domination of Firmicutes and Bacteroidetes phyla is observed in the first two or three years of life, when they make up most of the gut microbiome [15].Even then, the composition of gut bacteria changes from childhood through adolescence.The increased consumption of processed meat at that age is related to lower microbial α-diversity, characteristic of dysbiosis, and also to a greater intake of processed foods (Figure 1).Furthermore, skipping breakfast is associated with the reduced abundance of potentially beneficial taxa known to produce SCFAs [16].SCFAs with straight chains (acetate, propionate and butyrate) are produced by the fermentation of dietary fiber and resistant starch in the intestinal lumen [17].Butyrate is mainly produced by the following genera: Clostridium, Eubacterium and Fusobacterium, but Clostridium leptum, Roseburia spp., Faecalibacterium prausnitzii and Coprococcus spp.are the most productive.Propionate is a metabolite of Bacteroidetes and Propionibacterium [15].Branched-chain SCFAs (isobutyric acid, isovaleric acid and 2-methylbutyric acid) are produced from branched-chain amino acids (leucine, isoleucine and valine).These compounds are absorbed into the systemic circulation by passive diffusion and active transport, where they influence appetite regulation by binding to the G-protein-coupled free fatty acid receptor 3 (FFAR3) and stimulate leptin secretion by the adipose tissue [18].Thus, they take part in the maintenance of energy homeostasis.is associated with obesity [11].The loss of Bifidobacterium bacteria, which is the most abundant gut bacteria until weaning, was observed to be associated with decreased autoimmune activity and the possible development of allergic disease.The reduction of other early-life bacteria such as Faecalibacterium, Lachnospira, Veillonella and Rothia, and the resultant intestinal microbial dysbiosis, have been associated with a higher risk of developing asthma [12,13] and the development of type 1 diabetes, which was correlated with lower amounts of genes for carbohydrate fermentation and SCFA production [14].
After solid food introduction, the gut microbiota starts to develop at a faster pace and begins to resemble the microbiome of an adult person, but still the domination of Firmicutes and Bacteroidetes phyla is observed in the first two or three years of life, when they make up most of the gut microbiome [15].Even then, the composition of gut bacteria changes from childhood through adolescence.The increased consumption of processed meat at that age is related to lower microbial α-diversity, characteristic of dysbiosis, and also to a greater intake of processed foods (Figure 1).Furthermore, skipping breakfast is associated with the reduced abundance of potentially beneficial taxa known to produce SCFAs [16].SCFAs with straight chains (acetate, propionate and butyrate) are produced by the fermentation of dietary fiber and resistant starch in the intestinal lumen [17].Butyrate is mainly produced by the following genera: Clostridium, Eubacterium and Fusobacterium, but Clostridium leptum, Roseburia spp., Faecalibacterium prausnitzii and Coprococcus spp.are the most productive.Propionate is a metabolite of Bacteroidetes and Propionibacterium [15].Branched-chain SCFAs (isobutyric acid, isovaleric acid and 2-methylbutyric acid) are produced from branched-chain amino acids (leucine, isoleucine and valine).These compounds are absorbed into the systemic circulation by passive diffusion and active transport, where they influence appetite regulation by binding to the G-protein-coupled free fatty acid receptor 3 (FFAR3) and stimulate leptin secretion by the adipose tissue [18].Thus, they take part in the maintenance of energy homeostasis.SCFAs produced by gut bacteria can affect the bioavailability of minerals due to lumen acidification and changes in the amount of transport proteins on the intestinal surface [19].The gut microbiome produces tryptophan, which binds to the aryl hydrocarbon receptor (AhR) and enhances the function of the intestinal epithelial barrier, as well as regulatory immune responses of the human body [6].Butyric acid inhibits histone deacetylases and it is also the main source of energy for colonocytes.Short-chain fatty acids, especially butyrate, can modulate the expression of genes responsible for the synthesis of tight-junction proteins.They also regulate occludin redistribution to prevent increased intestinal permeability [4].Acetic acid is the most abundant SCFA in both intestinal lumen and systemic circulation, where it participates in cholesterol metabolism and lipogenesis [9].After absorption into systemic circulation, propionic acid is transferred to the liver where it is used as a substrate for gluconeogenesis [20].SCFAs also participate in the metabolism of glucose, lipids and cholesterol [21].They are key components for maintaining gut-barrier integrity.The intestinal microbiota is capable of maintaining homeostasis, or it may contribute to disease susceptibility by changing the composition of GM metabolites that may affect host physiology [8].Recent publications have indicated the relationship between dysbiosis, SCFA levels and genetic and immunologic factors that lead to the development of various conditions, mostly in adults, that reduce the patient's quality of life.The conditions include diarrhea [22], obesity [23], irritable bowel syndrome (IBS) [24], inflammatory bowel diseases (IBDs), colon cancer [25], celiac disease [6] and non-alcoholic fatty liver disease (NAFLD), which may progress to non-alcoholic steatohepatitis (NASH) or even cirrhosis as a result of gut-liver axis malfunction and the accumulation of lipids in the liver [26][27][28].Increased levels of trimethylamine-N-oxide (TMAO), a product of AA metabolism, may increase the risk of cardiovascular diseases by promoting atherosclerotic lesion development [29].Lumen bacteria are also important in the development of depression because they can produce neurotransmitters such as serotonin and γ-aminobutyric acid (GABA) that are crucial in neuronal signaling [30].Numerous studies have shown a direct link between dysbiosis and increased gut permeability, which allows the translocation of harmful compounds such as lipopolysaccharides (LPS) and pathogens to enter the inner layer of the intestinal barrier and, finally, to enter the bloodstream via the portal vein.This may disrupt the functioning of the gut-liver axis.It is related to the changes in SCFA production by the intestinal microbiome as it modulates the production of secretory immunoglobulin A (sIgA), a non-inflammatory antibody responsible for the prevention of pathogen invasion [31].Inflammation caused by dysbiosis and pathogens, and that persists for a long time, may induce an inflammatory response that promotes liver injury, fibrosis, cirrhosis and oncogenic transformation, contributing to the development of diseases such as nonalcoholic fatty liver disease (NAFLD), non-alcoholic steatohepatitis (NASH), hepatocellular carcinoma, or primary hypertension (PH) [32,33].NAFLD is the most common liver disease worldwide, estimated to affect up to 46% of the American population [34].Bacteria with pro-inflammatory characteristics such as Proteobacteria, Firmicutes, or Escherichia coli are predominantly present, while protective bacteria such as Faecalibacterium prausnitzii are reduced in NAFLD patients [35].At the bacterial family level, Enterobacteriaceae were reported to have increased, while Rikenellaceae and Ruminococcaceae were reported to have decreased.At the level of bacterial genera, Escherichia, Dorea and Peptoniphilus were reported to have increased, and Anaerosporobacter, Coprococcus, Eubacterium, Faecalibacterium and Prevotella were reported to have decreased [36].The prevalence of NAFLD is growing due to an increasing number of people with obesity and related metabolic disorders, caused by unhealthy lifestyle, lack of exercise and an excessive intake of empty calories [37].This results in insulin resistance due to decreased tissue sensitivity, which may ultimately lead to the development of type 2 diabetes.According to the latest data from the World Health Organization (WHO) from the year 2022, every one out of eight people is obese worldwide, and the number of obese adults has increased more than twice since 1990.It was also emphasized that up to 75% of obese adults and 50% of obese children developed metabolic disorders (Figure 2).Gut bacteria also produce endotoxins that can damage the liver and, thus, induce the promotion of NAFLD.There are three endotoxin-producing strains, i.e., Enterobacter cloacae B29, Escherichia coli PY102 and Klebsiella pneumoniae A7, which overgrow in the gut of morbidly obese patients and which have been shown to induce NAFLD when mono-associated with germ-free mice on a high-fat diet (HFD) [38].Glucagon-like peptide-1 receptor (GLP-1) is another key factor in the regulation of body weight.It is responsible for promoting insulin secretion, insulin sensitivity and β-cell mass, while inhibiting gastric emptying and appetite, and affecting lipid intake [39].The activity of the GLP-1 receptor can be regulated by the gastrointestinal microbiota due to the modulation of incretin hormone glucagon-like peptide-1 levels.Several strains of Enterococcus faecalis produce metabolites which decrease GLP-1 levels [40].Conversely, all GLP-1-positive strains in the human gut were identified as Staphylococcus epidermidis by 16S rRNA sequencing [39].metabolic disorders, caused by unhealthy lifestyle, lack of exercise and an excess take of empty calories [37].This results in insulin resistance due to decreased tiss sitivity, which may ultimately lead to the development of type 2 diabetes.Accord the latest data from the World Health Organization (WHO) from the year 2022, eve out of eight people is obese worldwide, and the number of obese adults has inc more than twice since 1990.It was also emphasized that up to 75% of obese adu 50% of obese children developed metabolic disorders (Figure 2).Gut bacteria al duce endotoxins that can damage the liver and, thus, induce the promotion of N There are three endotoxin-producing strains, i.e., Enterobacter cloacae B29, Escheric PY102 and Klebsiella pneumoniae A7, which overgrow in the gut of morbidly ob tients and which have been shown to induce NAFLD when mono-associate germ-free mice on a high-fat diet (HFD) [38].Glucagon-like peptide-1 receptor (GL another key factor in the regulation of body weight.It is responsible for promotin lin secretion, insulin sensitivity and β-cell mass, while inhibiting gastric emptyi appetite, and affecting lipid intake [39].The activity of the GLP-1 receptor can b lated by the gastrointestinal microbiota due to the modulation of incretin hormo cagon-like peptide-1 levels.Several strains of Enterococcus faecalis produce meta which decrease GLP-1 levels [40].Conversely, all GLP-1-positive strains in the hum were identified as Staphylococcus epidermidis by 16S rRNA sequencing [39].
Methodology of GC/MS Analysis
The most frequently used methods for SCFA analysis include nuclear magnetic resonance (NMR), gas chromatography (GC) and liquid chromatography (LC), with different types of detectors coupled with a mass spectrometer [20].NMR is a highly reproducible method for the analyzed compound, but it is less sensitive than GC or LC methods, which have lower limits of detection (LOD) and quantification (LOQ) [41].This is the main reason why GC and LC are more widely available in laboratories than NMR.Liquid chromatography is characterized by great resolution when complex matrices are analyzed, but GC is still the most commonly used method for SCFA analysis due to its reliability and accuracy [20,41].Other advantages of GC/MS are the relative ease with which analyzed compound separation and identification may be achieved, and its high metabolic coverage [42].
Evidence from GC/MS-Based Studies
In this article, we presented a review of the literature of the analytic methods of SCFAs from studies conducted in the period from January 2018 to March 2024 using GC/MS as the main method of SCFA analysis in stool samples obtained from humans, animals and cell cultures.The summarized data from these publications are included in Table 1.Data extracted from studies using GC/MS methods are shown to highlight the latest developments in the field of SCFA analysis by GC/MS.
Sample Storage before Analysis
Numerous authors of the scientific research included in this review recommended storing stool samples at −80 • C to stop the metabolic activity of gut microbiome in the collected sample, and also to prevent the degradation of the analytes in the sample due to the activity of bacteria at room temperature, mostly microbial fermentation, and also aerobic conditions outside the intestine [42].These are the main reasons why any steps taken before sample preparation for analysis should be performed at low temperatures, preferably on dry ice.Most samples are stored as raw feces, but Hsu et al. and Wang et al. used lyophilized samples for analysis [43,44].However, the best option is to process fresh samples [45].This is not an option in numerous analyses, so most researchers use frozen samples-it is more practical on a day-to-day basis.Only several protocols recommended the storage of samples at −20 • C in the form of fecal water [43] or of the stool sample in case of the acidification procedure [46].Most studies analyzed in this review required sample storage at minus 80 • C to prevent changes in the composition of stool metabolome and to produce more accurate results obtained during GC analysis.
Sample Weight
The main factor driving the sample weight used for GC/MS analysis was the amount of the biologic sample obtained from the patient and the number of procedures in which it was used.With regard to the size, it is hard to obtain large amounts of feces from mice or rats.This factor drives the development of new, more accurate and reliable methods of SCFA quantification.The amount of feces used for analysis ranges from 10 milligrams in patients with pancreatitis [47] to 1 g in other methods of SCFA quantification [12,16].The most common weights used for analysis are 50 and 100 milligrams of feces for human samples [49][50][51], and 10 to 50 milligrams for murine samples [44,52].These values are most often selected because an analytical method must ensure appropriate levels of sensitivity and reproducibility so that the results obtained are reliable and truthful.To prevent the misinterpretation of acquired spectra, the addition of extraction blanks to the analyzed set samples is recommended [42].
Sample Preparation
Feces are a complex and diverse material that contains various metabolites resulting from the metabolism of intestinal bacteria, human metabolism and undigested food residues.Therefore, before starting the GC/MS analysis, SCFAs must be isolated from the sample.The basic method of SCFA extraction involves sample acidification by hydrochloric acid, phosphoric acid, formic acid, or sulfuric acid.It was developed to improve extraction efficiency and peak shape during GC analysis [43].However, a faster loss of column quality is the main disadvantage of this method, contributing to higher analysis costs.To avoid this problem and extend the column life, sample acidification may be used with liquid-liquid extraction (LLE), which is the most frequently chosen method for SCFA isolation in this review.It uses organic solvents to make water-organic, two-phase solutions, which lead to the separation of analyzed compounds, e.g., chloroform, isobutanol, or ether.It is important to note that, because the charge of different compounds may vary with pH, there may not be one ideal pH value to suit all classes of compounds we would like to analyze.Therefore, any pH adjustment should be considered with respect to the experimental aim [42].Suspending a stool sample in an organic solvent and its homogenization ensures proper fragmentation and the effective extraction of metabolites.Numerous researchers have added another step in sample preparation by using derivatization to prepare SCFA samples for analysis.By implementing this procedure, they obtained higher-purity samples for analysis [20].Another advantage of this method is related to the fact that we obtain volatile compounds that are stable at high temperatures, in which GC/MS analysis is usually carried out.Methods involving derivatization are capable of achieving a lower limit of detection (LOD) and limit of quantification (LOQ) than previously used methods without derivatization [21].The ideal derivatization agent should react selectively with the specific functional group, without any by-products of the reaction formed.The detection and separation of analyte derivatives should not be interfered with by the residues of the derivatization agent [53].The most common approach presents silylation as the best way of preparing compounds for analysis.It results in the replacement of the acidic hydrogen atom with an alkylsilyl group [4] to form trimethylsilyl derivatives (TMS) using N-Methyl-N-(trimethyl-silyl)trifluoroacetamide (MSTFA) or bis(trimethylsilyl)trifluoroacetamide (BSTFA).These derivatives are highly volatile, stable and characterized by lower polarity, so they are more suited for GC analysis.If this method is used, we must remember that small, highly volatile compounds may evaporate from the sample during its preparation.Therefore, to avoid this, another modification of this method was developed: esterification using chloroformates, e.g., isobutyl chloroformate.In addition to the previously mentioned methods of preparing SCFAs for GC analysis, the latest and increasingly popular method is solid-phase extraction (SPE), or its more advanced version: solid-phase microextraction (SPME) [41].This technique is faster, more selective and more sensitive due to the smaller amount of impurities in the sample [20].SPME uses fibers for extraction, and it does not require a solvent to extract volatile compounds such as SCFAs.Due to the use of fibers, which are expensive and fragile, this method is more expensive than LLE with silylation [43].It also requires additional laboratory equipment and specialist knowledge to be performed effectively [20].Recently, researchers have more often combined solid-phase microextraction with derivatization into one method called headspace solid-phase microextraction (HS-SPME) [54].Due to the better matrix clean-up and the reduction of interfering compounds, this method is more selective and has better sensitivity [20,55].Such factors may also prolong the lifetime of the chromatographic system, thus lowering long-term analysis costs.
GC Parameters
The selection of appropriate GC analysis parameters is crucial for the effective separation of substances contained in the analyzed sample.It is most important to choose the appropriate chromatographic column-its length, width, type of stationary phase and its thickness.These parameters determine the efficiency of the column and its effectiveness in separating compounds with specific physicochemical properties.The length of the column and the thickness of the stationary phase film determine the duration of the analysis, i.e., the longer they are, the longer the separation time is.The width of the obtained peaks also increases.Almost all authors of articles included in this review used 30 m-long chromatography columns.Only Hough et al. [65] and Rui Wang et al. [21] used longer columns, i.e., 60 and 50 m, respectively.Shorter columns for analysis were used by Hoving et al. [66].For SCFA analysis, capillary columns with a non-polar stationary phase (5%-phenyl)-methylpolysiloxane are intended for the analysis of semi-volatile compounds (HP-5 column or analog), and high-polarity columns are intended for the analysis of volatile fatty acids, whose stationary phases are nitroterephthalic-acid-modified polyethylene glycol (DB-FFAP column or analog) or polyethylene glycol (DB-WAX column or analog).These types of columns are ideal for the separation of free fatty acids that are found in stool samples, especially in the case of methods without a derivatization procedure [21].Therefore, three such types of column were used in almost all methods mentioned in Table 1.Gray et al. used DB-FATWAX Ultra Inert Polyethylene Glycol (PEG), DB-WAX and CP-Wax 58 FFAP columns.He stated that the DB-FATWAX column was far superior to two previously mentioned columnsit demonstrated consistent peak responses, retention times, sufficient resolution and no peak tailing over four times longer than the other two under acidic conditions, which are preferred due to the promotion of solubility and SCFA recoveries at low pH (1476 vs. 361 injections) [67].Rohde et al. reported that succinic acid was a much better acidification agent than phosphoric acid because the recoveries obtained from it ranged from 95 to 117%, while from phosphoric acid they ranged from 111 to 177% [66].
Operating parameters such as the oven program, and carrier gas and its flow rate through the column, are also very important.The temperature at which the column operates determines the rate of the elution of the analyzed compounds from the column according to their increasing boiling points.Too low a temperature will result in the broadening of the peaks, while temperatures that are too high may lead to the overlapping of the peaks of the analyzed compounds.In both cases, performing a reliable analysis of the obtained results may be difficult.Overall, the main focus of researchers' attention was to ensure optimal conditions for the separation of a mixture of short-chain fatty acids, which involved the experimental search for the best temperature parameters for analysis.In the present study, the scientists took a different approach when it came to the oven temperature program.Some of them assumed a shorter analysis time, like Yunkyung Kim et al., who used a very high ramp to decrease the analysis time to just 4.63 min, using nitrogen as a carrier gas and flame ionization detection [63], while the remaining researchers using FID detection ran times between 13.5 [68] and 24 min [64].The fastest analysis using helium as a carrier gas was developed by Niccolai et al. and lasted 8.16 min [48].Conversely, the longest one was developed by Jain et al. and lasted 56.81 min [56].Looking chronologically, we can notice a tendency showing that, over time and with the appearance of subsequent publications, sample analysis times have shortened, which is undoubtedly related to the improvement of older methods, as well as the development of new ones due to the advances in the development of analytical research equipment.
The carrier gas used in GC analysis should be chemically neutral and should not interact with the analyzed compounds.It should also be of sufficient purity to prevent interference with the stationary phase, which could lead to a change in its properties.The viscosity and flow rate of the carrier gas exert a direct impact on the duration of the chromatographic analysis.The viscosity of hydrogen is twice as low compared to helium, making analysis using hydrogen twice as fast at the same flow.When selecting the carrier gas flow rate, the type of detector and its sensitivity, as well as the optimization of the analysis duration, should be considered.The most commonly used carrier gases include hydrogen, nitrogen, argon and helium, with helium usually being used in SCFA analysis, varying from 4N (99.99% purity) [21,65] to 6N (99.9999%).Nitrogen is used less commonly.Most authors chose helium at a flow rate of 1 mL/min, but some chose higher volumes, ranging from 1.1 [56] to 20 mL/min [58].In most cases, a higher flow was used for shortening the time of analysis and sometimes to compensate for a slow/complex oven temperature program, which is important, when a laboratory has to analyze a large number of samples over a short period.Only Łoniewiska et al. used hydrogen as a carrier gas at a flow rate of 14.4 mL/min.
Detectors
In the development of a new chromatographic method, it is important to select a detector that is sufficiently sensitive and adapted to our needs.It should be characterized by high baseline stability and a wide range of linearity of concentration measurements.For the analysis of short-chain fatty acids, a flame ionization detector (FID) and an electron ionization detector (EID) are most often used.FID requires burning the sample in a hydrogen flame.This allows for changes in the electric potential of the resulting ions to be recorded.EIDs register charge that has been carried out by the fragmented compound over a certain period.
Mass Spectrometry Analysis
In gas chromatography-mass spectrometry, different modes of operation are used during sample analysis.A full scan mode is the most common one, with a mass spectrometer scanning a wide range of mass-to-charge ratios (m/z) to detect all ions present in the analyzed sample.The main advantage of this detection mode is that it allows the detection of all compounds present in the sample, providing a complete mass spectrum.It is ideal for untargeted analysis because of the collection of the data of all ions.Conversely, that is why this method is characterized by lower sensitivity and specificity.The selected ion monitoring (SIM) mode is the preferred mode for the analysis of specific ions of interest.It allows other ions to be ignored during the analysis.Therefore, this mode is characterized by high sensitivity due to instrument focus on specific ions, allowing for a better detection of low abundance compounds, high specificity due to the reduction of interference from other ions and better quantification due to the analysis of only specific ions.The multiple reaction monitoring (MRM) mode allows for the monitoring of specific precursor-product ion transitions for targeted compounds.It is primarily used in tandem mass spectrometry (MS/MS).The main advantages of the MRM mode include ultra-high specificity and sensitivity, and enhanced selectivity.Monitoring pairs of precursor-product ions allows background noise to be reduced and it improves detection limits.This mode can only be used for the analysis of known targets, and requires method development, which can be time-consuming.
Our Own Experience Regarding GC/MS Metabolomics
In our research, we utilized the GC/MS method to determine the concentrations of SCFAs and selected amino acids.Due to the nature of the study conducted by our team, the concentrations were measured in stool samples of various origins, including samples obtained from mice, healthy children, children with non-alcoholic fatty liver disease, obesity, or essential hypertension.Additionally, we examined samples from healthy adults, e-sports athletes, amateur and professional athletes, oncology patients with various types of cancer [77], patients with Clostridium difficile diarrheal cancer and inflammatory bowel disease.In our research, we used a method based on derivatization to determine SCFA levels in stool samples.The method used in our laboratory is shown in Figure 3.
GC/MS Procedures
In brief, each collected stool sample was kept at −80 Celsius degrees before analysis.Next, the sample was weighed on dry ice (weighing 50-100 mg, depending on the origin:
GC/MS Procedures
In brief, each collected stool sample was kept at −80 Celsius degrees before analysis.Next, the sample was weighed on dry ice (weighing 50-100 mg, depending on the origin: mouse or human) and was placed in a 2 mL tube containing ceramic beads designated for environmental sample analysis (Ohaus Corporation, Parsippany, NJ, USA).One milliliter of fresh 10% isobutanol solution was added to each sample.The samples were mechanically homogenized three times for 2.5 min each and then incubated at room temperature for 30 min.This procedure was performed twice.The homogenized samples were subsequently centrifuged at room temperature for 5 min at 21,000× g.A volume of 675 µL of the supernatant was collected and transferred to a new Eppendorf tube.To this, 10 µg of the internal standard (3-methyl valeric acid), 125 µL of 20 mM NaOH and 400 µL of chloroform were added.The sample was vortexed for 1 min and centrifuged for 2.5 min.A total of 400 µL of the upper aqueous phase was transferred to a new tube, followed by the addition of 100 µL of pyridine and 80 µL of isobutanol.The volume was adjusted to 650 µL with ultra-pure water.Calibration standards for SCFAs (formate, acetate, propionate, butyrate, isobutyrate and valerate) and amino acids (alanine, L-arginine, L-cystine, L-glutamic acid, L-leucine, L-lysine, L-serine, L-threonine, L-tyrosine, L-valine and L-histidine) were obtained from Sigma-Aldrich (St. Louis, MO).The derivatization of samples and standards was conducted with isobutyl chloroformate (50 µL per 650 µL sample or standard).The samples were vortexed in total for 1 min, followed by the addition of 170 µL of hexane, then vortexed again and centrifuged.The upper isobutyl-hexane phase was transferred to an autosampler vial for gas chromatographic analysis.
The analysis was performed with an Agilent 7000D Triple Quadrupole mass spectrometer coupled to a 7890 GC System with a G4513A autosampler (Agilent Technologies, Santa Clara, CA, USA) and a VF-5ms column (30 m, 0.25 mm, 0.50 µm).The injector, ion source, quadrupole and transfer line temperatures were set at 260 • C, 250 • C, 150 • C and 275 • C, respectively.Helium served as the carrier gas at a flow rate of 1 mL/min.The derivatized sample was injected into the VF-5ms column (Agilent Technologies, Santa Clara, CA, USA) with a split ratio of 50:1 and a solvent delay of 3 min.The oven temperature program was started at 40 • C for 5 min, increased to 275 • C at a rate of 10 • C/min and was maintained at this temperature for 10 min.The total run time was 38.5 min.MS data were collected in full scan mode from m/z 15 to 650 at 4.9 scans per second and analyzed using MassHunter software (version 10.1 build 10.1.733.0)(Agilent Technologies, Santa Clara, CA, USA).Finally, the obtained results were analyzed using standard biostatistics programs, such as GraphPad Prism.
Our Results Obtained during Studies Conducted Employing GC/MS
In this section, we present the findings from four publications [22,23,77,78] that explore SCFAs and amino acids levels which, alongside a variable microbiota, could potentially be recognized as biomarkers of diseases.It is worth noting that the discussed studies also address changes in the microbiota related to alpha and beta diversity.Identified bacteria and differentiated levels of SCFAs and AAs may serve as biomarkers of diseases, potentially contributing to diagnostics and influencing treatment outcomes.This detailed analysis offers valuable insights into the possible applications of these findings in clinical practice.
The goal of the first study [78] was to investigate the impact of starch degradation products (SDexF) as prebiotics on obesity management in mice and overweight/obese children.We showed that SDexF reduced the relative fecal concentrations of pentanoic acid and all amino acids, while boosting the level of acetic acid in female mice on a normal diet and in male mice on a normal diet, respectively.In female mice on a Western diet, it led to an increase in propanoic acid and a reduction in alanine, valine, leucine, isoleucine and glutamic acid levels.Meanwhile, in male mice on a Western diet, there was an elevation in the levels of acetic acid, propanoic acid and butyric acid.In contrast to the significant effects of SDexF on weight gain, and on the gut microbiome and metabolome composition observed in the animal study, especially in female mice, SDexF did not influence weight loss or gut metagenomic and metabolomic profiles in children, with the only changes being noted in the abundance of specific taxa.However, a daily intake of vegetable and fruit mousses led to a notable reduction in relative amino acid levels by week 24 of the study, irrespective of SDexF treatment.This reduction was still partially evident at week 12, after the study concluded in both the prebiotic and control groups, though the clinical relevance of this finding remains uncertain.SDexF, known for its soluble fiber-like properties, is resistant to digestion by human enzymes due to its glycosidic bonds, which are not broken down by typical amylolytic enzymes.Consequently, it was anticipated that these compounds would pass through to the large intestine intact.Given SDexF's known prebiotic effects, an increase in SCFA production was expected.However, while this effect was demonstrated in animal studies, it was not replicated in studies examining human feces.
In a subsequent study [23], we examined the composition and function of the gut microbiota, as well as the levels of SCFAs and AAs, in a group of 109 well-built Polish male sports players.The findings were compared with two reference groups: 25 endurance athletes and 36 healthy students of physical education.A six-week exercise training program in lean sedentary individuals resulted in an increase in fecal SCFA concentrations [79].A literature review supported the view that exercise generally enhances the production of gut SCFAs.However, none of the SCFAs was distinct among the groups in our study.Instead, five SCFAs were associated with different enterotypes.Specifically, propanoic, isobutyric, pentanoic and hexanoic acids were linked to distinguishing between Alistipesand Bacteroides-dominated enterotypes, while acetic and propanoic acids differentiated between Prevotellaand Alistipes-dominated enterotypes.Additionally, pentanoic acid was unique in distinguishing between Prevotellaand Bacteroides-dominated enterotypes.Increased bacterial metabolic activity in the distal colon may be influenced by a greater availability of amino acids.Unlike fecal SCFAs, all nine amino acids examined in this study showed differences between sports players and students.Furthermore, four amino acids varied between professional athletes and students, with methionine uniquely distinguishing sports players from both other groups.We also determined the correlation coefficients to assess the relationship between bacterial abundance and the levels of SCFAs and AAs.Specifically, Bacteroides vulgaris, Barnesiella intestinihominis and Prevotella copri were associated with at least five of the seven SCFAs studied.Alistipes finegoldii showed positive correlations with all nine AAs analyzed.In contrast, Faecalibacterium prausnitzii was negatively correlated with seven AAs.
The aim of the third study [22] was to compare the metagenomic and metabolomic profiles of patients with Clostridioides (Clostridium) difficile-associated diarrhea, cancer and inflammatory bowel disease (IBD).In this study, we used shotgun metagenomic sequencing and GC-MS to define the additive effect of C. difficile infection (CDI) on intestinal dysbiosis.In this study, we observed that the relative abundance of seven out of the nine measured fecal SCFAs distinguished at least two groups of diarrheal patients from the healthy control group.Specifically, formic acid and caproic acid were found in higher concentrations, while pentanoic acid was present in lower concentrations across all three diarrhea groups.Additionally, five amino acids showed differences between at least two patient groups and healthy controls.Among these, glycine and valine were more abundant, whereas methionine and glutamic acid were less abundant in each patient group.
To assess the relationship between the abundances of 56 species that distinguish all diarrheal patients from healthy controls, and 27 species that distinguish CDI patients from controls, we employed the Spearman correlation coefficient to analyze the levels of SCFAs and amino acids.Four specific species that separated diarrheal patients from those without diarrhea were identified: Ruminococcus gnavus, E. coli and Klebsiella pneumoniae showed a negative correlation with pentanoic acid levels.Both E. coli and Klebsiella pneumoniae were negatively correlated with glutamic acid but positively correlated with valine, while Ruminococcus gnavus and E. coli exhibited a positive correlation with phenylalanine.Most species that were under-represented in diarrheal patients showed a negative correlation with formic acid, isocaproic acid, glycine and valine, but a positive correlation with isobutyric acid, butanoic acid and pentanoic acid.In the case of CDI patients, eight species were under-represented compared to healthy controls.Slackia isoflavoniconvertens, Blautia obeum, Ruminococcus torques, Dorea longicatena and CAG 139 showed negative correlations with isocaproic acid, while Eubacterium ramulus, Blautia obeum and Dorea longicatena were positively correlated with butanoic acid.Bacteroides dorei, Blautia obeum and Ruminococcus torques were correlated with methionine abundance.Among the 19 species that were over-represented in CDI patients, Enterococcus faecalis, Lactobacillus rhamnosus and C. difficile showed a positive correlation with isocaproic acid, whereas other metabolites were primarily correlated with individual bacterial species.
In the last of the studies discussed [77], we utilized shotgun sequencing along with GC/MS to perform metagenomic and metabolomic analyses.These techniques were employed to identify both common and distinct taxonomic configurations across patients with various cancers: 40 with colorectal cancer, 45 with stomach cancer, 71 with breast cancer, 34 with lung cancer, 50 with melanoma, 60 with lymphoid neoplasms and 40 with acute myeloid leukemia (AML).The findings were then compared to those from healthy controls (HC) who were matched for sex and age.In the present study, we discovered that fecal formic acid levels were significantly elevated across all seven case groups.Formate, an intermediate metabolite in one-carbon metabolism, facilitates metabolic interactions between mammals, their diet and the gut microbiome.It is produced by anaerobic fermentation from certain gut bacteria, and elevated levels in the gut lumen might indicate inflammation-related dysbiosis.In patients with breast cancer and colorectal cancer, there were increased levels of acetic, propanoic, isobutyric, butanoic and pentanoic acids, along with amino acids such as alanine, glycine and proline.In the group with lymphoid neoplasms, higher levels of isobutyric, pentanoic and hexanoic acids, as well as methionine and glutamic acid, were observed.However, in patients with lung cancer, stomach cancer, or melanoma, the concentrations of most fecal metabolites were similar to those of the control group.We recalculated the correlation coefficients between the bacteria differentiating the studied patient groups and HC, and the levels of bacterial metabolites.Most of the species that were over-represented in our case samples showed a positive correlation with fecal levels of valine, phenyloalanine and glycine, and a negative correlation with hexanoic acid levels.In contrast, bacterial species that were more abundant in control samples exhibited the opposite correlations.Additionally, a sub-group of seven species of Faecalibacterium correlated negatively with most AAs and formic acid, but positively with acetic, propanoic and butanoic acid levels.
As evidenced by the results of our own research, determining the correlations between bacteria and their produced metabolites appears to be a more effective tool for identifying biomarkers of various diseases.Integrating such studies into routine patient therapy and monitoring could potentially enhance diagnostic accuracy and treatment outcomes.By using these insights, healthcare providers can better tailor treatment plans and improve patient outcomes through a deeper understanding of microbial interactions.Further research in this area could lead to significant advancements in personalized medicine, emphasizing the importance of the gut microbiome in overall health.
Conclusions
Fecal metabolite analysis is gaining prominence in metabolomics due to its comprehensive metabolic insights and the accessibility of fecal samples.GC-MS is a highly effective technique.This method allows for accurate quantitative analysis, determining the exact concentrations of components within a sample, and provides a qualitative identification of compounds, which is essential across various scientific disciplines.The rapid separation process in gas chromatography facilitates quick results.Additionally, the automation of many GC-MS systems enhances efficiency and minimizes errors from manual sample handling.MS excels at distinguishing and analyzing closely related chemical compounds-a task that may be difficult for other analytical methods.GC is particularly adept at separating and analyzing volatile and semi-volatile substances, making it invaluable in numerous industrial and research contexts.Our review covers fecal metabolomics in human studies, highlighting common metabolic patterns associated with different diets and health conditions.We examined the available literature on the methods for analyzing SCFAs in stool samples obtained from humans, animals and cell cultures.The key parameters of the studies we reviewed included sample storage before analysis, sample weight, sample preparation methods, the use of internal standards, GC parameters, types of detector used and MS parameters.
GC-MS has long been a preferred method for analyzing volatile compounds in biological samples, including feces.In thermal desorption GC-MS, volatiles from the headspace of heated feces are absorbed onto a chosen medium or trapped directly, then released by heating, and injected into the GC column for MS detection.A common absorbent used is the polymer-coated fiber of an SPME system, with extraction effectiveness depending on the fiber type and extraction duration.For non-volatile compounds, chemical derivatization is essential in GC-MS studies to convert non-volatile forms into volatile ones suitable for GC analysis.Before derivatization, an extraction process is necessary to isolate the desired compounds from the biospecimen.Developing a robust and standardized fecal metabolomics methodology, including precise quantitation and identification of biomarkers, is crucial for advancing fecal metabolomics into wider clinical applications.
Figure 1 .Figure 1 .
Figure 1.Gut-microbiome relationship.Higher consumption of processed food lowers microbial α-diversity, characteristic of dysbiosis, and increases the intake of processed food.SCFAs (acetate,Figure 1. Gut-microbiome relationship.Higher consumption of processed food lowers microbial α-diversity, characteristic of dysbiosis, and increases the intake of processed food.SCFAs (acetate, propionate, butyrate) are produced by fermenting dietary fiber and resistant starch.Key SCFA producers include Clostridium, Roseburia and Faecalibacterium.SCFAs regulate appetite, energy homeostasis and the integrity of the intestinal barrier, altering mineral bioavailability and the metabolism of glucose, lipids and cholesterol.Dysbiosis increases intestinal permeability, allowing harmful compounds to enter the bloodstream, disrupting the gut-liver axis and immune response, and altered SCFA levels contribute to conditions such as obesity, IBS, IBD, colon cancer, celiac disease and NAFLD.Created with BioRender.com(accessed on 17 July 2024).
Figure 2 .
Figure 2. Development of metabolic syndromes through obesity.The prevalence of obes related metabolic disorders is increasing due to unhealthy lifestyles, lack of exercise and a sive intake of empty calories.This causes insulin resistance and may lead to type 2 diabe WHO estimates that 1 in 8 people worldwide is obese, with adult obesity more than doublin 1990.Up to 75% of obese adults and 50% of obese children develop metabolic disorders.with BioRender.com(accessed on 15 July 2024).
Figure 2 .
Figure 2. Development of metabolic syndromes through obesity.The prevalence of obesity and related metabolic disorders is increasing due to unhealthy lifestyles, lack of exercise and an excessive intake of empty calories.This causes insulin resistance and may lead to type 2 diabetes.The WHO estimates that 1 in 8 people worldwide is obese, with adult obesity more than doubling since 1990.Up to 75% of obese adults and 50% of obese children develop metabolic disorders.Created with BioRender.com(accessed on 15 July 2024).
Figure 3 .
Figure 3. Sample preparation for GC/MS analysis in our protocol.Created with BioRender.com(accessed on 17 July 2024).
Table 1 .
Review of methodological literature from 2018 to 2024. | 10,712.8 | 2024-08-01T00:00:00.000 | [
"Chemistry",
"Environmental Science",
"Medicine"
] |
MOTIVATION FOR INDIVIDUALS’ INVOLVEMENT WITH FAN PAGES
This research examines the empirical model of individuals’ involvement with fan pages. The research model was developed based on the social influence factors and the brand post popularity model. The research employed an online survey questionnaire. 300 samples were collected by using a purposive sampling technique, and analyzed using the Partial Least Square (PLS) method. The results showed that identification, interactivity, informational content and valence of comment were the motivating factors for the intent to become involved with fan pages. It was indicated that the brand popularity model was not the only relevant model to explain the social computing phenomenon in the context of fan pages, but social influence factors also play a part. The implications for stakeholders and further research are discussed.
INTRODUCTION
This research was motivated by the emergence of various types of Social Networking Sites (SNS) that influence the behavior of an individual's involvement with them, and the way organizations and individuals use online marketing practices, such as Facebook's fan pages. Although a prior study did examine the motivation for individuals' involvement with fan pages using the online brand popularity model (DeVries et al., 2012), but it had its limitations, because it only examined fan pages' characteristics as the motivator for becoming involved. Meanwhile, the real reasons for an individual's motivation have not been studied by previous research. This raises the opportunity to re-examine the individual's motivation to become involved with fan pages by completing and combining the online brand popularity model (fan pages' characteristics) and the social influence factors of an individual's motivation to involve him or herself with online social media (Abdillah et al., 2012).
Within a few years, SNS became quite popular, such as Facebook which claims, in 2011, to have more than 800 million active members, since its establishment in 2004 (www.facebook.com). SNS can be described as social networking for social or professional interactions (Trusov, Bodapati, and Bucklin, 2009). SNS members can become friends with other members, but they can also become fans of a brand on a particular fan page.
Conceptually, fan pages reflect the customers' relationship with the brand (McAlexander et al., 2002), expand the brandcustomer relationship (Muniz Jr. and O'Guinn, 2001), and provide resources and social benefits to members (Bagozzi and Dholakia, 2006). Through fan pages, companies post brand related anecdotes, photos, videos, or other material. Then, fans of the brand can interact with the brand by liking or commenting on them.
In 2011, more than 50 percent of social media users follow brands on social media and more companies were investing in social media, as indicated by worldwide marketing spending on SNS reaching $43 million (Williamson, 2011). Managers invested in social media sites to build relationships and interact with their customers. One way to achieve this goal was to create a brand community in the form of a fan page at a SNS, at which customers could interact with the company by giving likes and comments to the brand posted (Muniz Jr. et al., 2001). Fan page consumers of these brands tend to remain loyal and committed to the company, and more open to receiving information about the brand (Bagozzi et al., 2006). In addition, fans of the brand were more likely to visit the store, generate more positive Word-Of-Mouth (WOM) advertising, and be more emotionally attached to the brand than non-fans of the brand (Bagozzi et al., 2006). Thus, in general, the presence of SNS has changed the socio-economic patterns of human interaction and fan pages have changed the way companies communicate with their customers. This dynamic encourages research into fan pages in the marketing domain.
Although previous studies found social media marketing activities had successes, relatively little work was done into the factors that affected the popularity of the brand, as measured by the number of likes and comments posted on fan pages (Zabin, 2009). Studies of the brands' posts and popularity have not provided sufficient theoretical foundations and empirical examinations to explain the popularity of the brands. For example, previous studies indicated that the companies should experiment with different characteristics of the brand post, such as video, images, text, or questions (Keath et al., 2011). This situation provides an opportunity to conduct similar research.
The purpose of this study is to examine the individual's motivation to involve him or herself with fan pages. This study considers the characteristics of fan pages (for example, interactivity), their content (eg, information), and the valence comments that are replicated and adapted from research by De Vries et al. (2012). The third variables are used because they are the key variables that drive the individual's involvement with fan pages from the perspective of the online brands' popularity concept. However, the limitations of these variables (De Vries et al., 2012), in explaining the behavior of an individual's involvement with fan pages raises the opportunity to re-examine them. In addition, this study also considers the aspect of the user's motivation, namely if the internalization and identifi-cation can be replicated, as adapted from research by Abdillah et al. (2012). By integrating aspects of the fan pages' characteristics and the content and valence of comments with the user's motivational aspects, it is expected that this research model may comprehensively explain the reasons for an individual's involvement with fan pages.
This study differs from previous empirical studies conducted by De Vries et al. (2012) and Abdillah et al. (2012), because this study integrates two perspectives, social computing (theory of social influence) and social media marketing (brand popularity). This integration is expected to enrich the theoretical study of online marketing through the development of behavioral models for individuals' involvement with fan pages. It also contributes to developing research instruments that can be replicated by further similar studies. Practically, this study provides a scientific explanation for stakeholders. For corporations, particularly online marketers, this study presents an explanation of the implications of managerial behavior for an individual's involvement with fan pages, which will give strategic information to marketers about the ways to effectively build an online brand's popularity through its fan pages. Also, this study can be the basis for an analysis of business policies, in anticipation of changes in the pattern of society's socio-economic dynamics, as a result of the changes in the behavior of online marketing by the organizations and changes in the market's preferences that must be addressed by the company.
LITERATURE REVIEW AND HYPOTHESES DEVELOPMENT
This section describes the theories and concepts used to develop the research models and hypotheses. The theories used in this study were the social influence theory and the concept of individuals' involvement with fan pages.
Individuals' Involvement with Fan Pages
SNS are natural technology platforms for marketing because they provide access to a large number of users, who can be categorized based 222
Journal of Indonesian Economy and Business May
! on their non-geographical communities, and the structured set of social relationships among admirers of the brand in the form of fan pages (Muniz Jr. and O'Guinn, 2001). Fan pages are an effective tool for increasing sales (Bagozzi et al., 2006). Fan pages also have the potential to improve the relationship between consumers and brands, and may affect members' perceptions and actions (Muniz Jr. and O'Guinn, 2001).
Fan pages facilitate interaction through the exchange of opinions about brands or specific products among their consumers, thereby involving the members in a form of WOM communication (McAlexander et al., 2002). WOM has been found to be a powerful tool for marketing, and has been used by individuals as a source of brand or product information (Buttle, 1998). Therefore, fan pages play an important role in enhancing commitment to the brand, and in making decisions to purchase it (Godes and Mayzlin, 2004).
Fan pages can be defined as the means by which the involvement of consumers' intrinsic motivation to interact and cooperate with community members, both in a cognitive and emotional involvement form, or as the result of encouragement, finds release (Van Doorn et al., 2010). Previous studies focused on the achievements of fan pages marketing objectives in increasing profitability (Hallowell, 1996). A recent study conducted by De Vries et al. (2012) focused on the antecedents of online brands' popularity, which was displayed by brand pages. Although previous studies have examined individuals' involvement with SNS from a variety of viewpoints, but studies specifically aimed at the context of fan pages are relatively limited. By integrating the research model of online brands' popularity (interactivity, informational content, and valence comments) by De Vries et al. (2012) and the social influence factors (internalization and identification) by Abdillah et al. (2012), this study re-examined the antecedents of individuals' involvement with fan pages.
Social Influence Theory
Kelman (1953) revealed in his concept of social influence that the persuasive communication theme is called the social influence theory. Kelman's theoretical research focus was into social influences and attitude changes, with emphasis on the differences among the influence processes, the relationship between the action and changed attitudes, and the concept of personal responsibility for acts committed in order to fulfill official authority. The social influence theory explains that social influence occurs when the thoughts or actions of individuals were influenced, consciously or unconsciously, by others as a result of changing the way a person perceives him or herself in a relationship with influencers, or other persons and the community at large. Kelman (1961) divided the social influence processes into three main forms, namely compliant, internalization and identification. Compliant explains the situation when individuals accept social influences or avoid punishments (mandatory). Individuals who receive compliant social influences are seen as agreeing with the majority, even though they may refute this internally. But, this study excluded compliant because it was not a strong predictor of an individual's motivation to become involved with fan pages on online social media or social networking sites (Abdillah et al., 2012). Identification explains the situation when individuals receive social influences because of their interest in respected or admired sources of social influence (agents), such as celebrities or respected family members. Internalization describes the situation when individuals receive social influences because their content is congruent with the individuals' value systems. Individuals who receive internalization will receive social influences in general (public conformity) or private (private acceptance).
The application of the social influence theory in the study of online communities grew rapidly when empirical studies by Bagozzi and Dholakia (2006) confirmed the role of social factors in influencing social computing behavior. Those studies were not only conducted in the context of online communities, but also in the context of online marketing, particularly online brand communities (Bagozzi and Dholakia, 2002). Those studies not only confirmed the role of social influence factors but also found a new construct, namely the we-intention. The follow- Social networking sites can be described as networks of friends for social or professional interactions. Members of social networking sites can become friends with other members, but they can also become fans of brands on dedicated brand fan pages. Brand fans can share their enthusiasm about the brand on these dedicated pages and be united by their common interest in the brand (De Vries et al., 2012). Brand fan pages reflect part of the customers' relationship with the brand, broaden the brandcustomer relationship, and provide a source of information and social benefits to the members (Bagozzi and Dholakia 2002). On these brand fan pages, companies can create brand posts containing anecdotes, photos, videos, or other material; the brand's fans can then interact with these brand posts by liking or commenting on them.
In this article, this study focuses on the determinants of individuals' involvement with these fan pages by using the brand posts' popularity factors, i.e., the interactivity, informational content, and valence of comment (De Vries et al., 2012). Previous studies found the determinants affecting the brand posts' popularity by conducting research into the effectiveness of the brand posts (De Vries et al., 2012). Similarly, brand posts occupy only a small part of these brand fan pages, with companies wanting the brand's fans to like or comment on them. Thus, the challenges of brand posts are firstly to attract people's attention and secondly to induce people to click on and view the content.
Effect of Social Influence Factors on the Intention to Become Involved with Fan Pages
Social influence occurs when individuals' thoughts and actions are consciously or unconsciously influenced by others as a result of changes in their perception of other influencers or society (Kelman, 1961). The social influence theory describes two forms of the social influence processes, namely internalization and identification.
Internalization is the process of the formation of the perceptual suitability of values between individuals and other people or the community. Social influence will effectively form in a person when that individual is susceptible to agree with the attitudes of other people or the community. Individuals with internalization would voluntarily behave and consciously act with regard to something which they consider appropriate to their intrinsic value systems.
Individuals who perceive conformity among their intrinsic values and online communities will be motivated to get involved in the communities. Malhotra and Galletta (1999) found internalization predicted the intention to become involved in online communities. Internalization also predicted an intention to become involved in SNS, the intention to be involved in online brand communities (Bagozzi et al., 2002) and attitude preferences towards online advertising (Bagozzi et al., 2006). This study argues that individuals who receive social influences from fan pages, and perceive conformity between the values and goals of these fan pages and their own intrinsic values and goals, will have the intention to involve themselves with fan pages. Based on these explanations, the first hypothesis developed by this study is as follows: H1a: Internalization positively affects individuals' intentions to involve themselves with fan pages.
The second dimension of the social influence theory is identification, the formation process of an individual's perception to behave in accordance with the values espoused by certain people and the communities or society he or she admires. Identification shapes individuals' attitudes and behaviors to conform to community standards. Social influence will effectively form when an individual's attitude and behavior conforms with the attitude and behavior of 224
Journal of Indonesian Economy and Business May
! someone he/she admires or respects, such as the elderly or celebrities. Individuals with identification would voluntarily behave and consciously act in response to something which they consider congruent with their intrinsic values. However, identification can be mandatory when the individual's decision is motivated by the need to satisfy others or to maintain the relationship or social identity with the community.
Identification is a strong predictor of the extrinsic motivation of individuals to participate in SNS (Bagozzi et al., 2002). Individuals who perceive the attractions of a community, will be motivated to get involved with that community. Malhotra and Galletta (1999) found that identification predicted an individual's intention to be involved in online communities and online advertising (Bagozzi et al., 2006).
This study argues that individuals who receive fan pages' social influence and also perceive the attractiveness of fan pages will maintain their relationship with others and gain a social identity from the fan pages, which will encourage them to further engage with the fan pages. Based on these explanations, the second hypothesis developed in this study is as follows: H1b: Identification positively affects the individual's intention to be involved with fan pages.
Effect of Interactivity on the Intention to be Involved with Fan Pages
Interactivity is defined as the level of interparty involvement with communications, communication media, messages, and the degree of influence syncronization (Liu and Shrum, 2002). Interactivity is characterized by the twoway communications between companies and customers or among customers, which is differently characterizing the communication of many parties (Goldfarb and Tucker, 2011). Fan pages' characteristics differ in their degree of interactivity. For example, a text shaping fan page is simply less interactive than a website link (Fortin and Dholakia, 2005).
Previous studies show different findings for the effect interactivity has on attitudes toward advertising (Liu and Shrum, 2002). Some research suggests the possibility of an optimal level of interactivity (Fortin et al., 2005), but other studies have suggested a linear effect of interactivity (Coyle and Thorson, 2001). Because the purpose of fan pages is to motivate the fans' reactions to the brand (ie, liking and/or commenting), then a higher degree of interactivity will encourage individuals to become involved with the fan pages, by giving likes and comments. Thus, the third hypothesis proposed by this study is as follows: H2a. The higher that the interactivity of the fan pages is, then the higher the individual's intention to be involved with the fan pages will be.
Effect of the Informational Content on the Intention to be Involved with Fan Pages
Searching for information is the main reason for people to use social networking sites (Liao et al., 2011) and to participate in virtual communities (Bagozzi et al., 2006). Information searches explain the reason people consume a certain brand's content (Muntinga et al., 2011). Therefore, if the brand's posts contain information about the brand or product, then the motivation of the brand's fans to participate or consume the content are fulfilled. Previous studies show that humans tend to have a positive attitude towards informative advertising on social networks (Taylor et al., 2011). Therefore, fans of a brand may have a more positive attitude toward informative brand postings than noninformative ones, thus leading to the intention to be involved with its fan pages. Thus, the fourth hypothesis proposed by this study is as follows: H2b. The more informative the fan page is, the higher is the individual's intention to become involved with the fan page.
Effect of the Valence of Comment on the Intention to be Involved with Fan Pages
The valence of comments is the desire of the brand's fans to make positive, neutral, or negative comments on a fan page (De Vries et al., 2012). Previous research has shown that online consumer discussions about their positive experiences with the product or brand generated empathy and positive feelings among the members (Bickart and Schindler, 2001). The exchange of information and experiences among consumer had a positive effect on the perceived value of a product, and the likelihood of the product being recommend (Gruen et al., 2006) and purchased (Chintagunta et al., 2010). Positive comments on a fan page have values that complement the company's brand posts (Bronner and de Hoog, 2010), and thereby increase the attractiveness of the fan page. Additionally, positive comments from fans of the brand can increase the value of the brand and create empathy among the brand's fans. This study argues that positive comments on fan pages will encourage other members to involve themselves with a fan page. Thus, the fifth hypothesis proposed by this study is as follows: H2c. Positive comments on fan pages positively affect the intention to become involved with fan pages.
The Effect of Intention on the Involvement with Fan Pages
According to Bagozzi and Dholakia (2002), there are three levels of explanation for the decision making in social research: (1) Classical individual based models (a personal intention to perform an individual act by oneself), (2) contingency consistency and other normative based models (a personal intention to perform an individual act but with consideration of the social influence), and (3) a group-based model (the model comprises of both personal intention and social intention to perform a group act). Two important concepts arise with this classification, I-intentions (classical individual-based models) and we-intentions (group-based models).
In the past two decades of Information Systems (IS) research, the predominant focus has been on the classical individual based models (Bagozzi and Dholakia, 2006). The intention to use (I-intention) a new technology depended on an individual's reasons and the perceived social pressures for using the new technology. This approach was particularly useful to the previous studies, as the focus had been predominantly into standalone information systems. Decision makers were more likely to form an intention, or to act in concert with their attitudes, insofar as the perceived norms encouraged making such a decision. Web 2.0 created a new world of collaboration. People came together to create, collaborate, and contribute their expertise and wisdom. They supported themselves and each other through their comments, discussions, and instant messages. Unlike the traditional individualbased approach (personal intention to perform an individual act), social interaction and connection has been the objective with Web 2.0 technologies, including online social networks. Associated with these new phenomena in human communications and interaction patterns, the we-intention, which has encapsulated social behaviors by its collectivity, is a more appropriate approach to study users' participation in online social networks.
However, online marketing studies still used intention (the I-intention) to predict behavior. Bagozzi and Dholakia (2002) stated that intention gave encouragement to being involved or re-involved with online communities. Studies conducted by Bagozzi and Dholakia (2006) found a positive effect of intention on an individual's involvement with online brand communities. Their studies also found an indifference to the intention to be involved or reinvolved with online communities. Therefore, this study also used intention (I-intention) and argued that the intention to involve or re-involve with fan pages was shaped by social influences and the determinants of involvement with SNS will encourage individuals to get involved with the fan pages. Thus, the sixth hypothesis developed in this study is as follows: H3: The intention to be involved with fan pages has a positive effect on the individual's involvement with fan pages.
RESEARCH METHOD
This research is a confirmatory study that aims to answer the research questions and hypotheses (Cooper and Schindler, 2006) with a quantitative approach. The design used was a survey employing a questionnaire.
The measurement of internalization used three items adapted from Malhotra and Galletta (1999), namely: The availability of fan pages, the shared personal values with the fan pages, and personal interests. The measurement of identification used three items from Malhotra and Galletta (1999), namely: The proud statement, revealing to others, and the self-defining of fan pages. The measurements of interactivity used ten items from the three sub-dimensions of the interactivity constructs adapted from Liu and Shrum (2002), which were: The active control, two-way communication, and synchronicity. The measurement of informational content used three items which were adapted from Taylor et al. (2011), namely: Information is useful, it is easy to get the information, and the latest information. The measurement of the valence comments used three items adapted from Bickart and Schindler (2001), namely: Comments on the fan pages have high credibility, provide relevant information, and are able to generate empathy. The measurements of intention used three items adapted from Bagozzi and Dholakia (2006), namely: The intention to participate in the fan pages, an intention to participate in the fan pages while clearly describing myself, and a desire to participate in the fan pages. The measurement constructs used a five-response Likert scale, 1 for strongly disagree and 5 for strongly agree. The population in this study was Facebook members who had been involved with a fan page. The sampling procedure was non-probability with a purposive sampling technique. The criteria used to select the sample were: (1) The subjects or respondents were Facebook members who had been involved with a fan page over the past year, to get an overview of the respondents' experiences of their involvement, and (2) the type of fan pages were political campaigns, product advertising, or government pages.
This study collected data from a sample of respondents using online questionnaire survey techniques. Researchers sent online questionnaires to all the members of the community through the sites' pages https://docs.google. com/forms/d/16d80u_IlJDgih_-J_V7Pll6z5HuCjmgPrIpZ27dC_E8/viewform?c =0andw=1andusp=mail_form_link. In order to maximize the response rate, the researcher also designed pre-alert notices, such as an initial announcement to all the respondents via e-mail before the questionnaire was sent out; an electronic cover letter to be attached to the questionnaire to make the respondents feel appreciated, the returns were to be anonymous and finally a reminder e-mail.
ANALYSIS AND DISCUSSION
This research is a confirmatory study of fan page users in Indonesia. This study uses survey design. Of the 300 questionnaires distributed online during February through personalized emails and the mailing list of the respondents, all 300 of the questionnaires were returned, giving a response rate of 100 percent, and all of them were fit for use in our analysis. Table 1 presents a description of the characteristics of the study sample.
The description of the sample's characteristics provides an overview of the gender, age, occupation, marital status, type of fan pages visited, length of membership of the pages, and the number of likes and comments. Based on this description, there is no missing value in the sample, except for the number of comments but the percentage of the missing value is very small compared to the total data. Thus, statistically, this condition does not affect the total data analysis overall.
By sex, most of the respondents are men, so that the general findings of this study represent a group of respondents which, in cognitive psychology, is a group of people who tend to think more rationally. Therefore, the majority of the group is expected to represent research that examines the cognitive aspect, such as the perception of their motivation for their involvement with fan pages.
In terms of age, the average respondent is 27 years old (rounding down from 27.24). This age group is considered as adult in its capacity for thinking and acting, so that this group is expected to represent the research. Meanwhile, the majority of the respondents classed their occupation as employees. This productive, working, age group is expected to be relevant and to present sensible measurements of their rational motivation for their individual involvement with fan pages, because this group is one of the active user groups of online social media.
Based on their marital status, the majority of the respondents have not yet been married. Although previous empirical studies have not reviewed the relationship between marital status and involvement with fan pages or online social media, this study logically assumes that one's marital status indirectly shapes their maturity of thought, which would be more likely to be formed when the individual has married, so the learning process about the complexities and responsibilities of adult life starts. Thus, the majority of respondents, since they have not been married, which presumably would indirectly affect their individual intentions to be involved with fan pages, because of the tendency for motivational involvement, which is not based on conscientiousness. Error of Skewness 0.14 0.14 0.14 0.14 0.14 0.14 0.14 0.14 Source: Data processed (2015) 228
Journal of Indonesian Economy and Business May
! Based on the types of fan pages, this study found that the most widely followed types of fan pages are those featuring product advertising. This indicates that the online social media, such as Facebook, are filled and used as a communications arena for product marketing. This leads the analysis and discussions of this study to the motivation for an individual's involvement in product advertising fan pages. However, further analysis and discussion are still required for other types of fan pages.
Based on the length of time the respondents stated they have followed certain fan pages, this study found the average length of time was 2 years. This finding indicates the existence of sufficient experience in the respondents involved with fan pages. It also indicates the relevance of the careful selection of the sample in order to fulfill the research's objectives.
Based on the number of likes and comments given by the respondents to the fan pages, this study found the average number of likes to be approximately 4, and the average number of comments was 1. This finding indicates the existence of a certain level of respondents' activity to the fan pages. It also indicates that the tendency to give a like is easier than to make a comment. Thus, this finding implicitly indicates that the motivation for individuals to involve themselves with fan pages (internalization, identification, interactivity, content information, and valence comments) will tend to encourage them to get more involved by giving likes rather than comments.
Based on the outcome of the PLS measurement model in Table 2, the empirical model tested in this research has fulfilled the criteria of the validity and reliability tests.
This study examined two main hypotheses, i.e. the antecedents of the individual's intention to be involved (social influence factors and characteristics of fan pages), as well as the effect of the intention to be involved with fan pages on the individual's actual involvement with fan pages. Hypothesis testing using the Partial Least Square methods were evaluated through the parameter significance of the t-statistic. Table 3 presents the results of the hypothesis testing using the Partial Least Square techniques.
Based on the results of the hypotheses testing, it can be concluded that all of the hypotheses were statistically significant, except hypothesis 1a, which was not supported (internalization does positively affect the individual's intention to be involved with fan pages). Overall, the results were able to explain the antecedents of an individual's involvement with fan pages. This study examines an empirical model of an individual's involvement with fan pages. This study is important because practically, the growth of online social media, especially fan pages, has opened new marketing communications methods for the companies with their customers. It has also encouraged the emergence of urgent empirical studies evaluating the motivation for individuals' involvement with fan pages, because the online brand popularity model can be developed by integrating it with the social influence theory. This integration is expected to provide better theoretical explanations than the previous studies.
This study used a survey design with an online questionnaire as the data collection method. The study included individuals with diverse genders, ages, marital status, occupations, types of fan pages, and number of likes and comments. In general, this study found that not only the fan pages' characteristics (interactivity, content information, and valence comments) but also the social influences factor encouraged individuals to become involved with fan pages. However, this study only found the extrinsic motivation, which was identified as a predictor of individuals' intentions to be involved with fan pages. These findings indicated that fan page members in Indonesia tended to become involved because they were driven by an extrinsic motivation in the form of their interest in the fan pages' features, such as the call a friend or colleague feature, or because of an attractiveness agent (such as a public figure), and they had reasons to avoid the social sanctions or socio-economic benefits of their involvement with such fan pages. The following detailed discuss the results of this study.
The first analysis, of hypothesis 1a, which stated that internalization positively affects the individual's intention to be involved with fan pages. But, this study found that internalization has no positive effect on the intention to get involved with fan pages. It means that hypothesis 1a was not statistically supported. This finding is not consistent with the opinion of Kelman's (1953) social influence theory which states that when individuals receive social influences, in the form of messages about the similarity of values which are believed to influence social values, then people will receive social influences publicly or privately. In other words, the individual will be motivated intrinsically, committed, willing and will behave in accordance with the encouragement of the social influence. This finding is also inconsistent with the study by Abdillah et al. (2012) which showed the positive effect of the internalization of the intentions of individuals for involvement with social networking sites.
Internalization is a social influence factor which exhibits the nature of effect as an intrinsic motivation for individuals to involve themselves or behave in certain ways. The internalized people tend to tend act constantly in long term. The result indicates that the individual's involvement with fan pages is not driven by intrinsic motivations or full consciousness. This can be seen by the fact that the frequency and intensity of the individuals' involvement with fan pages are quite rare and the absence of similarity of fan pages' values with personal values.
The second analysis, of hypothesis 1b, which stated that identification positively influences the individuals' intention to be involved with fan pages. This study found that identification did positively influence the intention to be involved with fan pages. It means that hypothesis 1b was statistically supported. This finding is consistent with the opinion of Kelman (1953) which stated that when individuals received social influences in the form of messages from respected or admired agents, such as celebrities, friends, family members or colleagues, then the individual would receive a general social influence. In other words, the individual would be extrinsically motivated, committed, eager, and would behave in accordance with the encouragement of the accepted social influences. This finding is also consistent with Abdillah et al. (2012) which showed the positive influence of identification on the intention to get involved in social networking sites.
Identification is a social influence factor that indicates the nature of the social influence as an extrinsic motivation for individual involvement or behavior in certain ways. The individual with Identification's social influence tends to behave in the short term. This result indicates that the respondents' involvement with fan pages were reflecting extrinsic motivations, in the form of their interest in the fan pages' features and the agents' appeals.
The third analysis, of hypothesis 2a, which stated that interactivity had a positive effect on the individuals' intentions to be involved with fan pages. This study found that interactivity had a positive effect on the intention to be involved with fan pages. It meant that hypothesis 2a was statistically supported. This finding is consistent with the study by De Vries et al. (2012). Interactivity is defined as the level of inter-party involvement in the communication media, and marked by two-way communications. Fan pages' characteristics have differences degree of interactivity, such as by being text-based or a link to a website. Various degrees of interactivity are used to encourage individuals to get involved with fan pages. This study also found that a higher degree of interactivity will encourage individuals to be more involved with fan pages by giving more likes and comments.
The fourth analysis, of hypothesis 2b, which stated that information content had a positive effect on the individuals' intentions to be involved with fan pages. This study found that information content did have a positive effect on the intention to get involved with fan pages. It meant that hypothesis 2b was statistically supported. This finding is consistent with De Vries et al. (2012). The information content describes the ability of a fan page to provide information that acts as an important reason for people to use social networking sites (Liao et al., 2011), to participate in virtual communities (Dholakia et al., 2004), to contribute to Facebook (Park et al., 2009), and consume content about related brands (Muntinga et al., 2011). Therefore, based on the findings of the research, the study concluded that individuals would have more positive attitudes towards informative fan pages, as compared to noninformative ones. The practical implication of this finding is that online marketers and developers should build and offer informative fan pages in order to reach higher levels of individuals' interest in becoming involved with the fan pages.
The fifth analysis, of hypothesis 2c, which stated that the valence of comments had a positive effect on the individuals' intentions to be involved with fan pages. This study found that the valence of comments did have a positive effect on the intention to get involved with fan pages. It meant that hypothesis 2c was statistically supported. This finding is also consistent with the study by De Vries et al. (2012). The valence of comments showed that a positive experience of the product or brand can generate empathy and positive feelings among the members (Bickart et al., 2001) which are then exchanged via fan pages. Information and experience exchanges among consumers have a positive effect on the perceived value of a product, and the likelihood of the product being recommend by them (Gruen et al., 2006) and also purchased (Chintagunta et al., 2010;Mayzlin et al, 2006). Positive comments from a brand's fans can also increase the value of the brand and create empathy among the brand's fans. This study found that the higher the valence of comments was on fan pages, the more likely it was that the fan pages would encourage individuals to get involved. Practical implications of this finding is that online marketers and the developers of fan pages should stimulate the emergence of the valence of comments from their fan pages' members, so they would attract potential new members to get involved in the existing fan pages.
Based on the detailed description of the entire results of this study, it can be concluded that the empirical model of the individuals' involvement with fan pages may explain the motivation for an individual's involvement with these fan pages. The development of a research model by integrating the social influence theory and the online brand popularity model has provided a scientific explanation for individuals' involvement with fan pages.
Practically, the findings indicate that identification, as a representation of the effect of the superficial appeal and the characteristics of fan pages, is the driving factor for individuals to involve themselves with fan pages. This superficial interest causes individuals to become involved without any specific intrinsic reasons, but to self-define their social relations. The information content provided by fan pages for users, and the information shared through conversations among fellow community members, indicates that WOM is still an effective way to influence individuals' intentions to become involved with online communities, and particularly with fan pages. Both factors also indicate that the rationality aspect is the main factor affecting the individual's intention to be involved with fan pages. Individuals' assess rationally based on the information they receive, both what is available from the fan pages, or obtained through WOM from among the community's members. A rational intention to become involved with fan pages indicates the need to build fan pages as online social media sources, based on objective information that can communicate, educate, and persuade users.
The practical implications of these research findings for stakeholders is how they can improve their design and management of fan pages so they become healthy and productive communications and educational media platforms by providing content that is both symmetric and objective. The appropriate information content will catalyze the valence of comments from fan page users so fan pages will be an effective communication media through positive WOM strategies, both for online businesses, leaders and political parties, or any other non-profit institutions.
CONCLUSION
This study examined the antecedents of individuals' involvement with fan pages. The results showed that identification, interactivity, content information, and valence of comments had an effect on individuals' intentions to get involved with fan pages, however, internalization did not. This suggests that theoretically, this study presented the empirical explanation of the relevance of the social influence theory and the online brand popularity model in explaining the phenomenon of individuals' involvement with fan pages. Our empirical examination showed that two concepts were able to explain the motivation for individuals' involvement with fan pages.
Meanwhile, this study had several limitations. Firstly, this study used a purposive sampling technique that needed great care when generalizing the results for the various forms of online social media, other than the fan pages. Although the sampling frame of the fan page members was available, access from its administrator to the sampling frame was difficult to achieve. Finally, the online questionnaire had the potential for a low response rate, which necessitated efforts to improve the response rate, such as by personally and repeatedly contacting the respondents.
Practically, these findings may have implications for stakeholders in the social context,
Journal of Indonesian Economy and Business May
! such as individual and private or public sector organizations, particularly those with interests in electronic business marketing, fan page developers, as well as business leaders and political parties. For individuals, these results provide information about the importance of improving the aspects of rationality in establishing an intention to become involved with fan pages. Rationality, based on objective and symmetrical information, leads individuals to become more confident and conscious of their involvement with fan pages.
In the organizational context, these findings provide critical information for organizations in their planning for online marketing communications' strategies. This study suggests that the information content and positive WOM communications via fan pages can effectively encourage individuals to get involved with fan pages. For electronic business marketers and fan page developers, this study provides important information for designing a marketing communications' strategy and Customer Relationship Management (CRM). If electronic business marketers and fan page developers seek longterm relationships with their customers, the business players and fan page developers need to emphasize the aspects of rationality based on objective and symmetric information in developing and using their fan pages as marketing communications media. This can be fulfilled by providing relevant, productive and informative content for their users, containing aspects of knowledge, learning, and entertainment.
For public figures and political parties, fan pages have now become an important part of Public Relations (PR) strategies to build the popularity of candidates and establish long-term relationships with constituents. These findings can be important information for public figures and parties, since fan page users, who are potential constituents (voters) are now rational users who base their decisions on the information provided, so that the means to effectively entice potential constituents (voters) no longer simply relies on emotional aspects, such as fanaticism. Constituents are now increasingly critical and rational, and should be provided with informative, educational fan pages, which stimulate them to communicate with each other so that the valence of comments is an effective way of marketing communications through positive WOM. | 9,765 | 2016-05-01T00:00:00.000 | [
"Business",
"Computer Science"
] |
Comparison on Energy Economy and Vibration Characteristics of Electric and Hydraulic in-Wheel Drive Vehicles
: This paper compares the energy economy and vertical vibration characteristics of in-wheel drive electric vehicles (IEVs), in-wheel drive electric hydraulic hybrid vehicles (IHVs) and centralized drive electric vehicles (CEVs). The dynamic programming (DP) algorithm is used to explore the optimal energy consumption of each vehicle. The energy economy analysis shows that the IEV consumes more energy than the CEV due to its relatively lower electric motor efficiency, even with fewer driveline components. The IHV consumes much more energy than the IEV and CEV because of the energy loss in the hydraulic driveline. The vertical vibration analysis demonstrates that both IEV and IHV degrade the vehicle driving comfort due to increased unsprung mass. Taking the advantage of high power density of the hydraulic motor, IHV have less unsprung mass when compared with the IEV, which helps to mitigate the vibration problems caused by increased unsprung mass.
Introduction
Transportation electrification is an important solution for environmental degradation and non-renewable energy shortage problems.Various electric vehicle configurations have been proposed in academia and industry.At the moment, most of the electric vehicles on the market such as Tesla, Mercedez-Benz EQC, Nissan Leaf and BMW i3 are equipped with single gear transmissions owing to the large speed range and low-speed high-torque characteristics of electric motors [1,2].Some electric vehicles use two motors on the front axle and rear axle respectively to further improve the vehicle dynamic performance [3].The multi-gear and multi-motor powertrains are widely researched in academia with the motivation of improving the electric vehicle energy economy and dynamic performance.The automated manual transmission (AMT) [4,5], dual clutch transmission (DCT) [6], automatic transmission (AT) [7,8] and continuous variable transmission (CVT) [9,10] have been implemented in electric vehicles.
The in-wheel drive electric vehicles (IEV) in which electric motors are directly connected to wheels have been considered as one of the most important formats of electric vehicles [11].The IEV could eliminate all of the driveline components so that the transmission power loss is cancelled.The vehicle handling and stability performance are significantly improved by the torque vector control based on the quick torque response and outstanding controllability of electric motors [12,13].In addition to the attractive advantages of IEV, there are also some unsolved problems which hinder its implementation.Limited installation space makes it difficult for heat dissipation [14].The vibration caused by increased unsprung mass reduces the vehicle drive comfort and deteriorates the suspension and motor bearing working conditions, which accelerates the components' fatigue and failure [15].Compared with the electric motor, the hydraulic motor has a higher power density, which means less unsprung mass will be added if the hydraulic motor is used for in-wheel drive [16,17].So the vibration problems caused by increased unsprung mass could be mitigated.Besides, the hydraulic motor is driven by fluids, which naturally constitute the cooling system.The wheels have to work under complex environments like in water or off road, which proposes challenges for the high voltage electrical system.In contrast, the hydraulic system is more reliable in these complex working conditions.These advantages make the hydraulic motor a potential candidate for in-wheel drive [18].The hydraulic motor has been used for vehicle driving in massive researches combined with electric motors.The parallel electric hydraulic hybrid vehicle [19][20][21] and series electric hydraulic hybrid vehicle [22] have been widely investigated.These vehicles take the advantage of the high power density of hydraulic motors to recover more braking energy so that the vehicle energy economy is improved.The hydraulic motor has also been used for in-wheel drive [16].However, in this proposal, the engine is used to generate the hydraulic power so it still relies on traditional fossil fuel.
With the motivation of exploiting the merits of in-wheel drive and electrification, an inwheel drive electric hydraulic hybrid vehicle (IHV) is investigated in this paper where the hydraulic motor is used for in-wheel drive and an electric motor is used as the power source.The energy economy and vertical vibration characteristics of the IHV are compared with the IEV and a centralized drive electric vehicle (CEV).The dynamic programming (DP) algorithm is adopted in the energy management strategy design, which helps to find the optimal energy economy of each vehicle.Due to the vehicle vertical vibration having a significant impact on the vehicle driving comfort, the vertical characteristics of each vehicle are compared based on a quarter car model.
The remainder of this paper is presented as follows: Section 2 introduces the vehicle powertrain configurations and working principles of each vehicle.In Section 3, the dynamic models of vehicle powertrains are built.Section 4 designs the energy management strategies based on dynamic programming.In Section 5, simulations are conducted to analyze the energy consumption of each vehicle.Section 6 analyses the vertical vibration characteristics of each vehicle.In Section 7, conclusions are drawn for this paper.
Vehicle Powertrain Configurations and Working Principles
The configurations of CEV, IEV and IHV are shown in Figure 1.In the CEV, two central electric motors (CEM) are installed on the front axle and rear axle, respectively.Single speed transmissions are used to adjust the CEM speed and torque to coordinate with the vehicle maximum speed and dynamic performance demand.deteriorates the suspension and motor bearing working conditions, which accelerates the components' fatigue and failure [15].Compared with the electric motor, the hydraulic motor has a higher power density, which means less unsprung mass will be added if the hydraulic motor is used for in-wheel drive [16,17].So the vibration problems caused by increased unsprung mass could be mitigated.Besides, the hydraulic motor is driven by fluids, which naturally constitute the cooling system.The wheels have to work under complex environments like in water or off road, which proposes challenges for the high voltage electrical system.In contrast, the hydraulic system is more reliable in these complex working conditions.These advantages make the hydraulic motor a potential candidate for in-wheel drive [18].The hydraulic motor has been used for vehicle driving in massive researches combined with electric motors.The parallel electric hydraulic hybrid vehicle [19][20][21] and series electric hydraulic hybrid vehicle [22] have been widely investigated.These vehicles take the advantage of the high power density of hydraulic motors to recover more braking energy so that the vehicle energy economy is improved.The hydraulic motor has also been used for in-wheel drive [16].However, in this proposal, the engine is used to generate the hydraulic power so it still relies on traditional fossil fuel.
With the motivation of exploiting the merits of in-wheel drive and electrification, an in-wheel drive electric hydraulic hybrid vehicle (IHV) is investigated in this paper where the hydraulic motor is used for in-wheel drive and an electric motor is used as the power source.The energy economy and vertical vibration characteristics of the IHV are compared with the IEV and a centralized drive electric vehicle (CEV).The dynamic programming (DP) algorithm is adopted in the energy management strategy design, which helps to find the optimal energy economy of each vehicle.Due to the vehicle vertical vibration having a significant impact on the vehicle driving comfort, the vertical characteristics of each vehicle are compared based on a quarter car model.
The remainder of this paper is presented as follows: Section 2 introduces the vehicle powertrain configurations and working principles of each vehicle.In Section 3, the dynamic models of vehicle powertrains are built.Section 4 designs the energy management strategies based on dynamic programming.In Section 5, simulations are conducted to analyze the energy consumption of each vehicle.Section 6 analyses the vertical vibration characteristics of each vehicle.In Section 7, conclusions are drawn for this paper.
Vehicle Powertrain Configurations and Working Principles
The configurations of CEV, IEV and IHV are shown in Figure 1.In the CEV, two central electric motors (CEM) are installed on the front axle and rear axle, respectively.Single speed transmissions are used to adjust the CEM speed and torque to coordinate with the vehicle maximum speed and dynamic performance demand.In IEV, the in-wheel electric motors (IEM) are used to drive the vehicle.In this research, an IEM produced by Protean electric is used for analysis.The IEM parameters such as speed, torque and power are specifically designed for in-wheel drive so it can be directly installed in wheel without any additional gears for speed and torque adjustment.
In IHV, in-wheel hydraulic motors (IHM) are installed in wheel to drive the vehicle.At the moment, there is no hydraulic motor designed for in-wheel drive.However, considering the vehicle wheel speed and torque demand during driving, the dual functional axial piston hydraulic motor is a suitable candidate for in-wheel drive owning to its high power density and high speed advantages.The high pressure accumulator (HPA) is used to store energy and the low pressure accumulator (LPA) is used as an oil tank.During driving, the IHM works as a motor and the oil flows from the HPA to the LPA.During regenerative braking, the IHM works as a pump and the oil flows from the LPA to the HPA.In addition to regenerative braking, the HPA could also be charged by the central hydraulic motor (CHM).In this charging condition, the CEM drives the CHM to charge the HPA.The HPA can also be used to charge the battery through the CHM and CEM.
Electric Motor Model
The electromagnetic response of power electronics presents a higher frequency than that of mechanical driveline so the frequency oscillations from the power electronics systems can be overlooked to improve the computation efficiency and simplify the control problem [23].The maximum electric motor torque is modelled as a lookup table regarding the motor speed.The real-time electric motor torque output T m according to the driver's command can be expressed as: where α p is the accelerator pedal opening and T m_max (ω m ) is the tested maximum electric motor torque at speed ω m .
Battery Modelling
The battery parameters are affected by many factors like temperature, state of charge (SoC) and charging rate.An accurate dynamic model is difficult to build and would be very complicated.Therefore, in this paper, the battery is modelled as a simplified internal resistance model [24,25].Those battery parameters which could truly reflect the battery characteristics were obtained from the test.Based on the model, the SoC change rate is described by Equation (2).
where U oc is the open circuit voltage, R b is the battery internal resistance, Q max is the maximum capacity and P b is the battery power which is calculated by Equation (3).
where η m is the electric motor efficiency, which is modelled as a 2-D lookup table regarding to the output torque and speed.
The U oc and R b , along with SoC, are shown in Figure 2. In this model, the battery characteristics are calibrated with 25 • C temperature.
Hydraulic Motor Modelling
The hydraulic motor torque is generated by the pressure difference between HPA and LPA.By adjusting the swashplate angle, both positive and negative torques are available for vehicle driving and braking.The hydraulic motor torque is described by the following equation: where d is the hydraulic motor cylinder diameter, p n is the number of the hydraulic motor cylinders, R is the cylinder pitch radius [26,27], Δp is the hydraulic motor working pressure.η h is the hydraulic motor mechanical efficiency, which is mainly affected by the working pressure, speed and displacement.
Accumulator Modelling
The accumulator stores energy by compressing the inert gas.In this model, the compression and expansion process is considered as an adiabatic process [28].So the energy loss due to heat exchange with the environment is neglected as it is much less than the energy transferred in the charging and discharging process.Compared with the inert gas, the oil compressibility is much lower and is therefore ignored in this model [29].
The energy stored in the accumulator is described by: where E is the accumulator stored energy, 0 P is the accumulator pre-charged pressure, 0 V is the inert gas volume under the pressure 0 P , k is the gas ploy index and P is the accumulator working pressure.
Vehicle Resistance Model
The vehicle resistance mainly consists of rolling resistance, aerodynamic drag resistance and road slope resistance.The total vehicle resistant torque is derived as:
Hydraulic Motor Modelling
The hydraulic motor torque is generated by the pressure difference between HPA and LPA.By adjusting the swashplate angle, both positive and negative torques are available for vehicle driving and braking.The hydraulic motor torque is described by the following equation: where d is the hydraulic motor cylinder diameter, n p is the number of the hydraulic motor cylinders, R is the cylinder pitch radius [26,27], ∆p is the hydraulic motor working pressure.η h is the hydraulic motor mechanical efficiency, which is mainly affected by the working pressure, speed and displacement.
Accumulator Modelling
The accumulator stores energy by compressing the inert gas.In this model, the compression and expansion process is considered as an adiabatic process [28].So the energy loss due to heat exchange with the environment is neglected as it is much less than the energy transferred in the charging and discharging process.Compared with the inert gas, the oil compressibility is much lower and is therefore ignored in this model [29].
The energy stored in the accumulator is described by: where E is the accumulator stored energy, P 0 is the accumulator pre-charged pressure, V 0 is the inert gas volume under the pressure P 0 , k is the gas ploy index and P is the accumulator working pressure.
Vehicle Resistance Model
The vehicle resistance mainly consists of rolling resistance, aerodynamic drag resistance and road slope resistance.The total vehicle resistant torque is derived as: where g is the gravitational acceleration, ϕ is the road slope, ρ air is the air density, A V is the vehicle frontal area, C D is the air drag coefficient, V is the vehicle speed, f T is the rolling resistance coefficient, R W is the tyre radius.
Energy Management Strategy Design Based on Dynamic Programming
The DP is a widely used optimization method for vehicle energy consumption analysis [30][31][32].In this paper, the DP is adopted to explore the optimal energy economy of each vehicle so that the comparison is more convincing.Firstly, the driving cycle is divided into N points.At each point of 0, 1, 2, . . . . . ., N − 1, N, the vehicle speed and acceleration is determined by the driving cycle so the power demand is calculated.Besides, at each point, state variables are chosen to describe the concerned targets.In the CEV and IEV, the state variable is the battery SoC, which directly reflects the energy consumption of each vehicle.In the IHV, the state variables are the battery SoC and the HPA pressure.The HPA pressure of IHV determines how much driving torque is available.
How the state variables transfer from the current point to next point is determined by the control inputs in the current point: X is the state variables.U is the control input.With different control inputs, the energy consumption is different.In CEV, the control inputs are the front CEM torque and the rear CEM torque.In the IEV, four IEMs are adopted, so there are potentially four control inputs.However, the driving torque is normally allocated to the left wheels and right wheels evenly to reduce control complexity [33,34].Only when there are stability control or steering control requirements are all four IEMs independently controlled to generate a yaw moment for vehicle lateral dynamic control.In IHV, the front IHM torque, rear IHM torque, and CHM torque and speed are selected as the control inputs.
The DP calculates the energy consumption reversely from the Nth point to the 0th point.For point N to N − 1, it calculates all the possible control inputs and finds the minimum energy consumption J * (N − 1) from point N − 1 to N: where L(X, U) is the instantaneous energy consumption determined by X and U. Then the calculation keeps going recursively from N − 1 and the minimum energy consumption J * (n) from the point n to point N is obtained: When the calculation reaches the point 0, the minimum energy consumption J for the whole driving cycle is obtained accompanied by the optimal control inputs sequence: There are boundary conditions for the state variables and control inputs which should be satisfied during the whole process.These boundary conditions are caused by the components' physical characteristics.
In CEV, the control inputs are the front CEM torque T f _CEM and the rear CEM torque T r_CEM : The CEM torque is restricted between the minimum and maximum torque: In IEV, there are four IEMs.However, the driving torque is only allocated between the front wheels and the rear wheels.The left wheels and the right wheels are with the Energies 2021, 14, 2290 6 of 15 same torque.Therefore, the control inputs are the front IEM torque T f _IEM and rear IEM torque T r_IEM : The IEM torque is restricted between the minimum and maximum torque: In IHV, the driving torque demand is allocated to the front wheels and the rear wheels.Similar to the IEV, the driving torque is evenly allocated between the left wheels and the right wheels.Besides, the CEM and CHM are used to transfer energy between the battery and HPA.The CEM and CHM are decoupled from the wheels so that their speeds and torques could be optimized to achieve the best energy economy.The control inputs in the IHV are selected as the front IHM torque T f _I HM , rear IHM torque T r_I HM , CHM torque T CHM and speed n CHM : In IHV, the hydraulic motor swashplate angle could only be adjusted between its minimum and maximum limits, so they have limited output torques.The CHM speed n CHM and CEM speed n CEM are restricted by their speed limits.The HPA pressure P h should also be maintained between its maximum and minimum values.The boundary conditions in IHV are:
Energy Consumption Simulation Analysis
The vehicle simulation models are built with Matlab to investigate their energy consumption.In this research, a production SUV with CEV configuration is selected as the benchmark vehicle.Its vehicle parameters are shown in Table 1.The energy consumption research is based on the world harmonized light-duty vehicle test procedure class 3 (WLTP-3).It combines urban and high speed driving conditions, which are widely used to investigate the energy consumption of hybrid vehicles and electric vehicles.The WLTP-3 profile is shown in Figure 3.
Energy Consumption of CEV
The front CEM and rear CEM working points are shown in Figure 4. Most of the time it could be found that only rear CEM is used to drive the vehicle.This indicates that the CEV driving system is much oversized for normal driving conditions.The vehicle power demand and torque demand during the WLTP-3 are shown in Figure 5.It is demonstrated that the power demand is much less than the equipped motor power.However, the large motor improves the vehicle dynamic performance during accelerating and climbing.
Energy Consumption of CEV
The front CEM and rear CEM working points are shown in Figure 4. Most of the time it could be found that only rear CEM is used to drive the vehicle.This indicates that the CEV driving system is much oversized for normal driving conditions.The vehicle power demand and torque demand during the WLTP-3 are shown in Figure 5.It is demonstrated that the power demand is much less than the equipped motor power.However, the large motor improves the vehicle dynamic performance during accelerating and climbing.
Energy Consumption of CEV
The front CEM and rear CEM working points are shown in Figure 4. Most of the time it could be found that only rear CEM is used to drive the vehicle.This indicates that the CEV driving system is much oversized for normal driving conditions.The vehicle power demand and torque demand during the WLTP-3 are shown in Figure 5.It is demonstrated that the power demand is much less than the equipped motor power.However, the large motor improves the vehicle dynamic performance during accelerating and climbing.
Energy Consumption of IEV
There are not any IEVs on the market at the moment.However, the PD18 IEM designed by protean electric has been produced and promoted to the market.This IEM
Energy Consumption of IEV
There are not any IEVs on the market at the moment.However, the PD18 IEM designed by protean electric has been produced and promoted to the market.This IEM targets in-wheel drive passenger vehicles.Therefore, it is selected to drive as the benchmark vehicle to investigate the IEV energy consumption.With four IEMs, the IEV driving system power is similar to the CEV.The IEM parameters are shown in Table 2 and its efficiency map is shown in Figure 6.The IEM is designed for in-wheel drive, so it is installed on the wheel directly without any additional gears.
Energy Consumption of IEV
There are not any IEVs on the market at the moment.However, the PD18 IEM designed by protean electric has been produced and promoted to the market.This IEM targets in-wheel drive passenger vehicles.Therefore, it is selected to drive as the benchmark vehicle to investigate the IEV energy consumption.With four IEMs, the IEV driving system power is similar to the CEV.The IEM parameters are shown in Table 2 and its efficiency map is shown in Figure 6.The IEM is designed for in-wheel drive, so it is installed on the wheel directly without any additional gears.By simulation, the IEM working points during WLTP-3 are shown in Figure 6.It is shown that the rear IEM covers most of the driving torque, which means the powertrain By simulation, the IEM working points during WLTP-3 are shown in Figure 6.It is shown that the rear IEM covers most of the driving torque, which means the powertrain is also oversized in IEV.Compared with CEV, the driving torque is allocated more to the front wheels.
Energy Consumption of IHV
The IHV is a novel vehicle configuration proposed in this paper, so the powertrain parameters need to be designed here.To make sure the IHV has similar vehicle dynamic performance with the CEV and IEV, the IHM power is selected to be close to the IEM.In IHV, a reduction gear is adopted to adjust the IHM speed and torque.The CHM and CEM are disconnected with the wheels, so they just need to satisfy the vehicle power demand but not the torque demand.From Figure 5, the vehicle power demand is moderate while the torque demand is high.Therefore, only one CEM is reserved in the IHV powertrain.The CHM is selected as being of a similar power to the CEM.The parameters of the IHV are listed in Table 3.
The IHM working points during WLTP-3 are shown in Figure 7.It is shown that the IHVs also try to use only rear IHM for driving.It could also be found that the rear IHM working points distribution are different from the rear IEM.This is determined by the different efficiency maps of IHM and IEM.The IHM working points during WLTP-3 are shown in Figure 7.It is shown that the IHVs also try to use only rear IHM for driving.It could also be found that the rear IHM working points distribution are different from the rear IEM.This is determined by the different efficiency maps of IHM and IEM.The HPA inert gas real time pressure and volume are shown in Figure 8.It is shown that HPA pressure is always lower than its maximum working pressure.When the HPA is used for regenerative braking, the battery charging burden is relieved.The HPA inert gas real time pressure and volume are shown in Figure 8.It is shown that HPA pressure is always lower than its maximum working pressure.When the HPA is used for regenerative braking, the battery charging burden is relieved.The CEM and CHM working points are shown in Figure 9.As mentioned before, in IHV, the CEM and CHM are disconnected from the wheels.Therefore, under a certain power demand, the CEM and CHM could work at the most efficient point.The CEM and CHM working points are shown in Figure 9.As mentioned before, in IHV, the CEM and CHM are disconnected from the wheels.Therefore, under a certain power demand, the CEM and CHM could work at the most efficient point.The CEM and CHM working points are shown in Figure 9.As mentioned before, in IHV, the CEM and CHM are disconnected from the wheels.Therefore, under a certain power demand, the CEM and CHM could work at the most efficient point.
Energy Consumption Comparison
The energy consumption and SoC of each vehicle is shown in Figure 10 and listed in Table 4.It could be found that the IEV consumes slightly more energy than the CEV.The main reason is that the IEM has lower efficiency than the CEM, especially at a low speed area.These results indicate that although the driveline is simplified in IEV, which helps reduce power loss, the lower IEM efficiency makes the IEV not very competitive on the energy economy.However, as mentioned above, the advantage of the IEV is in improving the vehicle stability and handling performance by torque vector control.The energy consumption of IHV is 40% more than the CEV and 34% more than the IEV, which demonstrates a bad energy economy of the IHV.The reason for this is that the hydraulic
Energy Consumption Comparison
The energy consumption and SoC of each vehicle is shown in Figure 10 and listed in Table 4.It could be found that the IEV consumes slightly more energy than the CEV.The main reason is that the IEM has lower efficiency than the CEM, especially at a low speed area.These results indicate that although the driveline is simplified in IEV, which helps reduce power loss, the lower IEM efficiency makes the IEV not very competitive on the energy economy.However, as mentioned above, the advantage of the IEV is in improving the vehicle stability and handling performance by torque vector control.The energy consumption of IHV is 40% more than the CEV and 34% more than the IEV, which demonstrates a bad energy economy of the IHV.The reason for this is that the hydraulic accumulator has a much lower energy density than the battery, so when the CEM is used to charge the HPA, it is equivalent to use the CEM to drive the vehicle.The total driveline efficiency is degraded by the hydraulic circuit.accumulator has a much lower energy density than the battery, so when the CEM is used to charge the HPA, it is equivalent to use the CEM to drive the vehicle.The total driveline efficiency is degraded by the hydraulic circuit.
Vertical Vibration Analysis
The vehicle unsprung mass of IEV and IHV are increased by in-wheel motors.The increased unsprung mass remarkably changes the vehicle vertical vibration characteristics and degrades the vehicle driving comfort [35].In this section, the vertical vibration characteristics of each vehicle are compared.A quarter car dynamic model is built to research the vertical vibration as shown in Figure 11.In the model, the stiffness and damping are considered as constant parameters [36,37].For different vehicles, they have the same quarter car model but with different parameters.
Vertical Vibration Analysis
The vehicle unsprung mass of IEV and IHV are increased by increased unsprung mass remarkably changes the vehicle vertical v and degrades the vehicle driving comfort [35].In this section, characteristics of each vehicle are compared.A quarter car dyna research the vertical vibration as shown in Figure 11.In the mo damping are considered as constant parameters [36,37].For differe the same quarter car model but with different parameters.
where m s is the sprung mass, x s is the sprung mass displacement, k s is the suspension stiffness, c s is the suspension damping, m u is the unsprung mass, x u is the unsprung mass displacement, k t is the tyre stiffness, x g is the road excitation.In this model, the tyre damping is ignored due to its small effect on the vertical vibration [38].The parameters of each vehicle are shown in Table 5.In IEV, two CEMs are removed so that the sprung mass is reduced compared with CEV.The IEMs increase the unsprung mass.In IHV, one CEM is removed but a CHM and two accumulators are installed on-board, so the sprung mass does not significantly change.As mentioned, the IHM has a higher power density than the IEM, so the IHM mass is much smaller than the IEM with same power, which explains why the IHV unsprung mass is smaller than the IEV.To investigate the vehicle vertical vibration characteristics under the road excitation, the state function and output functions are built as follows: In the equation, the sprung mass displacement, sprung mass velocity, unsprung mass displacement, and unsprung mass velocity are selected as the state vector X.The sprung mass acceleration, unsprung mass acceleration, suspension deformation and tyre deformation are selected as the output vector Y [39].The road excitation is selected as the input vector.
From Equation ( 17), the state function and output function are obtained as shown in Equations ( 20) and (21).
The frequency response analysis under road excitation with 1 m amplitude and different frequencies is conducted and the results are shown in Figure 12.There are two natural frequencies in the quarter car system.In IEV, the natural frequencies and amplitudes are all greatly changed.In IHV, the first natural frequency is very close to the CEV but the second natural frequency is decreased.
Figure 12a shows the sprung mass acceleration frequency response to the road excitation.It is shown that the sprung mass acceleration is significantly increased in IEV with both natural frequencies, which indicates a worse driving comfort.The IHV sprung mass acceleration response is almost the same as the CEV at the first natural frequency.At the second natural frequency, the IHV sprung mass acceleration response is only slightly higher than the CEV.So from the vertical acceleration perspective, the IHV maintains the vehicle driving comfort while the IEV degrades the driving comfort.
Figure 12b shows that the unsprung mass acceleration responses of all vehicles are quite small at the first natural frequency.At the second natural frequency, the acceleration response of IEV and IHV are reduced due to larger unsprung mass.
The frequency response analysis under road excitation with 1 m amplitude and different frequencies is conducted and the results are shown in Figure 12.There are two natural frequencies in the quarter car system.In IEV, the natural frequencies and amplitudes are all greatly changed.In IHV, the first natural frequency is very close to the CEV but the second natural frequency is decreased.Figure 12a shows the sprung mass acceleration frequency response to the road excitation.It is shown that the sprung mass acceleration is significantly increased in IEV with both natural frequencies, which indicates a worse driving comfort.The IHV sprung mass acceleration response is almost the same as the CEV at the first natural frequency.At the second natural frequency, the IHV sprung mass acceleration response is only slightly higher than the CEV.So from the vertical acceleration perspective, the IHV maintains the vehicle driving comfort while the IEV degrades the driving comfort.The suspension deformation with different excitation frequencies is shown in Figure 12c.The IEV has a reduced suspension deformation at the first natural frequency; however, it has an increased suspension deformation at the second natural frequency.The IHV suspension deformation is also larger than the CEV at the second natural frequency.It should also be noticed that although the suspension deformations of IEV and IHV are increased at the second natural frequency, they are still smaller than the CEV suspension deformation at the first natural frequency.
The tyre deformation, which represents the dynamic wheel load, is shown in Figure 12d.It is demonstrated that at the first natural frequency, the larger unsprung mass in IEV and IHV do not remarkably increase the wheel loads.However, the wheel loads are increased a lot at the second natural frequency in IEV and IHV, which proposes higher requirements for tyre strength.The IHV dynamic wheel load is smaller than the IEV dynamic wheel load.
Conclusions
This paper compares the energy economy and vibration characteristics of CEV, IEV and IHV.By the energy management strategy designed with the DP algorithm, the IEV and IHV consume more energy than the CEV, which makes IEV and IHV incompetent for energy saving.In addition to the advantages of independent wheel torque control, the IEV and IHV also have the vibration problems caused by increased unsprung mass.The hydraulic motor has a higher power density than the electric motor, and so less unsprung mass is added in the IHV than the IEV.The vibration analysis results demonstrate that the vibration problems caused by increased unsprung mass could be alleviated in IHV, especially in the vehicle body acceleration, which directly affects driving comfort.Besides, the heat dissipation and IEM high voltage safety challenges are cancelled in IHV.Based on the above analysis, the IHV is more suitable for off-road vehicles which work in harsh conditions such as mining, forestry and agriculture vehicles.For these vehicles, the in-wheel drive improves the vehicle handling performance and agility by independent wheel torque control.Hydraulic motors also have a better reliability under bad working conditions such as muddy ground.
In the future, the following researches could be conducted.Firstly, this paper researches the optimal energy consumption of each vehicle by DP.It is a global optimization method, which helps to find the least energy consumption over a known driving condition.In real driving, it is hard to get prior driving condition information and so rule-based or real-time optimization energy management strategies should be designed.Secondly, the longitudinal vibration also deserves research.Comparisons could be made on how the IHM and IEM torque affect the vehicle longitudinal vibration.Besides, the lateral dynamics are also changed by different unsprung mass, which affects the steering control and the torque vector control.
Figure 10 .
Figure 10.Energy consumption and SoC of each vehicle.
Figure 10 .
Figure 10.Energy consumption and SoC of each vehicle.
Figure 11 .
Figure 11.Quarter car dynamic model.The quarter car model is described by Equation (17):
Figure 12 .
Figure 12.Frequency response of vehicle-to-road excitation.
Figure 12 .
Figure 12.Frequency response of vehicle-to-road excitation.
Table 1 .
Parameters of the CEV.
Table 1 .
Parameters of the CEV.
Table 1 .
Parameters of the CEV.
Table 4 .
Energy consumption and SoC comparison.
Table 4 .
Energy consumption and SoC comparison.
Table 4 .
Energy consumption and SoC comparison.
Table 5 .
Model parameters of different vehicles. | 7,928.2 | 2021-04-19T00:00:00.000 | [
"Engineering",
"Environmental Science"
] |
The multidimensional nucleon structure
We discuss different kinds of parton distributions, which allow one to obtain a multidimensional picture of the internal structure of the nucleon. We use the concept of generalized transverse momentum dependent parton distributions and Wigner distributions, which combine the features of transverse-momentum dependent parton distributions and generalized parton distributions. We show examples of these functions within a phenomenological quark model, with focus on the role of the spin-spin and spin-orbit correlations of quarks.
Introduction
During the past two decades, a lot of attention has been paid to generalized parton distributions (GPDs) [1][2][3][4][5][6][7] and to transverse-momentum dependent parton distributions (TMDs) [8][9][10][11][12].Those objects are of particular interest because they describe the three-dimensional parton structure of hadronsthe distribution of the parton's longitudinal momentum and transverse position in the case of GPDs, and the distribution of the parton's longitudinal momentum and transverse momentum in the case of TMDs.Even though GPDs and TMDs already are quite general entities, the maximum possible information about the (two-) parton structure of strongly interacting systems is encoded in GT-MDs [13][14][15].GTMDs can reduce to GPDs and to TMDs in certain kinematical limits, and therefore they are often denoted as mother distributions.Further limits/integrations reduce them to collinear parton distribution functions and form factors.The Fourier transform of GTMDs can be interpreted as Wigner distributions [16][17][18], the quantum-mechanical analogue of classical phase-space distributions.A classification of GTMDs for quarks (through twist-4) for a spin-0 target was given in Ref. [13], followed by a corresponding work for a spin- 1 2 target [14].In Ref. [15], the counting of quark GTMDs was independently confirmed, and a complete classification of gluon GTMDs was provided as well.Gluon GTMDs appear when describing high-energy diffractive processes like vector meson production or Higgs production [19][20][21] in the so-called k T -factorization in Quantum Chromodynamics.Recently, it was also suggested that the Wigner distributions of small-x gluons are closely related to the color dipole scattering amplitude [22].For a comprehensive review of both the actual status and future developments in the theoretical and experimental investigation of GPDs, TMDs and Wigner functions we refer to a series of papers collected in a "Topical issue on the 3-D structure of the nucleon" [23].Here, we review some aspects related to modelling and imaging of the nucleon structure [24].In Sect.2, we revisit the definition of the Wigner distributions obtained by Fourier transform of the GTMDs to the impact-parameter space.We identify all the possible correlations between target polarization, quark polarization and quark orbital angular momentum (OAM) encoded in these phase-space distributions, and we show results for a few selected examples.In Sect. 3 and 4, we discuss some of the complementary information encoded in GPDs and TMDs, in particular with regards to the information on the quark OAM.Concluding remarks are given in the final section.
Wigner distributions
The quark GTMD correlator is defined as [14,15] where W is an appropriate Wilson line ensuring color gauge invariance, k is the quark average fourmomentum conjugate to the quark field separation z, and |p, Λ is the spin-1/2 target state with fourmomentum p and light-front helicity Λ.A proper definition of the GTMDs should include also a soft-factor contribution [25].However, it is not relevant for the following multipole analysis.At leading twist, one can interpret with Γ S q = γ + + S q L γ + γ 5 + S q j T iσ j+ T γ 5 , as the GTMD correlator describing the distribution of quarks with polarization S q inside a target with polarization S [26].
The corresponding phase-space distribution is obtained by an appropriate Fourier transform [18] ρ S S q (x, k T , b T ; P, η) = where x = k + /P + and k T are, respectively, the longitudinal fraction and transverse component of the quark average momentum, b T is the quark average impact parameter conjugate to the transversemomentum transfer Δ T , ξ = −Δ + /2P + is the fraction of longitudinal momentum transfer, and η = +1 (η = −1) indicates a future-(past-) pointing Wilson line.This phase-space distribution can be interpreted semi-classically as giving the quasi-probability of finding a quark with polarization S q , transverse position b T and light-front momentum (xP + , k T ) inside a spin-1/2 target with polarization S [18].Thanks to the hermiticity properties of the GTMD correlator (2), these phase-space distributions are always real-valued [27], consistently with their quasi-probabilistic interpretation.Considering the various polarization configurations, one finds that there are 16 Wigner distributions just like there are 16 possible GTMDs [14,15].By construction, the real and imaginary parts of these GTMDs have opposite behavior under naive time-reversal transformation.Similarly, each Wigner distribution can be separated into naive T-even and T-odd contributions, ρ S S q = ρ e S S q + ρ o S S q , with ρ e,o S S q (x, k T , b T ; P, η) = ±ρ e,o S S q (x, k T , b T ; P, −η) = ±ρ e,o S S q (x, −k T , b T ; − P, η).We can interpret the Teven contributions as describing the intrinsic distribution of quarks inside the target, whereas the naive T-odd contributions describe how initial-and final-state interactions modify these distributions.The relativistic phase-space distribution is linear in S and S q S y S q y and can further be decomposed into two-dimensional multipoles in both k T and b T spaces [28].While there is no limit in the multipole order, parity and time-reversal give constraints on the allowed multipoles.It is therefore more appropriate to decompose the Wigner distributions ρ X as follows where X are the basic (or simplest) multipoles allowed by parity and time-reversal symmetries, multiplied by the coefficient functions C (m k ,m b ) X which depend on P and T-invariant variables only.The couple of integers (m k , m b ) gives the basic multipole order in both k T and b T spaces.All the contributions ρ X can be understood as encoding all the possible correlations between target and quark angular momenta, see Table 1.In order to obtain a two-dimensional representation of the Wigner functions, we integrate these phasespace distributions over x and discretize the polar coordinates of b T .We also set η = +1 and choose P = e z = (0, 0, 1) so that bT = (cos φ b , sin φ b , 0) and kT = (cos φ k , sin φ k , 0).The resulting transverse phase-space distributions are then represented as sets of distributions in k T -space with the origin of axes lying on circles of radius |b T | at polar angle φ b in impact-parameter space.In particular, we choose to represent only eight points in impact-parameter space lying on a circle with radius |b T | = 0.4 fm and φ b = kπ/4 with k ∈ Z .Also, for a better legibility, the k T -distributions are normalized to the absolute maximal value over the whole circle in impact-parameter space.
In the following, we will show results from the light-front constituent quark model (LFCQM) [29], which has been extensively applied to calculate form factors [30], TMDs [31][32][33][34] and GPDs [35][36][37][38], showing a typical accuracy of 30%.Since our purpose is simply to illustrate the multipole structure, we computed only the naive T-even contributions in this model.The naive T-odd contributions are obtained by extracting the coefficient functions from the naive T-even part and multiplying them by the appropriate basic multipoles.Therefore, the global sign of these naive T-odd contributions has been chosen arbitrarily.Only a proper calculation including initial-and/or final-state interactions can determine these global signs.
As an example, we discuss here the Wigner distribution for unpolarized quark in a longitudinal polarized target.We find only two phase-space distributions 1. Correlations between target polarization (S L , S T ), quark polarization (S q L , S q T ) and quark OAM ( q L , q T ) encoded in the various phase-space distributions ρ X , with X = UU, LU, . . . .which are represented in Fig. 1.The corresponding basic multipoles are None of these survive integration over k T or b T .Both therefore represent completely new information which is not accessible via GPDs or TMDs at leading twist.The k T -dipole in ρ (1,1) LU signals the presence of a net longitudinal component of quark OAM correlated with the target longitudinal polarization S L .By reversing the target longitudinal polarization S L , one reverses also the orbital flow.The coefficient function C (1,1) LU then gives the amount of longitudinal quark OAM in a longitudinally polarized target S L q L [18].Similarly, the contribution ρ (2,2) LU gives the difference of radial flows between quarks with opposite OAM S L q L , with the coefficient function C (2,2) LU representing in some sense the strength of the S L q L -dependent part of the force felt by the quark due to initial-and final-state interactions.As a matter of fact, the quark OAM can be obtained from the ρ LU distribution as [18,27,39] Since we are working here with a staple-like gauge link, l q z is the canonical version of quark OAM [40].On the other side, using a straight gauge link, Eq. ( 11) gives the kinetic OAM appearing in the Ji decomposition, as discussed in Sect. 4. From Fig. 1, we also note the ρ o LU cannot contribute to the quark OAM, and hence the quark OAM is η−independent [41][42][43].
Transverse Momentum Dependent Parton distributions
The forward limit (Δ = 0) of the correlator (1) corresponds to a transverse momentum dependent quark-quark correlator that can be parametrized in terms of 8 TMDs, depending on the possible polarizations for the nucleon and quark (see Table 2).They are a natural extension of collinear parton quark pol.
distributions from one to three dimensions in momentum space, being functions of both the longitudinal quark momentum fraction x and the square of the transverse momentum k T .The knowledge of TMDs allows us to build tomographic images of the inner structure of the nucleon in momentum space.The multipole pattern in k T is clearly visible in Table 2.The TMDs f 1 , g 1L and h 1 give the strength of monopole contributions and correspond to matrix elements without a net change of helicity between the initial and final states.The TMDs f ⊥ 1T , g 1T , h ⊥ 1 , and h ⊥ 1L give the strength of dipole contributions and correspond to matrix elements involving one unit of helicity flip, either on the nucleon side ( f ⊥ 1T and g 1T ) or on the quark side (h ⊥ 1 and h ⊥ 1L ).Finally, the TMD h ⊥ 1T corresponds to matrix elements where both the nucleon and quark helicities flip, but in opposite directions.Conservation of total angular momentum tells us that helicity flip is compensated by a change of OAM [31], which manifests itself by powers of k T /M.The corresponding quadrupole structure in k T is shown in Fig. 2, as obtained from a LFCQM [31].The function h ⊥ 1T has attracted a particular interest, since it has been suggested, on the basis of some quark-model calculations [44,45], that it may be related to the quark OAM: However, Eq. ( 12) is not a rigorous expression, and holds only in a restricted class of quark models [26,46].In general, no direct quantitative relations between OAM and TMDs should actually be expected as the former represents a correlation between parton position and momentum, whereas the latter only provide information about the momentum distribution.Nevertheless, TMDs do provide some indirect information about the OAM content of the nucleon, for example, by constraining the nucleon light-front wave functions that are eigenstates of the OAM [27].
Generalized Parton Distributions
When integrating the correlator (1) over k T , one obtains an off-diagonal quark-quark correlator that can be parametrized in terms of combinations of 8 GPDs (see Table 3).Comparing the entries in Tables 3 and 2, one notices that the same multipole pattern appears, where the role of k T in Table (2) is played by Δ T in Table (3).Although direct links between GPDs and TMDs cannot exist [14,47], this correspondence leads us to expect correlations between signs or similar orders of magnitude [48,49].The GPDs are functions of x, ξ, and t = −Δ 2 .Just like GTMDs and Wigner distributions are connected by Fourier transform at ξ = 0, one also finds a direct connection between GPDs at ξ = 0 and parton distributions in impact-parameter space.The multipole structure in b T is the same as in Table 3, with the only difference that there are no polarization effects in the impact-parameter distributions for longitudinally polarized quarks in a transversely polarized proton and vice versa, since they are forbidden by time reversal.For example, the distribution of unpolarized quarks in a transversely polarized target reads as This quark density is given by the sum of a nucleon spin-independent contribution related to the GPD H and a nucleon spin-dependent contribution from the GPD E, corresponding to monopole and dipole distributions in impact-parameter space, respectively.The dipole contribution introduces a large distortion perpendicular to both the nucleon spin and the momentum of the proton, with opposite sign for u and d quarks, as shown in Fig. 3.While details of the GPD E are not known, its xintegral is equal to the Pauli form factor F 2 , which allows one to constrain the average deformation model-independently to the contribution from each quark flavor q to the nucleon anomalous magnetic moment.
Even before 3D imaging was introduced, there was great interest in GPDs due to their connection with the form factors of the energy-momentum tensor and thus to the angular momentum (spin plus quark pol.
U T x T y L
nucleon pol.orbital) carried by quarks of flavor q as described by the Ji relation [2] J q = 1 2 1 0 dx x H q (x, ξ, 0) + E q (x, ξ, 0) , where the ξ-dependence on the r.h.s.disappears upon x-integration.The quark kinetic OAM is then obtained by subtracting the quark spin contribution, which is given by the first Mellin moment of the quark helicity distribution.
Figure 1 .
Figure 1.Naive T-even (left) and T-odd (right) contributions to the transverse phase-space distribution ρ LU .Light and dark regions represent, respectively, positive and negative domains of the phase-space distributions.
Figure 2 .
Figure 2. Quark density in the transverse-momentum plane for transverse polarization of quarks and nucleon in perpendicular directions.Left (right) panel is for up (down) quarks.
Figure 3 .
Figure 3. Quark density in the impact parameter space b T for unpolarized quarks in a transversely polarized nucleon along the x direction, as obtained within a LFCQM[37].The left (right) panel is for up (down) quark. | 3,463.6 | 2016-01-01T00:00:00.000 | [
"Physics"
] |
DRAFT: Dense Retrieval Augmented Few-shot Topic classifier Framework
With the growing volume of diverse information, the demand for classifying arbitrary topics has become increasingly critical. To address this challenge, we introduce DRAFT, a simple framework designed to train a classifier for few-shot topic classification. DRAFT uses a few examples of a specific topic as queries to construct Customized dataset with a dense retriever model. Multi-query retrieval (MQR) algorithm, which effectively handles multiple queries related to a specific topic, is applied to construct the Customized dataset. Subsequently, we fine-tune a classifier using the Customized dataset to identify the topic. To demonstrate the efficacy of our proposed approach, we conduct evaluations on both widely used classification benchmark datasets and manually constructed datasets with 291 diverse topics, which simulate diverse contents encountered in real-world applications. DRAFT shows competitive or superior performance compared to baselines that use in-context learning, such as GPT-3 175B and InstructGPT 175B, on few-shot topic classification tasks despite having 177 times fewer parameters, demonstrating its effectiveness.
Introduction
With the prevalence of the Internet and social media, there is a significant demand for classifying or detecting texts related to specific topics within the vast amount of information pouring in from the Internet.For instance, on social media platforms where an overwhelming volume of content is generated, there may exist a need to monitor and filter content associated with particular issues (e.g., drugs).Additionally, with the remarkable progress in large language models (LLMs) (Brown et al., 2020;Ouyang et al., 2022;Chowdhery et al., 2022;Rae et al., 2021;Scao et al., 2022;Thoppilan et al., 2022) in recent times, there is also an increasing * Work done while at Neosapience.demand to detect specific topics within the text generated by LLMs.The use of LLMs often contains ethical concerns with the issues of hallucination, as they possess the capability to generate morally inappropriate or unintended content (Ganguli et al., 2022;Perez et al., 2022).However, as the amount of content shared on social media and generated by LLMs increase exponentially, verifying each piece of content becomes challenging for individuals.
In natural language processing (NLP), research related to the challenges mentioned earlier can be considered a topic classification task since the demand for automatically classifying texts on a specific topic exists.Recent pre-trained language models (Devlin et al., 2018;Liu et al., 2019;Clark et al., 2020;He et al., 2020) have gained considerable recognition for their ability to achieve high performance in topic classification tasks.
To train a topic classification model, it is common practice to rely on supervised learning using a training dataset with labeled data.Most existing methods on a topic classification have primarily relied on benchmark datasets (Zhang et al., 2015;Auer et al., 2007).To the best of our knowledge, they have predominantly focused on improving model performance on benchmark datasets that involve a limited number of topics rather than addressing long-tailed arbitrary topics in real-world scenarios.Regarding real-world applications, the availability of labeled datasets that cover diverse topics is often limited due to the substantial cost of building such datasets.This constraint poses a challenge for directly deploying topic classification models in practical scenarios, thereby calling for a solution that enables their flexible application.
Few-shot classification, which performs classification using few text examples, can be applied even without a training dataset for a predefined topic, enabling its extension to tasks classifying a diverse range of arbitrary topics.To the best of our knowledge, existing few-shot classification methods operate exclusively on tasks with two or more defined classes and cannot conduct in oneclass classification tasks (Zhang et al., 2023;Chen et al., 2022a;Mukherjee and Awadallah, 2020;Sun et al., 2019).However, by leveraging LLMs with in-context learning (Brown et al., 2020;Holtzman et al., 2021;Min et al., 2021), we can conduct one-class few-shot topic classification tasks across various topics, showcasing superior performance.This approach garnered significant attention due to its applicability in scenarios with limited labeled data (Zhao et al., 2021;Holtzman et al., 2021;Min et al., 2021).However, successful implementation of in-context learning relies on LLMs with billions of parameters (Kaplan et al., 2020a).Such models suffer from high computational costs, extensive resource requirements, and slow inference speed to apply in real-world applications.
To address the few-shot topic classification more efficiently in real-world applications, we propose a simple framework called Dense Retrieval Augmented Few-shot Topic classifier framework (DRAFT), which can classify arbitrary topics given limited labeled data.DRAFT uses a dense retriever model (Karpukhin et al., 2020) to construct Customized dataset, using examples of a target topic provided as queries.Subsequently, a pre-trained language model is finetuned with the Customized dataset for the topic classification task.We evaluate the performance of DRAFT by conducting experiments on general benchmarks and manually constructed datasets with 291 topics.The former datasets are widely regarded as benchmark datasets in recent classification research.In contrast, the latter datasets are manually constructed to replicate real-world scenarios, allowing for a thorough assessment of the diverse topic classification capability.They are used for one-class classification tasks where only a single topic is defined.Our experiment results demonstrate that DRAFT consistently achieves competitive or superior performance compared to LLMs, such as GPT-3 175B and Instruct-GPT 175B, which have 177 times more parameters on topic classification tasks.These findings provide strong empirical support for the efficacy of DRAFT in tackling few-shot topic classification tasks.The contributions are summarized as follows: 1. We propose DRAFT as a simple but effective framework that classifies texts related to arbitrary topics using a few labeled data.
2. To the best of our knowledge, we are the first to attempt to classify a topic in texts through a dense retriever model.
3. We introduce the MQR algorithm, which is the first to accommodate multiple queries simultaneously as inputs for the retriever.
4. The results of extensive experiments show that DRAFT achieves competitive performance compared to large language models.
Related Works
Retrieval-augmented methods Information retrieval aims to find semantically relevant documents based on a query.Traditional methods employ lexical approaches to retrieve support documents using sparse vectors (Hiemstra, 2000;Robertson et al., 2009).With the recent development of deep learning (Vaswani et al., 2017), neural network-based methods have demonstrated high performance.The bi-encoder structure (Karpukhin et al., 2020;Izacard et al., 2022a) offers the advantage of pre-encoding document candidates in an offline setting, which allows for faster computation.Nonetheless, the lack of token-level interaction between query and document tokens in the bi-encoder models can lead to lower performance compared to the cross-encoder models (Devlin et al., 2018).Nevertheless, we use a bi-encoder in DRAFT for efficient retrieval, which facilitates the immediate creation of a classifier for any given topic.
There exist various retrieval-augmented methodologies (Cai et al., 2022;Izacard et al., 2022b) in recent NLP research.They encompass solutions for tasks such as fact retrieval (Thorne et al., 2018), open-domain question answering (Chen et al., 2017;Izacard and Grave, 2020;Lewis et al., 2020;Guu et al., 2020), and others.They also include techniques applied during inference to reduce perplexity in language modeling (Khandelwal et al., 2019) and strategies operate akin to memory for specific knowledge or dialogues (Chen et al., 2022b;Fan et al., 2021).All existing retrievalaugmented methods universally handle only a single query as the input to the retriever and subsequently execute downstream tasks.However, unlike existing approaches, DRAFT processes multiple queries simultaneously as input for retrievers.
In-context learning with LLMs Recent LLMs (Thoppilan et al., 2022;Zhang et al., 2022;Scao et al., 2022;Rae et al., 2021;Shoeybi et 2019; Chowdhery et al., 2022) represent a critical development in NLP and have been considered an attempt to develop intelligent language systems with fluency approaching that of humans.According to (Kaplan et al., 2020b), as the scale of the language model increases, its performance is also improved on many tasks that typically require models with hundreds of billions of parameters.LLMs primarily perform tasks through in-context learning (ICL) (Brown et al., 2020;Holtzman et al., 2021;Min et al., 2021), which feeds concatenated prompt and k input-target examples (referred to as 'k-shot') into the model without weight updates.It exhibits superior performance over zero-shot inference across an extensive array of tasks (Zhao et al., 2021;Liu et al., 2021a)
Method
In this section, we begin by describing the application of DRAFT to a simple binary classification and elaborate on the extension of DRAFT.DRAFT comprises two stages for few-shot topic classification: (1) constructing Customized dataset from multiple queries using a dense retriever model and (2) training a classifier.Figure 1 (a) illustrates the overall process of DRAFT.
Building Customized dataset
In the first stage, we use a pre-trained dense retriever, a bi-encoder consisting of a query encoder and a passage encoder, to construct Customized dataset.Customized dataset is created by employing a few texts related to a target topic as queries.
To efficiently retrieve relevant passages from Data Collection, which serves as the external knowledge base (e.g., Wikipedia), we employ a Maximum Inner Product Search (MIPS) algorithm (Shrivastava and Li, 2014) that finds the vector with the highest inner product value with a given query vector.The retriever is defined by employing a query encoder E query and a passage encoder E passage : E query embeds query x, and E passage embeds passages z ∈ Z, where Z indicates Data Collection.
We select the top-k passages with the highest prior probability p(z | x), which is proportional to the inner product of the query and passage vectors.
Algorithm 1: Multi-Query Retrieval Result: An array C of target samples Input: An array S with n queries cos(θ) We define Customized dataset as the construction of a collection of positive and negative samples, including multiple queries, specifically designed to train a topic classifier.To build positive samples within Customized dataset, we propose the Multi-Query Retrieval (MQR) algorithm, depicted in Figure 1 (b).As outlined in Algorithm 1, MQR begins by gathering n sentences or keywords related to the specific topic to form queries.A dense retriever model for each query is employed to retrieve top-k passages, where k denotes the subspace size.From the retrieved n × k passages, only passages vectors that exceed a threshold cos(θ) determined by the average pairwise cosine similarity score among the n query vectors are retained.Unlike general dense retriever models that take a single query as input, it can accept multiple queries as input.By combining the n queries and the m passages retained from Data Collection, we collect a total of n + m positive samples.Subsequently, we create an equivalent number of negative samples by randomly selecting passages from Data Collection, thereby forming Customized dataset, which comprises 2(n + m) samples.
Training a topic classifier in DRAFT
In the following stage, we proceed with fine-tuning a pre-trained language model on the classification task, employing Customized dataset constructed in the preceding stage.The fine-tuning process is similar to (Devlin et al., 2018) for downstream tasks.It passes [CLS] token, a special classification token representing sentence-level embedding obtained from the hidden vector after passing through the encoder layers through an MLP layer.The classifier is trained using binary cross-entropy loss.
with an indicator function 1, a text x i , a label for the corresponding text y i ∈ {0, 1}, and a probability on model's prediction q.
Expanding the Capabilities of DRAFT
Negative query We can improve DRAFT's performance by introducing an additional stage after training a classifier.In this stage, we manually incorporate negative queries that belong to a semantically similar category but are different from the target topic.Constructing negative samples follows the process outlined in Section 3.1 for constructing positive samples, which uses MQR.After training the classifier with the updated Customized dataset, it becomes more robust in handling hard negatives that are difficult to classify.This expansion of DRAFT enables it to handle complex cases and enhance its overall performance.
Multi-class classification Moreover, through the expansion of the class set, it is possible to develop a multi-class classifier.For each class, MQR is employed to construct class-specific positive samples.
The training dataset for a multi-class classifier is created by merging the aggregated class-specific constructed positive samples for each class, eliminating the need for a separate process of constructing negative samples within each class due to the presence of independent other defined classes.Subsequently, the classifier is trained with the merged dataset using cross-entropy loss.
Experiments
To evaluate the performance of DRAFT, we conduct three experiments with limited labeled data in classification tasks.
3. We evaluate the multi-class classification capabilities of DRAFT using three commonly used benchmark datasets.
DRAFT Setup
We When fine-tuning a classifier, we use the AdamW (Loshchilov and Hutter, 2017) optimizer with a learning rate of 1e-5 using a linear learning rate scheduler.We divide Customized dataset into an 80% to 20% split to form the training and validation datasets, respectively.The classifier is trained by employing early stopping against the validation loss with the patience of two epochs.We perform all experiments using the PyTorch framework and three 32GB Tesla V100 GPUs.
Few-shot topic classification task
Dataset To evaluate the effectiveness of DRAFT in few-shot topic classification, specifically in diverse topic scenarios, we construct 291 test datasets.Given the absence of existing benchmark datasets specifically designed for its task, we perform web crawling on the FactsNet website 1 , which covers a broad spectrum of subjects comprising 291 distinct topics.The content on the website has a three-level hierarchical structure consisting of a major category, a subcategory, and a subtopic.The major categories are comprised of five types: Lifestyle, History, Nature, World, and Science.Additional information about datasets is in Appendix A.
In our dataset construction, we leverage contents in subtopics.We consider classifying each subtopic as a distinct topic classification task, resulting in 291 test datasets.We select subtopics with at least 1 The website is as follows: https://facts.net50 samples that belong to the positive class.For each dataset, we construct negative samples, composed of easy negatives and hard negatives, to the same size as the positive samples.Easy negatives are randomly sampled from subtopics that belong to a different subcategory than the positive ones; hard negatives are randomly mined from subtopics within the same subcategory as the positive class.
Baselines We set LLMs as baseline models due to their capability to serve as classifiers for various topics when provided with a few labeled samples for ICL.The format of ICL is described in Appendix B.3.We use two types of LLMs, GPT-3 (Brown et al., 2020) and InstructGPT (Ouyang et al., 2022), both with two versions of model sizes: 2.7B and 175B.InstructGPT is an improved version of GPT-3, fine-tuned through reinforcement learning with human feedback to enhance its understanding of prompts.To assess the capability of classifying diverse topics, we derive rankings based on the F1 score for each major category across all methodologies and subsequently compute an average rank based on the five major categories.The robustness of each methodology in topic classification can be assessed through the average rank. 1 presents the evaluation results of the few-shot classification tasks on diverse topics.We evaluate the F1 score for all 291 subtopics and aggregate the results based on the five major categories.Among the baselines with billions of parameters, except for InstructGPT 175B 1-shot, DRAFT, only with millions of parameters, demonstrates superior performance compared to the others in all categories.When considering the average rankings across five major categories, DRAFT achieves the highest rank of 1.4, followed by InstructGPT 175B 1-shot with an average rank of 1.6, implying DRAFT's optimality.Ablation study We conduct an ablation study to highlight the difficulty of few-shot topic classification across diverse topics.We establish three simple baselines in this experiment using the same datasets in Table 1.(1) Random method randomly assigns classes to a sample with a uniform distribution of positive and negative classes, where the positive class corresponds to a target topic while the negative class corresponds to all other topics.
Results and analysis Table
(2) Noun-based method classifies a sample as a target topic if any nouns from the queries exist in the sample.We use NLTK package2 to extract all nouns.
(3) Dense-based method classifies a sample using embeddings obtained from [CLS] token.If the cosine similarity score between a query vector and a sample vector surpasses a threshold determined by MQR for any of the queries, the sample is classified as a target topic.The queries used in (2) and (3) are identical to those used in DRAFT.
We observe a clear trend of DRAFT outperforming three baselines across all main categories in Table 2.It implies the difficulty of the task and highlights the limitations of simple approaches, such as Noun-based or Dense-based methods.Nevertheless, the Noun-based method outperforms LLMs in Table 1, excluding InstructGPT 175B 1-shot.Also, the most straightforward approach, Random method, surpasses some LLMs.Thus, we emphasize that LLMs are ineffective for few-shot topic classification tasks across diverse topics.
Including negative queries on DRAFT
Dataset We manually construct two additional test datasets with Religion and South Korea topics using a similar format to Section 4.2.In contrast to the automatically constructed datasets in Section 4.2 by crawling the website, five annotators manually construct datasets that determine whether each sample belongs to the positive, easy negative, or hard negative class.The easy negative and hard negative in the test dataset share the same negative class label.However, the differentiation is made to demonstrate the construction process of the negative dataset.We define easy negatives as samples unrelated to the positive class in terms of their semantic content.In contrast, hard negatives are samples that fall into semantically similar categories to positive ones but have distinct content.In Religion dataset, we define 'Jewish' and 'Islam' as positive classes.In contrast, the hard negatives consist of content that falls within the religion category but pertains to different specific religions, such as 'Buddha' and 'Hinduism'.The easy negatives are composed of content unrelated to religion altogether.The examples of classes within the dataset on Religion dataset, additional details about South Korea dataset, and instructions for annotators can be found in Appendix A.
Baselines We investigate the impact of different methods on building negative datasets in DRAFT using three distinct methods: M1, M2, and M3.M1 is defined by its use of random sampling, while M2 exclusively employs negative queries as dictated by MQR.M3 is a combination of two methods, with 50% of the dataset constructed from M1 and the remaining 50% from M2.
Detail settings We use three positive and two negative queries in Religion dataset, whereas four positive and three negative queries in South Korea dataset.The subspace size associated with each query is set at 10,000.Detailed instances of two types of queries can be seen in Appendix B.4.
Results and analysis
We evaluate the F1 score and accuracy for each methodology on the Religion and South Korea datasets.To further examine the impact of negative queries, we measure the accuracy based on the three distinct classes defined during the dataset construction process, which include the positive, easy negative, and hard negative classes.In Table 3, M1 demonstrates proficient classification of easy negatives, albeit struggles in effectively identifying hard negatives.Conversely, M2 exhibits reasonable performance in classifying hard negatives but at the expense of lower accuracy for easy negatives.Remarkably, M3, which builds a negative dataset constructed through a combination of random sampling and employment of negative queries, consistently shows superior performance.Our experimental findings emphasize the significance of M3 in effectively mitigating bias associated with negative queries while ensuring accurate classification of semantically independent content from positive samples.It verifies the potential of employing negative queries to enhance the performance of DRAFT.
Multi-class classification task
Dataset We employ three general benchmark datasets to evaluate the performance of DRAFT with a limited number of samples.AGNews (Zhang et al., 2015) is a collection of news articles used for a 4-way topic classification task.DBpedia (Auer et al., 2007) is an ontology dataset for a 14-way topic classification task.TREC (Voorhees and Tice, 2000) is a dataset for a 6-way question classification task, which differs from topic-based content.Additional details can be found in Appendix A.
Baselines Among various LLMs, we consider GPT-2 XL with 1.3B parameters (Radford et al., 2019) and GPT-3 (Brown et al., 2020) with different model sizes, such as 175B and 2.7B parameters.Results and analysis Experiments are run five times, each iteration using a different random seed for sampling queries and examples.Table 4 3 presents the accuracy results in classification on benchmark datasets.DRAFT outperforms all baselines on the topic classification tasks in both AG-News and DBpedia.Comparing DRAFT with the best performance cases of GPT-3 175B, the results show a difference of 3.7%p accuracy in AGNews and 12.4%p in DBpedia.While DRAFT achieves a lower accuracy than GPT-3 175B in TREC, it still outperforms GPT-2 XL and GPT-3 2.7B.We find that the performance of DRAFT varies across different benchmark datasets, suggesting that the attribute of Customized dataset plays a crucial role.As DRAFT uses Data Collection to construct Customized dataset, the choice of Data Collection strongly influences its performance.In our experiments, by leveraging Wikipedia as Data Collection, which primarily consists of topic-based content, DRAFT consistently outperforms all baselines with lower variance on AGNews and DBpedia, which also consist of topic-based content.However, on TREC, which involves attributes different from topic-based content, DRAFT exhibits a lower performance compared to GPT-3 175B.These results indicate that DRAFT works outstanding for classifying topics but may not exhibit robust performance in other classification tasks.
Discussion
Potential points in DRAFT In DRAFT, the number of queries and the subspace size are considered the most crucial factors among various hyperparameters.Queries provide information related to the target topic, while subspace size determines how many passages related to each query are retrieved from Data Collection.They influence the performance of DRAFT, as they significantly impact the construction of Customized dataset, which directly impacts the process of training a classifier.
We investigate the relationship between the number of queries and the subspace size by varying both variables using AGNews.The experiments are repeated five times with different configurations, and the average accuracy results are presented in Figure 2. Increasing the number of queries exhibits a positive correlation with accuracy when the subspace size is fixed.The highest accuracy of 88% is achieved with a subspace size of 10 and 50 queries.Although the increase in the number of queries is limited to 50 due to computational resource constraints, the consistent trend implies that more queries can improve performance.
We find that DRAFT has the potential for improvement with an increased number of queries.Unlike DRAFT, LLMs can suffer from degraded performance due to the majority label bias (Zhao et al., 2021) when the number of examples from the same class increases in few-shot samples.In Section 4.2, InstructGPT 175B demonstrates a noticeable decline in performance as the value of k increases in k-shot settings.Considering majority label bias and experimental results, DRAFT shows a more robust performance than LLMs.
Data Collection
We underscore the importance of Data Collection in Section 4.4.DRAFT shows the highest accuracy on DBpedia due to the similar distribution between the test dataset and Data Collection.However, classifying topics that reflect recent content becomes a challenging issue for DRAFT, which uses a Wikipedia dump from 2018 for Data Collection, since there is a discrepancy between the distribution of the training dataset and that of topics that reflect the recent content.DRAFT can simply solve the problem by building Data Collection with recent knowledge.From the perspective of injecting external knowledge into the model or framework, DRAFT offers a more straightforward approach than LLMs (Meng et al., 2022;Mitchell et al., 2021).
Real-world applications DRAFT can effectively classify content related to specific topics from the Internet or SNS.It can swiftly generate a classifier for the given topic upon user request with few queries.However, a challenge emerges as the number of tasks for classifying topics escalates significantly with the increasing number of users on the Internet or the growing quantity of topics requested.Storing the weights of all individually trained classifiers for each task is inefficient.Thus, to effectively implement DRAFT in real-world scenarios, one must consider an approach centered on parameter-efficient learning (Houlsby et al., 2019;Liu et al., 2021b;Hu et al., 2021) to allow the efficient management of weights for each task.
Conclusion
In this study, we introduce DRAFT, a simple but effective approach that first applies a dense retriever model for few-shot classification across diverse topics.Despite possessing 177 times fewer parameters than LLMs, DRAFT demonstrates superior performance in few-shot topic classification.These results imply the effectiveness of DRAFT in classifying a diverse array of real-world topics.We anticipate that DRAFT holds the potential to be implemented in practical contexts and actively contribute to addressing diverse societal challenges, including those encompassing specific topics.
Limitations
In Section 4.3, the negative query is defined as a text with content similar to the positive class but with a different topic.Although DRAFT demonstrates the ability to improve performance upon receiving a negative query, the automatic generation or construction of negative queries is necessary for real-world applications since people cannot manually provide a negative query for every topic.
Also, some ambiguous topics need to be calibrated in automatically constructed 291 datasets using the FactsNet website.For example, the queries in 'Sports' topic primarily revolve around baseball and golf.After training DRAFT, it can effectively classify content related to baseball and golf.However, after manually examining the test dataset for 'Sports' topic, it becomes apparent that examples of other sports, such as basketball and tennis, are belonged to the positive class.Although basketball and tennis undoubtedly fall under the sports category, the queries are composed solely of content related to specific examples of sports, such as baseball and golf.The ambiguity of the test dataset poses a challenge for DRAFT, proving to be a difficult task even for humans to classify these contents with the same few-shot samples accurately.Therefore, conducting human manual reviews for each of the 291 subtopics within FactsNet to filter out ambiguous topics could enhance the reliability of experimental results.
Moreover, a limitation of DRAFT lies in the need for mathematically rigorous proof for the validity of its MQR.As a result, in future research, we plan to undertake endeavors to address the quality issue of FactsNet and establish rigorous mathematical proof for evaluating the effectiveness of MQR.
Ethics Statement
We explicitly mention the copyright of the FactsNet dataset, crawled from the website.We firmly state that we use the Factset dataset simply for evaluation due to the absence of a benchmark dataset containing diverse topics.Also, we employ five annotators while building two additional manually constructed datasets in Section 4.3.Our annotators are affiliated with our company and receive compensation through wages for their labeling work.Detailed instruction for the annotation task is in Appendix A. Also, we strongly discourage any misuse of DRAFT for illegal activities.
Table 5: The detailed information includes the 'Topicnum', 'Sample-num', and 'Avg.token length', which represent the number of subtopics, the average number of samples, and the average token count, respectively.
In this study, we use a total of six datasets.Fact-sNet is used in Section 4.2.Religion and South Korea are used in Section 4.3.AGNews, DBpedia, and TREC, are used in Section 4.4.
FactsNet We manually construct 291 test datasets for few-shot topic classification tasks across diverse topics by crawling http://www.facts.net.It has a three-level hierarchical structure consisting of a major category, a subcategory, and a subtopic.The major category comprises six topics ('Lifestyle,' 'History,' 'Nature,' 'World,' 'Science,' and 'General').However, we exclude 'General' when constructing the dataset since it consists of ambiguous content that does not align well with topic classification.Detailed information for five major categories can be found in Table 5.Table 6 provides types of subcategories under each major category and all subtopics under each subcategory.In constructing the dataset, we set the positive class as 0, the easy negative class as 1, and the hard negative class as 2. The composition of the label is: (0:Positive, 1:Negative), where the positive class belongs to content related to the subtopic, and the negative class contains easy negative and hard negative.Table 7 shows example samples of datasets.
Religion Unlike FactsNet dataset, we determine whether samples are appropriate for positive and negative classes by examining each sample individually.Five annotators label each sample to determine if it contains content related to the topics defined in Religion.Samples for the hard negative class are constructed with the same method.The instruction for annotators regarding all samples is as follows: 'Please choose the correct label for the following sentence.If the following sentence is related to Jewish or Islam, choose 0. If the fol-lowing sentence is not related to religion, choose 1.If the following sentence is related to Buddha or Hinduism, choose 2. Answer: 0, 1, 2'.The final label for all classes is determined through a majority vote.Religion dataset consists of 78 samples from https://www.history.com/topics/religion.The composition of the label is: (0:Positive, 1:Negative), where the negative class contains both easy negative and hard negative.Examples of the dataset can be seen in Table 8.
South Korea For South Korea, the test dataset consists of 112 samples from http://www.facts.net,https://pitchfork.com,https://www.britannica.com,and https://en.yna.co.kr.This dataset is constructed using a similar method to Religion dataset.Positive samples are related to 'South Korea'.Hard negatives are composed of content related to other Northeast Asian countries, such as 'North Korea', 'China', and 'Japan', which fall under the same country category but differ from South Korea.The instruction for annotators regarding all samples is as follows: 'Please choose the correct label for the following sentence.If the following sentence is not related to the country, choose 1.If the following sentence is related to South Korea, choose 0. If the following sentence is related to North Korea, China, or Japan, choose 2. Answer: 0, 1, 2'.The composition of the label is: (0:Positive, 1:Negative).Examples of the dataset can be seen in Table 9.
AGNews A collection of news articles from ComeToMyHead is used for a 4-way topic classification problem.We use a test dataset consisting of 7,600 samples from https://huggingface.co/ datasets/ag_news.The composition of the label is: (0:World, 1: Sports, 2:Buisness, 3:Sci/Tec).
DBpedia DBpedia ontology classification dataset is used for a 14-way topic classification problem.
TREC Text Retrieval Conference Question Classification is used for 6-way question classification tasks, which differ from topic-based content classification.The sample consists of a question, and the labels are divided into six types of question answers.A test dataset consisting of 500 samples is used from https://huggingface.co/datasets/trec.The composition of the label is: (0:Abbreviation, 1:Entity, 2:Description and abstract concept, 3:Human being, 4:Location, 5:Numeric value).
B Details of experiment B.1 Resources
When training a dense retriever model in DRAFT, a bi-encoder, we employ a Distributed Data Parallel (DDP) setting with three GPUs.However, we only use a single GPU to train the classifier for the topic classification task in DRAFT.
During the experiments with LLMs, we use Ope-nAI's API 4 and conduct ICL.The cost for GPT-3 and InstructGPT models, with a model size of 175B, is $0.02 per thousand tokens, while the cost for a model size of 2.7B is $0.0004 per thousand tokens.Due to API costs, we run the LLMs experiments directly only in Section 4.2, and in Section 4.4, we take the results from (Zhao et al., 2021).Therefore, the candidates for k in the k-shot setting differ between them.
B.2 Hyperparameters
Hyperparameter settings for training a bi-encoder are identical to those of (Karpukhin et al., 2020).In all experiments, all classifiers in DRAFT use a fixed batch size of 256 and a maximum token length of 128.As mentioned in Section 4.4, the subspace and number of queries are tuned using grid search for hyperparameter search, using accuracy as the criterion, while the remaining hyperparameters are not tuned.The values used for the subspace size and the number of queries are [1, 5, 10, 50, 100, 500, 1000] and [5, 10, 15, 20, 25, 50], respectively.The samples extracted from the training datasets of benchmark datasets in Section 4.4 are randomly selected using five random seeds: [1234,5678,1004,7777,9999].
B.3 Prompts format
We refer to (Chiu et al., 2021) for the prompt format on LLMs for ICL in Section 4.2.Table 11 lists examples of prompt formats.The prompt format for LLMs in Section 4.4 can be found in (Zhao et al., 2021).In Section 4.2, the queries obtained from DRAFT, sourced from Quick Facts, are additionally utilized as ICL examples for the LLMs.On the other hand, in Section 4.3, five annotators formulate both positive and negative queries relevant to defined classes in Religion and South Korea.Queries used in Section 4.2 and Section 4.3 can be seen in Table 10.For Section 4.4, we select queries randomly from the training dataset, using the random seed referred to in Appendix B.2.
Given the absence of training datasets, we adopt Quick Facts, a collection of five texts associated with each subtopic in FactsNet, as queries for DRAFT and examples of ICL, serving as sample instances of the positive class.We employ various ICL examples from Quick Facts for LLMs, specifically selecting one, three, or five examples.For DRAFT, we configure a set of five examples as queries, with a subspace size of 10,000 allocated for each query.The examples of Quick Facts can be seen in Appendix B.4.
Figure 2 :
Figure 2: Heatmap shows the impact of the number of queries and subspace size on DRAFT using AGNews.
4
https://openai.com/api/pricing/B.4 Query examples al., Overall pipeline of DRAFT.DRAFT receives n queries as input, and a trained classifier is only used in the test phase.(b) Illustration of MQR in two-dimensional space.A circle represents the normalized embedding space of texts in Data Collection.For each query, passages only within an angle size θ, calculated as a threshold from n query vectors, are retrieved as positive samples, while others are classified as negative samples.
Table 1 :
F1 scores on few-shot topic classification tasks.We use k-shot setting, where k denotes the number of examples with labels for ICL on LLMs.We present the average score for each subtopic within its corresponding major category.The values within parentheses indicate the ranking of the 13 methods based on the highest scores for each row.'Avg.Rank' represents the average ranking for each method.
Table 4 :
Results show accuracy on benchmark datasets.'k-shot' represents the number of examples used in ICL.All values are presented in the mean std format. | 7,813.4 | 2023-12-05T00:00:00.000 | [
"Computer Science"
] |
Self-Adaptive Pendulum-Ball Switches for Piezoelectric Synchronous-Extraction Circuits
Electronic synchronous switches are usually used to enhance the performance of piezoelectric energy-extraction circuits, but the electronic components leading to additional power consumption are not desired for energy extraction. In view of the advantage of mechanical switches without power consumption, this article proposed a synchronous-switch circuit which can adapt to the amplitude of a cantilever-beam-vibration generator with less energy loss. This mechanical switch consists of two pendulum balls and two buffer springs. This switch mechanism can automatically adapt to the cantilever-displacement amplitude, control the closing and opening of switches with the decrease in phase advance angle, and increase in energy-extraction efficiency. Different from previous adaptive mechanical switches, this unique pendulum-ball mechanism can not only reduce the weight and volume of the generator to improve the energy density, but can also simply adjust the pendulum length to achieve better harvesting performance. It is verified experimentally that the adaptive mechanical switch can close and open automatically under different cantilever amplitudes and excitation frequencies; the results show that the optimal power of the proposed circuit can reach 4.2 times that of the standard circuit. In order to further optimize the adaptive mechanical switch, the parameters of the swing-ball mechanism affecting harvesting performance is analyzed.
Introduction
With more and more low-power electronic components, energy harvesting is a key technology for the power supply for wireless sensor network. Piezoelectric materials with high energy density and low cost are widely used in vibration-energy harvesting [1,2]. In addition, a piezoelectric-energy generator can supply power to wireless sensors [3] and wearable devices [4], which not only saves energy but also greatly improves the service life of the device.
A vibration-energy generator is mainly composed of mechanical power generation and an energy-extraction circuit. To improve the energy-extraction efficiency of the generator, on the one hand, the energy-generator structure can be optimized to increase the bandwidth [5][6][7][8]; on the other hand, the energy-extraction circuit can be improved, such as SSHI (Synchronized Switching Harvesting on an Inductor) [9,10], DSSH (Double SSH) [11], SECE (Synchronous Electric-Charge Extraction) [12], OSECE (Optimized SECE) [13], Tunable SECE [14], etc. According to the research, the energy-extraction efficiency of these circuits is higher than that of the traditionally standard energy-extraction circuit, but their performance needs further study. The typical energy-extraction circuits mentioned above are shown in Figure 1. Among them, a simple one is the standard circuit which compromises a rectifier and a filtering capacitance. However, the generator's charge is not completely transferred to the energy-storage element; thus, the performance is poor in low-electromechanical-coupling cases. To fully utilize the generated charge and enhance Most of the circuits depend on the synchronous switches to close and open near the voltage peak to increase the extraction efficiency, while common synchronous switches include electronic circuit breakers [15][16][17][18][19][20], speed-control switches [21] and mechanical switches [22][23][24][25][26]. Among the above switches, electronic circuit breakers and speed-control switches are controlled by electronic devices, which requires a certain starting voltage and consumes part of the power, while the starting voltage of the mechanical switch is low and does not consume extra energy. In fact, most of the current mechanical switches [22][23][24] are designed with fixed electrodes; when the amplitude is constantly changing, the mechanical switches can hardly work normally, which is not conducive to energy extraction. In addition, there is a mechanical switch [26] design of two-degree-of-freedom mechanism, which can only work normally near the natural frequency and has poor environmental adaptability. Another two kinds of adaptive mechanical switches [27,28] have been designed, which can work normally under most conditions, and the energy extraction efficiency is greatly improved, while the extraction efficiency is also limited by the large phase advance when the mechanical switch is closed. Recently, Liu et al. [29] presented a mechatronic switch using the snubber structure of viscous materials; the harvesting performance of the harvester is sensitive to the parameters of the auxiliary oscillator or snubber structure, especially the stiffness, but the harvesting performance is slightly affected by the auxiliary mass. Obviously, such a complex structure makes it difficult to adjust and optimize the energy harvester. Therefore, an adaptive mechatronic switch with easy ad- Most of the circuits depend on the synchronous switches to close and open near the voltage peak to increase the extraction efficiency, while common synchronous switches include electronic circuit breakers [15][16][17][18][19][20], speed-control switches [21] and mechanical switches [22][23][24][25][26]. Among the above switches, electronic circuit breakers and speed-control switches are controlled by electronic devices, which requires a certain starting voltage and consumes part of the power, while the starting voltage of the mechanical switch is low and does not consume extra energy. In fact, most of the current mechanical switches [22][23][24] are designed with fixed electrodes; when the amplitude is constantly changing, the mechanical switches can hardly work normally, which is not conducive to energy extraction. In addition, there is a mechanical switch [26] design of two-degree-of-freedom mechanism, which can only work normally near the natural frequency and has poor environmental adaptability. Another two kinds of adaptive mechanical switches [27,28] have been designed, which can work normally under most conditions, and the energy extraction efficiency is greatly improved, while the extraction efficiency is also limited by the large phase advance when the mechanical switch is closed. Recently, Liu et al. [29] presented a mechatronic switch using the snubber structure of viscous materials; the harvesting performance of the harvester is sensitive to the parameters of the auxiliary oscillator or snubber structure, especially the stiffness, but the harvesting performance is slightly affected by the auxiliary mass. Obviously, such a complex structure makes it difficult to adjust and optimize the energy harvester. Therefore, an adaptive mechatronic switch with easy adjustment of structural parameters is expected. Furthermore, though there have been extensive researches on mechanical switches, most of them focus on how to automatically adapt to the displacement amplitude of the harvester. On this basis, there are few investigations on lighter and smaller mechanical switches to improve the energy density of the harvester.
In this paper, a novel lightweight SSHI-PBMS (SSHI with Pendulum-Ball Mechanical Switch) circuit is proposed as seen in Figure 2. The proposed design is composed of a main piezoelectric generator and two auxiliary oscillators. Specifically, the cantilever beam with PZT and adjustable mass is used as the generator to convert vibration energy into electrical energy, which contributes to evaluating the performance of mechanical switches. With regard to the auxiliary oscillator, it includes a cycloid with adjustable length and a ball with adjustable mass. This adaptive mechanical switch is composed of two pendulum-ball mechanisms and two buffer springs fixed at the end of the cantilever beam. The equivalent stiffness of the moving electrode is very low so that the phase advance angle is very small; therefore, the energy-extraction efficiency is further improved. Moreover, the stiffness of the auxiliary oscillator depends on the pendulum length, which indicates that the pendulum length can be simply adjusted to improve the performance of the auxiliary oscillator, so as to ensure that the energy harvester can work efficiently. The proposed mechanical switch can adapt to the peak displacement of the cantilever and work normally in a wide frequency range without additional energy consumed. The experiments show that the proposed circuit can work normally under different amplitudes and excitation frequencies; the maximum harvested power of the proposed circuit is 4.2 times that of the standard circuit and the harvested power is also higher than other adaptive mechanical-switch circuits. Obviously, the harvested energy of the proposed circuit can fully meet the power demand of most wireless sensors.
Micromachines 2022, 13, x FOR PEER REVIEW 3 of 16 justment of structural parameters is expected. Furthermore, though there have been extensive researches on mechanical switches, most of them focus on how to automatically adapt to the displacement amplitude of the harvester. On this basis, there are few investigations on lighter and smaller mechanical switches to improve the energy density of the harvester.
In this paper, a novel lightweight SSHI-PBMS (SSHI with Pendulum-Ball Mechanical Switch) circuit is proposed as seen in Figure 2. The proposed design is composed of a main piezoelectric generator and two auxiliary oscillators. Specifically, the cantilever beam with PZT and adjustable mass is used as the generator to convert vibration energy into electrical energy, which contributes to evaluating the performance of mechanical switches. With regard to the auxiliary oscillator, it includes a cycloid with adjustable length and a ball with adjustable mass. This adaptive mechanical switch is composed of two pendulumball mechanisms and two buffer springs fixed at the end of the cantilever beam. The equivalent stiffness of the moving electrode is very low so that the phase advance angle is very small; therefore, the energy-extraction efficiency is further improved. Moreover, the stiffness of the auxiliary oscillator depends on the pendulum length, which indicates that the pendulum length can be simply adjusted to improve the performance of the auxiliary oscillator, so as to ensure that the energy harvester can work efficiently. The proposed mechanical switch can adapt to the peak displacement of the cantilever and work normally in a wide frequency range without additional energy consumed. The experiments show that the proposed circuit can work normally under different amplitudes and excitation frequencies; the maximum harvested power of the proposed circuit is 4.2 times that of the standard circuit and the harvested power is also higher than other adaptive mechanicalswitch circuits. Obviously, the harvested energy of the proposed circuit can fully meet the power demand of most wireless sensors.
Modeling and Principle
The proposed design is based on a cantilever piezoelectric-energy generator with pendulum balls as fixed electrodes, which are composed of guide wires and light metal balls. Buffer springs are set on both sides of the inertia mass as the center electrodes and the two pendulum balls serve as moving electrodes. These electrodes form two mechanical switches and are used in the SSHI-PBMS circuit, as shown in Figure 2. The buffer springs can reduce the rigid collision between the ball and the mass to improve the stability of the pendulum-ball mechanism. It is worth noting that the pendulum ball makes only contact with the buffer spring, and the stiffness of the thin guide wire in the horizontal direction can be ignored. When the pendulum ball swings, the stiffness of the pendulumball mechanism is very low, which is different from other adaptive mechanical switches.
Modeling and Principle
The proposed design is based on a cantilever piezoelectric-energy generator with pendulum balls as fixed electrodes, which are composed of guide wires and light metal balls. Buffer springs are set on both sides of the inertia mass as the center electrodes and the two pendulum balls serve as moving electrodes. These electrodes form two mechanical switches and are used in the SSHI-PBMS circuit, as shown in Figure 2. The buffer springs can reduce the rigid collision between the ball and the mass to improve the stability of the pendulum-ball mechanism. It is worth noting that the pendulum ball makes only contact with the buffer spring, and the stiffness of the thin guide wire in the horizontal direction can be ignored. When the pendulum ball swings, the stiffness of the pendulum-ball mechanism is very low, which is different from other adaptive mechanical switches. Figure 3 shows the simplified model of the generator structure: the cantilever generator and two pendulum mechanisms are represented by three typical spring-mass-damping systems. The proposed pendulum switch has a lower damping, µ 2 . Moreover, a special piezoelectric element is added in the simplified model of the beam to include the electromechanical-coupling effects. It is noted that the electric charge is mainly converted from the first mode of the beam with PZT. The charge induced by higher modes is neglected. The piezoelectric element with piezoelectric-force factor α is viewed as an equivalent cur-rent source i and an intrinsic capacitor C 0 . Therefore, the dynamic equations of the system can be written as follows: .. .. ..
in which γ is the excitation acceleration; x 1 , x 2 and x 3 are the displacements of the cantilever beam and the two pendulum balls, respectively. In the initial state x 1 = x 2 = x 3 = 0, M 1 and M 2 are the equivalent masses of the cantilever beam and the pendulum ball. K 1 and K 2 are the stiffness of the generator and the pendulum, where K 2 = M 2 gtan(arcsin(x 2 /L))/x 2 . L is the length of the cycloid; µ 1 and µ 2 are the damping coefficients; F 1 and F 2 are the interaction forces between the cantilever and the pendulum balls, respectively. Since the pendulum length L is much larger than x 2 , the x 2 can be regarded as approximately equal to the vibration amplitude of the pendulum ball A m . From the equation for stiffness K 2 , it can be seen that there are two methods to reduce K 2 : one is to increase the length of the pendulum L and the other is to reduce the mass of the pendulum ball M 2 . Consequently, from the above analysis it is not difficult to find that the value of stiffness K 2 is affected by the pendulum length L and the pendulum ball mass M 2 , which is conducive to improving the performance of synchronous switches. Since F 1 and F 2 only exist when the cantilever is in contact with the pendulum balls, the corresponding expressions can be derived: where Figure 3 shows the simplified model of the generator structure: the cantilever generator and two pendulum mechanisms are represented by three typical spring-mass-damping systems. The proposed pendulum switch has a lower damping, μ2. Moreover, a special piezoelectric element is added in the simplified model of the beam to include the electromechanical-coupling effects. It is noted that the electric charge is mainly converted from the first mode of the beam with PZT. The charge induced by higher modes is neglected. The piezoelectric element with piezoelectric-force factor α is viewed as an equivalent current source i and an intrinsic capacitor C0. Therefore, the dynamic equations of the system can be written as follows: in which γ is the excitation acceleration; x1, x2 and x3 are the displacements of the cantilever beam and the two pendulum balls, respectively. In the initial state x1 = x2 = x3 = 0, M1 and M2 are the equivalent masses of the cantilever beam and the pendulum ball. K1 and K2 are the stiffness of the generator and the pendulum, where K2 = M2gtan(arcsin(x2/L))/x2. L is the length of the cycloid; μ1 and μ2 are the damping coefficients; F1 and F2 are the interac- The working principle of the adaptive mechanical switch is shown in Figure 4. As shown in Figure 4a, in the initial state, x 1 = x 2 = x 3 = 0, with the cantilever moving towards the positive direction, the peak value x 1 = A m is reached, the displacement of the pendulum ball in the positive direction x 2 = A m , as shown in Figure 4b. Then, the cantilever moves to the negative direction until the negative peak value x 1 = −A m , and the pendulum ball displacement x 3 = −A m in the negative direction, as shown in Figure 4c. In other words, the cycloid stiffness in the horizontal direction is low, so that the natural frequency of the auxiliary vibrator is kept at a low level to adapt to the frequency of the surrounding environment. In this way, the displacement of the pendulum ball in the positive direction is basically unchanged x 2 ≈ A m . When the cantilever moves to the positive direction again, it only needs to lose a small part of kinetic energy to make the pendulum ball in the positive direction reach the positive peak displacement again, as shown in Figure 4d; the motion of the pendulum ball in the negative direction is similar to that of the pendulum ball in the positive direction.
other moments H(x) = 0 and S2 is open.
The working principle of the adaptive mechanical switch is shown in Figure 4. As shown in Figure 4a, in the initial state, x1 = x2 = x3 = 0, with the cantilever moving towards the positive direction, the peak value x1 = Am is reached, the displacement of the pendulum ball in the positive direction x2 = Am, as shown in Figure 4b. Then, the cantilever moves to the negative direction until the negative peak value x1 = −Am, and the pendulum ball displacement x3 = −Am in the negative direction, as shown in Figure 4c. In other words, the cycloid stiffness in the horizontal direction is low, so that the natural frequency of the auxiliary vibrator is kept at a low level to adapt to the frequency of the surrounding environment. In this way, the displacement of the pendulum ball in the positive direction is basically unchanged x2 ≈ Am. When the cantilever moves to the positive direction again, it only needs to lose a small part of kinetic energy to make the pendulum ball in the positive direction reach the positive peak displacement again, as shown in Figure 4d; the motion of the pendulum ball in the negative direction is similar to that of the pendulum ball in the positive direction. When the system is stable, the cantilever and the pendulum ball repeat the above processes ( Figure 4c,d). The moving electrode of the adaptive mechanical switch contacts the central electrode alternately near the displacement extremum of the cantilever, and the switches S1 and S2 close and open respectively near the displacement extremum of the cantilever. When the displacement of the beam increases or decreases, the ball is able to rely on the kinetic energy or gravitational potential energy of the beam to achieve new balance and stay near the peak displacement of the beam; thus, the adaptive mechanical switch can automatically track the displacement amplitude of the beam and control the synchronous switch to close near the displacement extremum without consuming additional electric energy. There is no doubt that in the harvesting process, there would be a small amount of energy loss due to the collision between the auxiliary oscillator and the cantilever beam, but the pendulum-ball switch designed in this paper has less energy loss because of its light weight. When the system is stable, the cantilever and the pendulum ball repeat the above processes ( Figure 4c,d). The moving electrode of the adaptive mechanical switch contacts the central electrode alternately near the displacement extremum of the cantilever, and the switches S 1 and S 2 close and open respectively near the displacement extremum of the cantilever. When the displacement of the beam increases or decreases, the ball is able to rely on the kinetic energy or gravitational potential energy of the beam to achieve new balance and stay near the peak displacement of the beam; thus, the adaptive mechanical switch can automatically track the displacement amplitude of the beam and control the synchronous switch to close near the displacement extremum without consuming additional electric energy. There is no doubt that in the harvesting process, there would be a small amount of energy loss due to the collision between the auxiliary oscillator and the cantilever beam, but the pendulum-ball switch designed in this paper has less energy loss because of its light weight.
Experiments and Results
According to the above principle, a piezoelectric-energy generator is designed and manufactured, which is composed of one stainless-steel beam with the size of (100 × 20 × 1) mm and two piezoelectric patches with sizes of (30 × 20 × 0.4) mm. The two piezoelectric patches, with capacitances of 2.7 × 10 −8 F, are respectively pasted on the two surfaces near the fixed end of the cantilever beam, and the piezoelectric patches are connected in parallel, as shown in Figure 5. A mass block is fixed near the free end of the cantilever beam. To avoid the rigid collision between the mass block and the moving electrodes, the foam is pasted on both sides of the mass block as support, and the buffer spring is formed by covering a layer of arc-conductive tape on the foam block. The stiffness of the buffer spring 200 N/m is much lower than that of the cantilever beam 1032 N/m. The combination of mass block, foam block and buffer spring is used as the central electrode. Two pendulumball mechanisms are vertically installed on the bracket, and the pendulum ball is adjusted to be located on both sides of the central electrode of the cantilever. Considering the low rigidity and conductivity of the moving electrode, the cycloid is made of conductive tape, and the pendulum ball is made of a stainless-steel ball. In order to connect the pendulum ball with the cycloid, a layer of conductive tape is covered on the pendulum ball. manufactured, which is composed of one stainless-steel beam with the size of (100 × 20 × 1) mm and two piezoelectric patches with sizes of (30 × 20 × 0.4) mm. The two piezoelectric patches, with capacitances of 2.7 × 10 −8 F, are respectively pasted on the two surfaces near the fixed end of the cantilever beam, and the piezoelectric patches are connected in parallel, as shown in Figure 5. A mass block is fixed near the free end of the cantilever beam. To avoid the rigid collision between the mass block and the moving electrodes, the foam is pasted on both sides of the mass block as support, and the buffer spring is formed by covering a layer of arc-conductive tape on the foam block. The stiffness of the buffer spring 200 N/m is much lower than that of the cantilever beam 1032 N/m. The combination of mass block, foam block and buffer spring is used as the central electrode. Two pendulumball mechanisms are vertically installed on the bracket, and the pendulum ball is adjusted to be located on both sides of the central electrode of the cantilever. Considering the low rigidity and conductivity of the moving electrode, the cycloid is made of conductive tape, and the pendulum ball is made of a stainless-steel ball. In order to connect the pendulum ball with the cycloid, a layer of conductive tape is covered on the pendulum ball. This experimental set-up is installed on the shaker (The Modal Shop©, 2075e-ht) which is driven by a signal generator (RIGOL©, DS1022Z) to generate the excitation signal; the laser sensor (SUNX©, hl-c203be) obtains the displacement of the cantilever; the piezoelectric voltage and cantilever displacement are displayed and saved through the oscilloscope (Tektronix©, MDO3024). The acceleration sensor (PCB©, M352C68) is mounted on the shaker to obtain the practical excitation acceleration. Based on the standard diode-rectifier circuit, a parallel SSHI circuit is composed of an inductor and a mechanical switch. The parameters in the system are shown in Table 1. The natural frequency of the cantilever beam measured by manual sweeping is 49.4 Hz, which is close to the theoretical value of 50 Hz. This experimental set-up is installed on the shaker (The Modal Shop©, 2075e-ht) which is driven by a signal generator (RIGOL©, DS1022Z) to generate the excitation signal; the laser sensor (SUNX©, hl-c203be) obtains the displacement of the cantilever; the piezoelectric voltage and cantilever displacement are displayed and saved through the oscilloscope (Tektronix©, MDO3024). The acceleration sensor (PCB©, M352C68) is mounted on the shaker to obtain the practical excitation acceleration. Based on the standard diode-rectifier circuit, a parallel SSHI circuit is composed of an inductor and a mechanical switch. The parameters in the system are shown in Table 1. The natural frequency of the cantilever beam measured by manual sweeping is 49.4 Hz, which is close to the theoretical value of 50 Hz. To verify the performance of the designed structure, the first step is to maintain the excitation frequency of 50 Hz and obtain the waveforms of the piezoelectric-patch voltages and cantilever displacement under three displacement amplitudes, as shown in Figure 6. It can be seen that the adaptive mechanical switch can work normally at low amplitude and high amplitude. In the figure, dotted lines represent the reverse position of the voltage waveform of the piezoelectric patches, that is, the closed position of the mechanical switch.
In addition, the closed position is close to the displacement peak of the cantilever beam. At the same time, through the derived model, the displacement-simulation waveforms of the cantilever beam and the pendulum ball are obtained, and the closed position of the mechanical switch is marked with the circle. Obviously, when x 1 > x 2 , S 1 is closed and disconnected after the peak displacement, and when x 1 < x 3 , S 2 is closed. In Figure 6, it can be observed that the results of the experiment and simulation match well, and the switches S 1 and S 2 can automatically open and close near the displacement peak of the cantilever beam. Careful observation shows that the phase advance angle of the mechanical switch increases slightly with the increase in the amplitude of the cantilever beam; due to the increase in the pendulum amplitude of the ball, the stiffness K 2 increases and the restoring force of the pendulum ball increases. On account of the certain mass and rigidity of the pendulum mechanism, the closing times of the mechanical switches S 1 and S 2 are always earlier than the peak displacements of the cantilever beam, which is inevitable. It is not difficult to see that the curve part in the voltage matches with the sine displacement in [29]. However, in this paper in Figure 6, the curve part of the voltage has the opposite shape to the displacement. In fact, the positive and negative of the voltage value is not directly related to the positive and negative of the displacement value. The positive and negative of the displacement value is determined by the installation position of the laser sensor and the cantilever beam. However, the positive and negative of the piezoelectric voltage value is related to the polarization direction of the piezoelectric plates and the wiring sequence of two interfaces of the interface circuit. In addition, it is verified that the amplitude of the cantilever beam is Am = 1 mm under different excitation frequencies. As shown in Figure 7, there are three waveforms: (a) 48 Hz, (b) 50 Hz, (c) 52 Hz. The results show that the adaptive mechanical switch can work stably at different excitation frequencies, and the experimental and simulation results In addition, it is verified that the amplitude of the cantilever beam is A m = 1 mm under different excitation frequencies. As shown in Figure 7, there are three waveforms: (a) 48 Hz, (b) 50 Hz, (c) 52 Hz. The results show that the adaptive mechanical switch can work stably at different excitation frequencies, and the experimental and simulation results match well. However, it can be found that with the increase in the excitation frequency, the phase advance angle slightly decreases. This is because the higher the excitation frequency, the less time it takes for the switch to close twice continuously. Finally, the smaller the distance of the pendulum-ball restoration, the closer the closed position of the switch is to the displacement extreme of the cantilever beam. To further illustrate the performance advantages of the circuit with the adaptive mechanical switch, the following experiments are carried out, keeping the amplitude of the cantilever beam as 1 mm, selecting the excitation frequency as 45 Hz, 48 Hz, 50 Hz, 52 Hz and 55 Hz, respectively, and the load-resistance value changes between 20 kΩ and 2 MΩ to measure the load power. For comparison, the standard energy-extraction circuit is tested under the same conditions. Figure 8 shows that the load resistance at which maximum power is obtained in the SSHI-PBMS circuit is higher than that of the standard circuit, and the power of the proposed circuit is higher than that of the standard circuit under the optimal resistance. In Figure 8a, when the excitation frequency changes from 45 Hz to 55 Hz, the optimal load of the SSHI-PBMS circuit decreases, while the corresponding maximum load power increases from 2.38 mW to 3.34 mW. In Figure 8b, the optimal load of the standard circuit also decreases with the increase in the excitation frequency, and the maximum load power increases from 0.77 mW to 0.92 mW. Compared with the standard To further illustrate the performance advantages of the circuit with the adaptive mechanical switch, the following experiments are carried out, keeping the amplitude of the cantilever beam as 1 mm, selecting the excitation frequency as 45 Hz, 48 Hz, 50 Hz, 52 Hz and 55 Hz, respectively, and the load-resistance value changes between 20 kΩ and 2 MΩ to measure the load power. For comparison, the standard energy-extraction circuit is tested under the same conditions. Figure 8 shows that the load resistance at which maximum power is obtained in the SSHI-PBMS circuit is higher than that of the standard circuit, and the power of the proposed circuit is higher than that of the standard circuit under the optimal resistance. In Figure 8a, when the excitation frequency changes from 45 Hz to 55 Hz, the optimal load of the SSHI-PBMS circuit decreases, while the corresponding maximum load power increases from 2.38 mW to 3.34 mW. In Figure 8b, the optimal load of the standard circuit also decreases with the increase in the excitation frequency, and the maximum load power increases from 0.77 mW to 0.92 mW. Compared with the standard circuit, the load power of the SSHI-PBMS circuit is always higher, which also shows that the proposed self-adaptive mechanical switch can work normally in different cantilever-displacement amplitudes. Similarly, the excitation frequency is kept at 50 Hz and the amplitudes of the cantilever beam are 0.5 mm, 0.75 mm, 1 mm, 1.25 mm and 1.5 mm, respectively; the load powers of the two circuits are measured, as shown in Figure 9. Obviously, the load power of the SSHI-PBMS circuit is higher than that of the standard circuit under all conditions, and their power ratio is always more than 240%. When the cantilever-beam amplitude is 0.5 mm, the optimal power of the SSHI-PBMS circuit is 0.79 mW and the optimal power of the standard circuit is 0.33 mW, while the cantilever beam amplitude is 1.5 mm, the optimal power of the SSHI-PBMS circuit is 6.76 mW and the optimal power of the standard circuit is 1.63 mw, and the power improvement is significantly increased. More importantly, as can be seen from Figures 8 and 9, the SSHI-PBMS circuit works well over a wide range of frequencies and amplitudes, with a significant increase in load power compared to the standard circuit. For comparison, the maximum power of the two circuits is shown separately. The load power increases with the increase in excitation frequency; as shown in Figure 10a, the SSHI-PBMS circuit is always higher than the standard circuit, and the power of the SSHI-PBMS circuit is 3.6 times that of the standard circuit under the excitation frequency Similarly, the excitation frequency is kept at 50 Hz and the amplitudes of the cantilever beam are 0.5 mm, 0.75 mm, 1 mm, 1.25 mm and 1.5 mm, respectively; the load powers of the two circuits are measured, as shown in Figure 9. Obviously, the load power of the SSHI-PBMS circuit is higher than that of the standard circuit under all conditions, and their power ratio is always more than 240%. When the cantilever-beam amplitude is 0.5 mm, the optimal power of the SSHI-PBMS circuit is 0.79 mW and the optimal power of the standard circuit is 0.33 mW, while the cantilever beam amplitude is 1.5 mm, the optimal power of the SSHI-PBMS circuit is 6.76 mW and the optimal power of the standard circuit is 1.63 mw, and the power improvement is significantly increased. More importantly, as can be seen from Figures 8 and 9, the SSHI-PBMS circuit works well over a wide range of frequencies and amplitudes, with a significant increase in load power compared to the standard circuit. Similarly, the excitation frequency is kept at 50 Hz and the amplitudes of the cantilever beam are 0.5 mm, 0.75 mm, 1 mm, 1.25 mm and 1.5 mm, respectively; the load powers of the two circuits are measured, as shown in Figure 9. Obviously, the load power of the SSHI-PBMS circuit is higher than that of the standard circuit under all conditions, and their power ratio is always more than 240%. When the cantilever-beam amplitude is 0.5 mm, the optimal power of the SSHI-PBMS circuit is 0.79 mW and the optimal power of the standard circuit is 0.33 mW, while the cantilever beam amplitude is 1.5 mm, the optimal power of the SSHI-PBMS circuit is 6.76 mW and the optimal power of the standard circuit is 1.63 mw, and the power improvement is significantly increased. More importantly, as can be seen from Figures 8 and 9, the SSHI-PBMS circuit works well over a wide range of frequencies and amplitudes, with a significant increase in load power compared to the standard circuit. For comparison, the maximum power of the two circuits is shown separately. The load power increases with the increase in excitation frequency; as shown in Figure 10a, the SSHI-PBMS circuit is always higher than the standard circuit, and the power of the SSHI-PBMS circuit is 3.6 times that of the standard circuit under the excitation frequency of 55 Hz. Figure 10b shows the relationship between the optimal power of the two circuits For comparison, the maximum power of the two circuits is shown separately. The load power increases with the increase in excitation frequency; as shown in Figure 10a, the SSHI-PBMS circuit is always higher than the standard circuit, and the power of the SSHI-PBMS circuit is 3.6 times that of the standard circuit under the excitation frequency of 55 Hz. Figure 10b shows the relationship between the optimal power of the two circuits and the cantilever amplitude. Obviously, the power increases rapidly with the increase in the cantilever amplitude, and the load power of the SSHI-PBMS circuit is always better than that of the standard circuit. The higher the amplitude, the more obvious the power increase. In addition, the power of the proposed circuit is 4.2 times that of the standard circuit under the displacement amplitude of 1.5 mm. At the same time, the optimal powers of other adaptive mechanical-switch circuits are also much higher than those of the standard circuit, but its power is slightly lower than that of the proposed circuit under different conditions, which further indicates that the energy-extraction efficiency of the proposed adaptive mechanical switch is higher. circuit under the displacement amplitude of 1.5 mm. At the same time, the optimal powers of other adaptive mechanical-switch circuits are also much higher than those of the standard circuit, but its power is slightly lower than that of the proposed circuit under different conditions, which further indicates that the energy-extraction efficiency of the proposed adaptive mechanical switch is higher. As mentioned earlier, it is not difficult to find that the length of the cycloid can affect the stiffness K2. Therefore, the following experiments are carried out to analyze the influence of pendulum length on harvested power: keeping the excitation frequency at 50 Hz, the acceleration at 2 m s −2 and the load resistance at 800 KΩ. Selecting different cycloid lengths to measure the power of the load resistance, as shown in Figure 11a, it can be found that with the increase in cycloid length, the load power corresponding to the two circuits increases slowly, which is because after the cycloid becomes longer the kineticenergy loss of the system decreases, so the load power of the circuit increases. Thus, relying on the adjustment of the pendulum length of the mechanical switch, a larger power output can be obtained without the adjustment of more complex structural parameters, which undoubtedly provides better convenience for the application of the energy harvester in more practical environments. It should be noted that it is difficult to ensure that the installation position of the cycloid is consistent all the time during each measurement, which leads to some measurement errors. In the next chapter, the influence of cycloid length on the system will be further discussed through the model.
Meanwhile, the case of constant excitation acceleration is analyzed. As shown in Figure 11b, the excitation-frequency acceleration is 0.2 g, and the excitation frequency continuously changes from 45 Hz to 55 Hz. Obviously, the displacement for 45 Hz or 55 Hz is much lower than 50 Hz in Figure 11b, while the power output is similar, at 45 Hz or 55 Hz and 50 Hz in Figure 10a. In Figure 10a, the optimal resistance value under 50 Hz excitation is selected, and the acceleration is adjusted to keep the amplitude of the cantilever beam at 1 mm under all excitation frequencies. When the displacement amplitude remains constant, more energy is generated at the same time under the excitation of higher frequency, so the power output in Figure 10a increases slowly from 45 Hz to 50 Hz. Meanwhile, the acceleration is constant at 0.2 g in Figure 11b, so there is a large displacement only near the resonance frequency. The displacement amplitude of the cantilever decreases slightly when the mobile electrode is introduced disconnected to the circuit, which As mentioned earlier, it is not difficult to find that the length of the cycloid can affect the stiffness K 2 . Therefore, the following experiments are carried out to analyze the influence of pendulum length on harvested power: keeping the excitation frequency at 50 Hz, the acceleration at 2 m s −2 and the load resistance at 800 KΩ. Selecting different cycloid lengths to measure the power of the load resistance, as shown in Figure 11a, it can be found that with the increase in cycloid length, the load power corresponding to the two circuits increases slowly, which is because after the cycloid becomes longer the kinetic-energy loss of the system decreases, so the load power of the circuit increases. Thus, relying on the adjustment of the pendulum length of the mechanical switch, a larger power output can be obtained without the adjustment of more complex structural parameters, which undoubtedly provides better convenience for the application of the energy harvester in more practical environments. It should be noted that it is difficult to ensure that the installation position of the cycloid is consistent all the time during each measurement, which leads to some measurement errors. In the next chapter, the influence of cycloid length on the system will be further discussed through the model. is slightly lower than that of the unconnected circuit, but significantly higher than that of the self-adaptive mechanical-switch circuit, which also shows that the energy extraction efficiency of the standard circuit is not high, while the designed switch can effectively improve the extraction efficiency. From the anterior analysis, the designed adaptive mechanical-switch structure has a small equivalent stiffness and small damping, so the pendulum ball can be kept near the peak displacement of the cantilever beam with little energy. Through the experimental study of constant cantilever amplitude and excitation frequency, the adaptive performance of the self-adaptive mechanical switch is verified, which proves that the structure can work efficiently in a wide range of excitation frequencies and cantilever amplitudes. At the same time, in comparison of the same research on the standard circuit, it is proved that the load power of the proposed circuit is significantly higher than that of the standard circuit, and the higher the excitation frequency and acceleration, the more obvious the advantages of the SSHI-PBMS circuit. Moreover, compared with the previous adaptive mechanical switch [29] whose performance was greatly affected by the stiffness and damping of the auxiliary oscillator and buffer structure, the proposed mechanical-switch structure is simpler and easy to adjust to improve the harvesting performance by changing the pendulum length.
Further Discussions
The advantages of the proposed adaptive mechanical switch have been verified by experiments. In order to further improve the performance of the pendulum-ball mechanism, we conduct an in-depth study on the system parameters. In fact, SSHI technology can improve the performance of the circuit mainly depending on the synchronous switch in the circuit, and the closing time of the synchronous switch directly affects the efficiency of the circuit. Therefore, this paper uses the phase advance angle of the closing time of the mechanical switch to evaluate the performance of the proposed mechanical switch.
Using the simulation model, the main system parameters of the pendulum structure are studied and analyzed. Five excitation frequencies (40 Hz, 45 Hz, 50 Hz, 55 Hz and 60 Hz) are selected for analysis, as shown in Figure 12. Firstly, the length of the cycloid is analyzed; as shown in Figure 12a, with the decrease in cycloid length L, the phase advance angle decreases rapidly and then slowly. The reason is because when the amplitude is constant, the longer cycloid length L leads to the smaller equivalent stiffness k2, and the restoration of the pendulum ball is slower, thus the position of the second closing of the synchronous switch is closer to the displacement peak, resulting in the decrease of the phase advance angle. The smaller the phase advance angle, the lower the energy loss when the cantilever beam contacts the pendulum ball, which is conducive to improving Meanwhile, the case of constant excitation acceleration is analyzed. As shown in Figure 11b, the excitation-frequency acceleration is 0.2 g, and the excitation frequency continuously changes from 45 Hz to 55 Hz. Obviously, the displacement for 45 Hz or 55 Hz is much lower than 50 Hz in Figure 11b, while the power output is similar, at 45 Hz or 55 Hz and 50 Hz in Figure 10a. In Figure 10a, the optimal resistance value under 50 Hz excitation is selected, and the acceleration is adjusted to keep the amplitude of the cantilever beam at 1 mm under all excitation frequencies. When the displacement amplitude remains constant, more energy is generated at the same time under the excitation of higher frequency, so the power output in Figure 10a increases slowly from 45 Hz to 50 Hz. Meanwhile, the acceleration is constant at 0.2 g in Figure 11b, so there is a large displacement only near the resonance frequency. The displacement amplitude of the cantilever decreases slightly when the mobile electrode is introduced disconnected to the circuit, which shows that the designed self-adaptive mechanical switch has little impact on the system. However, when the designed switch is connected to the circuit, the displacement amplitude decreases significantly, which indicates that the system damping increases, and more kinetic energy is converted into electrical energy. In order to ensure the consistency, keeping the mechanical switch connected to the standard circuit, the displacement amplitude is slightly lower than that of the unconnected circuit, but significantly higher than that of the self-adaptive mechanical-switch circuit, which also shows that the energy extraction efficiency of the standard circuit is not high, while the designed switch can effectively improve the extraction efficiency. From the anterior analysis, the designed adaptive mechanical-switch structure has a small equivalent stiffness and small damping, so the pendulum ball can be kept near the peak displacement of the cantilever beam with little energy.
Through the experimental study of constant cantilever amplitude and excitation frequency, the adaptive performance of the self-adaptive mechanical switch is verified, which proves that the structure can work efficiently in a wide range of excitation frequencies and cantilever amplitudes. At the same time, in comparison of the same research on the standard circuit, it is proved that the load power of the proposed circuit is significantly higher than that of the standard circuit, and the higher the excitation frequency and acceleration, the more obvious the advantages of the SSHI-PBMS circuit. Moreover, compared with the previous adaptive mechanical switch [29] whose performance was greatly affected by the stiffness and damping of the auxiliary oscillator and buffer structure, the proposed mechanical-switch structure is simpler and easy to adjust to improve the harvesting performance by changing the pendulum length.
Further Discussions
The advantages of the proposed adaptive mechanical switch have been verified by experiments. In order to further improve the performance of the pendulum-ball mechanism, we conduct an in-depth study on the system parameters. In fact, SSHI technology can improve the performance of the circuit mainly depending on the synchronous switch in the circuit, and the closing time of the synchronous switch directly affects the efficiency of the circuit. Therefore, this paper uses the phase advance angle of the closing time of the mechanical switch to evaluate the performance of the proposed mechanical switch.
Using the simulation model, the main system parameters of the pendulum structure are studied and analyzed. Five excitation frequencies (40 Hz, 45 Hz, 50 Hz, 55 Hz and 60 Hz) are selected for analysis, as shown in Figure 12. Firstly, the length of the cycloid is analyzed; as shown in Figure 12a, with the decrease in cycloid length L, the phase advance angle decreases rapidly and then slowly. The reason is because when the amplitude is constant, the longer cycloid length L leads to the smaller equivalent stiffness k 2 , and the restoration of the pendulum ball is slower, thus the position of the second closing of the synchronous switch is closer to the displacement peak, resulting in the decrease of the phase advance angle. The smaller the phase advance angle, the lower the energy loss when the cantilever beam contacts the pendulum ball, which is conducive to improving the load power. Figure 12b shows the effect of the pendulum-ball mass on the phase advance angle. Obviously, the pendulum-ball mass increases, and the phase advance angle almost increases linearly. This is because the pendulum-ball mass directly affects the equivalent stiffness K 2 ; the larger the pendulum-ball mass, the greater the equivalent stiffness K 2 and the faster the pendulum ball recovers. Therefore, choosing a smaller pendulum-ball mass M 2 can make the mechanical switch close in time to realize charge retention, unlike the previous mechanical switch whose mass adjustment has little influence on the harvesting performance [29]. In this way, the power density of the energy harvester can be significantly improved, and the energy loss caused by the pendulum-ball switch with smaller mass can be greatly reduced. Figure 12a,b shows that the higher the excitation frequency, the smaller the corresponding phase advance angle, which is caused by the decrease in the interval time between two consecutive closures of the switch. Meanwhile, from the comparison between Figure 12a,b, the gradual curve in Figure 12b implies that the pendulum-ball mass M 2 has a smaller effect on the phase advance angle than the pendulum length. Consequently, adjusting the pendulum length L to change the cycloid stiffness K 2 is also a good choice to improve the performance of the pendulum-ball switch.
Micromachines 2022, 13, x FOR PEER REVIEW 13 of 16 the load power. Figure 12b shows the effect of the pendulum-ball mass on the phase advance angle. Obviously, the pendulum-ball mass increases, and the phase advance angle almost increases linearly. This is because the pendulum-ball mass directly affects the equivalent stiffness K2; the larger the pendulum-ball mass, the greater the equivalent stiffness K2 and the faster the pendulum ball recovers. Therefore, choosing a smaller pendulum-ball mass M2 can make the mechanical switch close in time to realize charge retention, unlike the previous mechanical switch whose mass adjustment has little influence on the harvesting performance [29]. In this way, the power density of the energy harvester can be significantly improved, and the energy loss caused by the pendulum-ball switch with smaller mass can be greatly reduced. Figure 12a,b shows that the higher the excitation frequency, the smaller the corresponding phase advance angle, which is caused by the decrease in the interval time between two consecutive closures of the switch. Meanwhile, from the comparison between Figure 12a,b, the gradual curve in Figure 12b implies that the pendulum-ball mass M2 has a smaller effect on the phase advance angle than the pendulum length. Consequently, adjusting the pendulum length L to change the cycloid stiffness K2 is also a good choice to improve the performance of the pendulum-ball switch. For further quantitative analysis, according to the experimental results under different frequencies and constant amplitudes, the power comparison between the SSHI-PBMS circuit and the standard circuit is summarized in Table 2. The results at 40 Hz, 50 Hz and 55 Hz are obtained with the constant amplitude 1 mm, while the results at 0.5 mm, 1 mm and 1.5 mm are obtained with the frequency 50 Hz. It can be found that for both the standard circuit and the SSHI-PBMS circuit, the power increases with the increase in frequency or displacement amplitude, with other conditions remaining unchanged. However, in general, the power ratio of the SSHI-PBMS circuit is between 200% and 500% compared with the standard circuit in all cases, which implies the advantage of the proposed mechanical switch in energy harvesting. For further quantitative analysis, according to the experimental results under different frequencies and constant amplitudes, the power comparison between the SSHI-PBMS circuit and the standard circuit is summarized in Table 2. The results at 40 Hz, 50 Hz and 55 Hz are obtained with the constant amplitude 1 mm, while the results at 0.5 mm, 1 mm and 1.5 mm are obtained with the frequency 50 Hz. It can be found that for both the standard circuit and the SSHI-PBMS circuit, the power increases with the increase in frequency or displacement amplitude, with other conditions remaining unchanged.
However, in general, the power ratio of the SSHI-PBMS circuit is between 200% and 500% compared with the standard circuit in all cases, which implies the advantage of the proposed mechanical switch in energy harvesting. From the foresaid study related to the influence of the load connected in the electrical circuit, the proposed generator with SSHI-PBMS shows huge potentiality for providing sustainable and clean power sources for sensors. Figure 13 presents a possible application scheme with the proposed SSHI-PBMS generator. By putting the piezoelectric generator with the SSHI-PBMS circuit under the vibration environment, the vibrations can be converted into electricity by the generator. The harvested energy is then supplied to a wireless node through a power-management unit. This node integrates the desired sensors (vibration, temperature etc.) for acquiring the status of the device required to be monitored and sends the information to the coordinator through the wireless link. Therefore, the desired status can be monitored in real time. From the foresaid study related to the influence of the load connected in the electrical circuit, the proposed generator with SSHI-PBMS shows huge potentiality for providing sustainable and clean power sources for sensors. Figure 13 presents a possible application scheme with the proposed SSHI-PBMS generator. By putting the piezoelectric generator with the SSHI-PBMS circuit under the vibration environment, the vibrations can be converted into electricity by the generator. The harvested energy is then supplied to a wireless node through a power-management unit. This node integrates the desired sensors (vibration, temperature etc.) for acquiring the status of the device required to be monitored and sends the information to the coordinator through the wireless link. Therefore, the desired status can be monitored in real time.
Conclusions
In this article, a novel adaptive mechanical-switch circuit adopting a simple harmonic-motion structure as a moving electrode is proposed. The mechanical switch can automatically adapt to the displacement amplitude of the cantilever beam, and it can close and open near the displacement amplitude of the cantilever beam. Due to the equivalent stiffness of the pendulum mechanism being lower than other adaptive mechanical switches, the closed position of the mechanical switch is closer to the peak displacement, and the energy-extraction efficiency is higher. The performance of the adaptive mechanical switch has been verified by experiments, and it can work normally in a wide range of cantilever amplitudes and excitation frequencies. In the experiment, the maximum power of the SSHI-PBMS circuit was 6.76 mW at the cantilever amplitude of 1.5 mm, while the maximum power of the standard circuit was 1.63 mW, and the maximum power of SSHI was 4.2 times that of standard circuit.
For further optimization, the main parameters of the pendulum mechanism have been studied. It is found that the mass of the pendulum ball determines the equivalent stiffness, and the equivalent stiffness directly affects the phase advance angle of the mechanical switch; thus, choosing a lower pendulum-ball mass is conducive to improving the performance of the mechanical switch, which is not only helpful to reduce relevant
Conclusions
In this article, a novel adaptive mechanical-switch circuit adopting a simple harmonicmotion structure as a moving electrode is proposed. The mechanical switch can automatically adapt to the displacement amplitude of the cantilever beam, and it can close and open near the displacement amplitude of the cantilever beam. Due to the equivalent stiffness of the pendulum mechanism being lower than other adaptive mechanical switches, the closed position of the mechanical switch is closer to the peak displacement, and the energy-extraction efficiency is higher. The performance of the adaptive mechanical switch has been verified by experiments, and it can work normally in a wide range of cantilever amplitudes and excitation frequencies. In the experiment, the maximum power of the SSHI-PBMS circuit was 6.76 mW at the cantilever amplitude of 1.5 mm, while the maximum power of the standard circuit was 1.63 mW, and the maximum power of SSHI was 4.2 times that of standard circuit.
For further optimization, the main parameters of the pendulum mechanism have been studied. It is found that the mass of the pendulum ball determines the equivalent stiffness, and the equivalent stiffness directly affects the phase advance angle of the mechanical switch; thus, choosing a lower pendulum-ball mass is conducive to improving the performance of the mechanical switch, which is not only helpful to reduce relevant energy loss, but also contributes to the portability and integration of energy harvesters in specific environmental applications. Similarly, under the same conditions, increasing the length of the cycloid can also reduce the equivalent stiffness of the pendulum mechanism. Therefore, a better adaptive mechanical switch with better harvesting performance can be designed by selecting appropriate parameters. In short, two key factors in the design of self-adaptive pendulum-ball switches are that the pendulum length L of the auxiliary oscillator should be longer, but too long a cycloid is disadvantageous for the miniaturization design of the energy harvester; whereas the pendulum-ball mass M 2 should be as small as possible.
The performance of the adaptive mechanical switch proposed in this paper has obvious advantages over the previous self-adaptive mechanical switches. Thanks to the unique lightweight pendulum-ball structure, the energy density of the generator is further improved with less energy loss. Although part of the excitation conditions is analyzed in this article, the proposed mechanical switch can adapt to more excitation conditions and expand the application by appropriate designs. | 12,870.2 | 2022-03-28T00:00:00.000 | [
"Engineering",
"Physics"
] |
Effect of beam oscillation and focusing on the electron beam welded 1100M high strength structural steel joint
The development of ultra-high-strength steels (UHSS) is revolutionizing its need in the diverse field of application, and the main credit going to the new technological advancement in the manufacturing of steels using special heat treatment like the thermomechanical rolled process to produce UHSS with up to 1300 MPa tensile strength in the thicker plate. The steel provides higher strength, toughness, and extensive reduced weight, significant in structural components and higher load lifting vehicles (e.g., mobile cranes, trailers, concrete pump trucks, etc.) with lower fuel consumption. However, welding of UHSS is also a challenge due to their higher crack susceptibility and hardness reduction in the heat-affected zone (HAZ). The study’s main objective is to analyse the effect of beam focus on the weld geometry and the different beam oscillation on the weld microstructure and hardness behaviour of the 1100M EB-welded joint. The S1100M steel samples of the thickness of 15 mm were butt-welded by autogenous electron beam welding (EBW). The study finds that UHSS can be satisfactorily welded with EBW, improving the weld geometry with beam focus. The observed results show that beam oscillation’s microstructural and hardness behaviour was attributed to developing a more uniform microstructure.
Introduction
Because of growing environmental concern and sustainable development, the demand for lightweight materials has increased over the last decade, and steel manufacturers have shifted their focus to higher strength steels (HSS) and lighter weights with higher safety. Various kinds of high-strength structural steels (HSSS) have been developed through different technological and heat treatment processes [1]. In the case of HSSS, the available maximum strength steel with thicker plate is up to 1300 MPa. However, as tensile strengths increase, so does the complexity of the joining process, which leads welding experts and manufacturers to produce more efficient, productive, adaptable, smart, and novel welding technologies [2]. Therefore, it is very important to understand the weldability of these steels with different new innovative welding processes to understand the microstructural change and mechanical behaviour of the welded joints and heat-affected zone (HAZ). The HSSS with a higher tensile strength hardens more in the fusion zone (FZ) and especially in the coarse-grained heat-affected zone (CGHAZ).
The beam welding process like electron beam welding (EBW) technology finds more efficient methods in welding thicker high strength steel plates in a single pass rather than conventional arc welding processes which leads in reduction in welding time, quality, strength etc. [3,4]. Furthermore, it is essential to comprehend the beam welding process and its effect on the welded joint and HAZ in terms of its various characteristics (accelerating voltages Ua; beam current, Ib, and so on), as well as dynamic effects on the beam (beam oscillations, beam focus position etc.) etc. [5]. We often use static beam in the EBW process with optimal parameters for welding the different materials. However, the use of beam with various dynamic effects in the case HSSS changes the geometry of the weld and HAZ, proves many benefits in terms of microstructural and mechanical properties of the welded joints [6]. The use of dynamic effects aids in improving mechanical properties, obtaining uniform structures, particularly in the case of dissimilar materials welded joints, and avoiding defects such as porosity, cold and hot cracks, and so on [3,7,8]. The different beam oscillation methods were like circular, ellipsoidal, parallel etc. and the different focusses like sharp focus, over focussed, under focussed [7]. Several studies have been reported before on the effect of beam oscillation on the welded joint of different materials and various alloys, however, a very little or no research has been found with the HSSS.
In this paper, the main focus is given on the comparison of the effect of different beam oscillations and beam focusses on the weld geometry, weld microstructure and hardness behaviour of the S1100M.
Material properties
The base material (BM) used in the study was S1100M, thermomechanically rolled steel with thickness of 15 mm. The plates with the dimension of 150 × 50 mm were cut and the joining faces of the plates were machined precisely by milling machine to the maximum allowable airgaps of 0.20 mm along the weld joint to be produced to secure precise fit for the welding. The mechanical and chemical properties of the investigated BM are provided in the table 1 and table 2 respectively.
Experimental set-up
The welding was performed by using the electron beam welding robotized device PZ EZ 30 STU complex, (First Welding Company, Bratislava, Slovakia) equipped with two electron beam guns with the power of 30 kW for each gun, a vacuum chamber with dimensions of 1800 × 2360 × 3150 mm and volume of 13.4 m 3 and the pumping system allowing reaching the vacuum of 5 × 10 -2 Pa within 25 minutes, and the vacuum in an electron gun was 10 -5 Pa. The vacuum pressure in the chamber was 9.8 × 10 -5 Pa. The samples were cleaned in acetone and dried before performing the welding. Then the samples were placed on a workbench in the vacuum chamber. Jigs were used to prevent deformation. The work distance (WD) was 200 mm. The EBW trials were conducted to obtain the optimal parameters with the full depth penetration for the static beam. Then the experiments were done with different focuses and oscillation while the accelerating voltage (Ua) in kV beam current (Ib) in mA and welding velocity (v) in mm/s were kept constant. The calculated welding linear heat input was 0.462 kJ/mm. After chemical etching, the specimens were examined under a microscope to determine weld profile characteristics such as weld width, HAZ, and weld depth, etc. This was done to understand the effect of various process parameters on weld bead geometry. The hardness tests were performed according to EN The hardness of the BM is 383 ±3. Figure 1 showed the macrohardness graphs for different beam oscillation, the macrohardness at the center of the FZ with beam circular oscillation (403 HV10) have nearly similar macrohardness in comparison with no oscillation (399 HV10) while with elliptical oscillation it was 410 HV10. The elliptical beam oscillation (sample 9) showed highest macrohardness in HAZ 450 HV10, no oscillation (sample 1) showed 441 HV10 while circular oscillation measured 436 HV10. The average FZ and HAZ macrohardness values are presented in the table 4. The use of circular beam oscillation in EBW of S1100M steel joints caused the nearly similar average hardness in FZ and slightly higher in HAZ compared to no oscillation.
The macroscopic examination of the welded cross section with various beam oscillations and without oscillation revealed that the width of FZ was greatest with elliptical oscillation (sample 9) and narrowest with circular oscillation (sample 6), with full depth of penetration achieved in all cases. Figure 2 shows a smoother transition from the top of the weld seam to the end of it with the circular oscillation (sample Figure 3, S-1, without beam oscillation, depicts a typical very fine pine leaves pattern at the weld's centre. The influence of the circular beam oscillation pattern in the FZ microstructure is clearly shown in figure 3, S-6. The step solidification of the weld zone induced by the circular beam oscillation pattern increased the cooling rate. The weld zone hardened in the steps as the beam oscillation repeatedly melted the weld pool. Nucleation and grain growth began separately at each stage of solidification. Furthermore, when circular oscillation was used, the width of the parting zone in the centre of the welded joint was greater than when the joint was welded without beam oscillation. In case of elliptical oscillation pattern, the width of the weld across the thickness was not uniform but bulged at one side of the parting line and seems zigzag which can be seen from figure 2, S-9. Also, figure 2 shows weld faces and reverse beads formed without undercuts in S-1, S-6, and S-9. The fast cooling caused by the EBW process resulted in the FZ having an entirely martensitic structure.
Beam focus
The beam focus plays a significant role in the welding of thicker plate since it influences the forces in the molten pool. Incorrect selection of the focal points leads to the creation of undercuts on weld faces and reverse beads, also cavities in the weld seam. The optimal focus position in EBW in terms of maximizing weld depth is controlled by varying the focusing current, If [6]. The investigation of the focus position is made without oscillations. The focusing was on the surface and the focusing current (If) means the diameter of the beam for 900 -910 mA was 2 mm and for 920 -940 mA was 3 mm. It can be observed from the figure 5, that the optimum focus position for maximum weld depth and defect- Table 5 shows the welding parameters used with various beam focus positions. EBW is a specialised welding process technology with high energy power beam applications to obtain thicker welds without using filler materials in a single pass. The lower linear heat input in the process helps with a very narrow HAZ and FZ. As a result, the welded joint typically experiences very high heat transfer. Thus, due to this, the high peak temperatures do not show much effect on the grain size of the HAZ microstructure, and the very fine HAZ microstructure in UHSS usually increases the 6 hardness in excess due to the formation of martensite structure [9]. Therefore, it is very imperative to understand the hardness behaviour of the UHSS in HAZ and FZ with different dynamic effects of the EB-welding process. The measured weld bead geometry features in mm and macrohardness with different beam focusses are shown in table 6. Macrohardness results showed that FZ average hardness of the sharp focus (410 HV10), under focus (413 HV10) and over focus (412 HV10) sample are similar while the average hardness of HAZ is increasing from sharp focus (406 HV10) to over focus (428 HV10). It is worth noting that hardness values along the depth of the weld are varying and higher in the root for both sharp focus (S-1) and over focus (S-5) while it is decreasing in the case of under focus (S-3) and lowest at the root. It shows the inhomogeneous microstructure of the welded joint due to the non-uniform properties.
From the figure 5 and table 6, we can clearly observe that the sharp focus (S-1) has full depth of penetration, width of the HAZ and FZ is less than the under focused (S-3). However, the penetration of the under focused sample, S-3 is about 70% and sample, S-4 is about 86% of the complete thickness of the welded joint. This implies that the under focused are not giving full penetration while we are increasing the focusing current (can be seen from S-3 to S-4 in table 5) in under focused condition towards sharp focus (S-1), HAZ and FZ width decreasing and penetration increasing. In case of under focus, from sample S-3 and S-4, it can be observed that the one side of the top face bead showed undercut and cavity formation due to the process instability. However, in the case of over focus (S-5), full penetration has been achieved, while the width of top FZ is higher and width of top HAZ is lower compared to the sharp focus (S-1) but overall width is lower than the both sharp focus (S-1) and under focus (S-3 and S-4). The cross section of the weld profile is observed like funnel shaped and not smooth transition from top to middle (figure 5, S-5). The microstructure of the welds with different beam focus current are shown in Figure 6. The microstructural study of the welds clearly showed that welds have non-uniform microstructure which in conformance with variation in the hardness along the width and the depth of the weld. The width of the parting zone for over focus (S-5) along the centre line of the welded joint is greater than when the joint was welded with sharp focus and under focus current.
Conclusion
In this study, we observed that effect of beam oscillation, no oscillation, and different beam focus on the weld profile, weld bead geometry especially on width of HAZ and FZ, and depth of penetration for the UHSS EB-welded joint. Also, how it affects the microstructure of the FZ, hardness in the FZ and HAZ. The use of circular beam oscillation in EBW of S1100M steel joints caused the nearly similar average hardness in FZ and slightly higher in HAZ compared to no oscillation but overall width of the FZ and HAZ are narrower compared to the no oscillation because of step solidification which enhanced the cooling rate. Variation in beam focus affects the penetration depth in the weld, sharp focus and over focus showed full penetration while under focused showed partial penetration. The overall width of the HAZ and FZ for the over focus (S-5) is lowest among others. So, it can be concluded that the focusing affects the final weld geometry to the greater extent. The weld cross section geometry of the over focus shows a characteristic funnel shaped. The average hardness along the width of FZ are nearly similar for sharp focus, under focus and over focus while the HAZ average hardness increasing from sharp focus to over focus. | 3,116.4 | 2023-02-01T00:00:00.000 | [
"Materials Science"
] |
Deuterium ordering found in new ferroelectric compound Co2(OD)3Cl
A detailed temperature-dependent Raman spectroscopic study revealed a new type of deuterium-order ferroelectrics in a geometrically frustrated magnet Co2(OD)3Cl at Tϵ = 229 K. Significant changes in the parameters of the Raman vibration modes were observed near Tϵ, suggesting a strong phonon-charge coupling. Additional asymmetric phonon bands appeared below around Tϵ, which are consistently interpreted by phonon folding processes due to a small local structural change resulting from the ordering of deuterium. The wavenumber and intensity changes of the Raman-active modes, as well as the normalized intensities of the additional bands, all follow a power-law fit Δω, ΔI, I ∝ (1 − T/TC)2β, wherein TC = 230 K ∼ Tϵ and β = 0.35(2), clearly demonstrating an ordering process below Tϵ. The critical exponent is reminiscent of a second order transition. Our study presents a rare and new type of multiferroic material with ferroelectricity arising from the deuterium ordering in geometrically frustrated magnets.
Introduction
Hydroxyl salts of the type M 2 (OH) 3 X have been known for a long time [1]. In recent years those with the magnetic ions of M = Cu 2+ , Ni 2+ , Co 2+ , Fe 2+ and Mn 2+ were shown to be geometrically frustrated magnets [2][3][4][5][6][7][8][9][10], and the substituted compounds of ZnCu 3 (OH) 6 Cl 2 [11,12], ZnCo 3 (OH) 6 Cl 2 [13] and MgCo 3 (OH) 6 Cl 2 [14] showed complete or partial spin liquid features resulting from the geometric frustration. Furthermore, measurements of the lattice parameters and dielectric constants in M 2 (OH) 3 X revealed simultaneous changes at their respective magnetic transition temperatures, demonstrating that those hydroxyl salts universally have strong magnetic-dielectric lattice couplings [15]. In special, the cobalt hydroxyl salts of Co 2 (OH) 3 Cl and Co 2 (OH) 3 Br, which possess the highest crystal symmetry of R m 3 among the hydroxyl salts, showed anomaly in dielectric constants at high temperatures of 229 and 224 K, respectively, when deuterated. Their crystal structure is similar to the spin-liquid compounds ZnCu 3 (OH) 6 Cl 2 , ZnCo 3 (OH) 6 Cl 2 and MgCo 3 (OH) 6 Cl 2 by having strong geometric frustration with alternatively stacked layers of regular kagome and triangle lattice planes. Ferroelectric transition was suspected and it was tentatively attributed to the modified hydrogen bonding due to a giant isotope effect, where geometric frustration provided a necessary condition so that a subtle change in the lattice/bonding produced dramatic change in their physical properties in Co 2 (OD) 3 Cl. However, because single crystals are not available at the present time and the usual sintering process cannot be applied to the hydroxyl salts, this subtle ferroelectricity has not been confirmed and its mechanism is unclear.
Ferroelectricity was first discovered in hydrogen-bonded materials and the ferroelectric transitions are characterized as either displacive (such as BaTiO 3 ) or order-disorder (such as NaNO 2 or KDP). In recent years, a different type termed as 'multiferroic' receives intense attention for scientific interest in their physical properties and potential for applications. Since Co 2 (OH) 3 Cl and Co 2 (OH) 3 Br showed magnetic transitions at low temperatures but with strong magnetic couplings even at 400 K [6,8,16], if the ferroelectric transition get confirmed, they can be grouped into multiferroic materials in the wide meaning of multiferroicity. Therefore, they can be viewed as unique multiferroic compounds linking geometric frustration and hydrogen-related ferroelectricity. However, since neither magnetic order nor obvious structure transition exists in this temperature range (e.g. in Co 2 (OD) 3 Cl, the ferroelectric response occurs at 229 K, which is much higher than its magnetic transition at T N = 10.5 K) [15], the origin for the observed 'ferroelectricity' in this insulating material remains mysterious and demands clarification. On this background, we carried out a detailed temperaturedependent Raman spectroscopic measurement to study the mechanism for the unusual ferroelectricity.
Experiments
Polycrystalline Co 2 (OD) 3 Cl synthesized using a hydrothermal reaction from CoCl 2 and NaOD at around 200°C, as previously reported, were pressed into a pellet and adhered to a silver plate with silver paste for Raman spectroscopic measurements. The Raman spectra were obtained with a computer-assisted Raman instrument HR800 HORIBA Jobin-Yvon using a special ×50 Olympus objective with an ultra-long working distance to improve the signal-to-noise ratio in the spectra, and a charge-coupled device (CCD) system to collect and process the scattering light. The scattering spectra were excited by a Spectra-Physics model 127 Ar + -ion laser (488.0 nm) with a resolution of 0.5 cm −1 between 4000 and 95 cm −1 . Low temperature measurements were performed using a liquid nitrogen dewar and a helium flow cryostat (Oxford Instruments) equipped with a temperature controller. The temperatures were maintained within a stability of ±0.2 K and a low laser power (5 mW) was used to minimize possible local heating.
Results and discussion
3.1. Mode assignment at room temperature The measured Raman spectra of Co 2 (OD) 3 Cl at typical temperatures are plotted in figure 1. Upon cooling to around 230 K, where the ferroelectric response occurred, significant changes in the Raman parameters as described below, as well as additional bands were observed. It is mentioned earlier that Co 2 (OD) 3 Cl has the same crystal structure with hydrogenated compound Co 2 (OH) 3 Cl, which is a highly symmetric rhombohedral structure in the space group R m 3 (No. 166) [1]. The magnetic ions Co 2+ form a three-dimensional network of linked tetrahedron with alternatively stacked layers of regular kagome and triangle lattice planes in the [001] direction. All Co 2+ ions are surrounded by six ligand ions, and surrounded by four oxygen ions at equal distances and two chlorine ions on the kagome lattice plane. On the other hand, Co 2+ ion on the triangular lattice plane is surrounded by six oxygen ions at equal distances. Another prominent structural feature is a notable distortion in the tetrahedron that the Co-Co distance on one side of the tetrahedron that has Cl − ion nearby is 3.42 Å, whereas those on the other three sides bonded with O 2− ions are 3.12 Å, indicating a 10% shorter Co-Co distance on the triangular lattice plane [15,16]. Thus, the symmetries were determined to be C s for the O site, C 3v for the Cl site, C 2h and D 3d for the Co K and Co T sites, wherein Co K and Co T denotes the Co 2+ ions on the kagome and the triangle lattice planes, respectively. Factor group analysis for this structure suggests 12 Raman active modes (5A 1g + 7E g ) and 17 infrared active modes (7A 2u + 10E u ), the Raman active modes of Co 2 (OD) 3 Cl are labeled M1 to M12. According to the previously reported assignment results of Co 2 (OH) 3 Cl/Br [17,18], and Cu 2 (OH) 3 Cl [19], the Raman spectra could be separated into four regions: (4)[Co 3 Cl] fingerprint-2 (FP 2 ) region: <200 cm −1 .
The assignment of various modes of Co 2 (OD) 3 Cl could been done as follows.
In the [OD] function group (FG) region, there are M1 (2630 cm −1 ) and M2 (2620 cm −1 ) two Raman bands with peak separations of several cm -1 . From the fact that all red-shift ratios are close to the theoretical value [μ OH /μ OD ] 1/2 = 72.8% (here, μ OH(D) is the [OH/D] reduced mass), M1 and M2 can be safely assigned to [OD] stretching modes.
The small band at 3555 cm -1 was confirmed to be due to contamination of a small amount of hydroxyl (strength ratio I OH /I OD ∼ 3%). The bands at 1600 and 1475 cm −1 (as denoted by asterisks) also exist in Co 2 (OH) 3 Cl, we could assign them to the combinations of multi-phonon modes, which are correlated with the residual H nuclei.
In [20]. The assignment of the main modes has been summarized in table 1, and the mode displacements are illustrated in figure 2.
Evolution of Raman modes with temperature
The Raman scattering profile has been fitted using a Lorentz function to compute the exact wavenumber (Raman shift), line-width (full width at half maximum, FWHM) and intensity of each peak. In widths decrease as a result of anharmonic effects and thermal changes. Here, we tried to fit the wavenumber and line-width variations using conventional formulae with lattice and phonon-phonon anharmonic interaction processes up to three phonons [21]: Here, x = hc ω 0 /2k B T and y = hc ω 0 /3k B T. As shown in figure 3, the wavenumber at high temperatures could be well fitted by the anharmonic equation. However, the selected modes showed clear deviation from the fitted curves below T ε , suggesting that there are additional interactions besides the expected lattice and phononphonon interaction. In order to explore the correlation between the vibrational and structural changes, we also considered the temperature dependence of the wavenumber differences for these modes. The temperature dependence of the wavenumber difference Δω 3 , Δω 8 and Δω 11 for mode M3, M8 and M11 between the observed and extrapolated wavenumbers below T ε could be well expressed in a power-law equation like that in the displacive-type ferroelectric Sn 2 P 2 Se 6 [22]. As exemplified in figure 3, the difference Δω 3 , Δω 8 and Δω 11 increased abruptly from T ε , following the equation Δω ∝ (1-T/T C ) 2β with T C = 230 K~T ε , β = 0.35(2) (β is the critical exponent for the order parameter, the error of the critical exponent is from the upper and lower limits in the fitting process). This suggests a subtle local structural change below T ε . Since the present material is geometrically frustrated, the variation in local [OD] unit vibration (M3) will induce subtle changes in the integral structure. Thus, [Co 3 O(D)] unit (M8) and [Co 3 Cl] unit (M11) exhibited nearly the same variation with that in the [OD] unit. The line-widths for these modes especially M8 involving the magnetic Co 2+ ions, showed obvious anomalies near T ε deviating from the expected behavior, as illustrated in figure 4. In general, the change in Raman parameters with temperature can be caused by several factors, such as phonon-phonon anharmonic interaction, spin-phonon coupling, or phonon renormalization resulting from electron-phonon coupling [23,24]. The latter one can be neglected when the carrier concentration is low. Since the line-widths are not susceptible to the subtle lattice volume changes due to magnetostriction, the variation in the line-width of M8 should be induced by the spin-phonon coupling. This result is needed to be confirmed by further studies.
Since the Raman scattering intensity is susceptible to the change of ferroelectricity, we also considered the integrated intensities and intensity differences below T ε for the selected modes. As shown in figure 5, the intensities below T ε deviated from the straight lines extrapolated from the data above T ε and saturated toward 150 K. The intensity difference (absolute value) ΔI 3 , ΔI 8 and ΔI 11 between the observed and extrapolated intensities can be well fitted in the same way as that in the well-known proton-ordering ferroelectric PbHPO 4 [25] and order-disorder ferroelectric NaNO 3 [26,27], similarly following the power-law expression ΔI ∝ (1-T/ 230) 2 * 0.35 . The results suggest an ordering process below T ε accompanying the appearance of ferroelectricity. This ordering is strongly coupled with the Co tetrahedron, and gives rise to the structural change. Direct evidence for the transition near 230 K appeared as the additional spectral bands labeled N1 to N7, as shown in figure 1, which are highly asymmetric in their line shapes. The Raman spectra of Co 2 (OH) 3 Cl (not shown here), measured at the same conditions as that on the deuterated compound, showed no additional spectral bands as on the deuterated one in the same frequency and temperature ranges. Thus, considering the fact that their lattice structures are quite the same, it is apparent that these additional bands below 230 K on Co 2 (OD) 3 Cl have close relation with the deuterium motion. Asymmetric Raman line shapes have once been attributed to a Fano effect, which are often found in charge-ordered ferroelectric semiconductors [29]. The temperature-dependent normalized intensities for the additional bands in the present material, as illustrated in figure 6, can also be well fitted by the above ordering expression I ∝ (1-T/230) 2 * 0.35 . Apparently, the intensities of the additional bands could be used conveniently to describe the ordering process for the ferroelectric transition below T C = 230 K, as in other materials [22,[25][26][27]. The additional bands arising below 230 K might be infrared active modes, which become Raman active due to the symmetry breaking at the phase transition. Inspection of their frequencies suggests that the additional bands can be assigned to the combination or overtone of anharmonic vibrations of the [Co 3 O(D)] units, as shown in table 1. This kind of anharmonic overtone and combination were rare, however, they have been observed in a proton-ordering ferroelectric material NaNH 4 SO 4 ·2H 2 O [28]. The fact of the occurrence of ferroelectricity with deuteration in Co 2 (OD) 3 Cl and the overtone and combination of the [Co 3 O(D)] unit modes strongly suggest a kind of deuterium ordering near the T ε . Thus, the additional asymmetric bands, as well as the prominent changes of the selected modes can be consistently explained by changes in lattice and anharmonicities arising from the deuterium ordering in the insulating Co 2 (OD) 3 Cl. Several additional modes are still recognizable in the paraelectric phase at 240 K, showing remaining phonon-charge couplings as observed in proton-ordering ferroelectric compounds [25].
Through the analyses in the present work, we obtained the critical exponent β = 0.35 (2). As is well known, second order phase transitions follow a power-law expression with universal critical exponents, wherein the β values are calculated to be around 0.31 ∼ 0.35 for different models [30]. The present β value is consistent with the value predicted for intrinsic second-order transitions. This interpretation is consistent with the experimental facts that no obvious structural phase transition was observed in the present material. On the other hand, rearrangement of all [OD], [Co 3 O(D)] and [Co 3 Cl] units occurred accompanying the D sub-lattice ordering. This kind of rearrangement, we suspect, gave rise to the ferroelectricity. The nature of the ferroelectric phase transition in the present material is nearly the same as that showed in KDP, wherein both displacive and orderdisorder type transitions were involved.
Another relevant feature is the temperature dependence of a band at ∼210 cm −1 (marked by the vertical arrows in figure 1) in the vicinity of the mode M10. This band decreased upon heating and completely disappeared at about 150 K. This change, together with the tendencies of saturated wavenumbers and intensities of the phonon modes at lower temperatures (see figures 3 and 5), may suggest that the system reached a new equivalent state for the deuterium ordering below 150 K. This feature deserves further investigation. In summary, strong evidences of deuterium-order ferroelectricity in compound Co 2 (OD) 3 Cl are obtained from a Raman spectroscopic study. A critical scaling is found near the T ε ∼ 230 K with a critical exponent β = 0.35(2), suggesting a second order transition. Since prominent changes occurred in the A 1g and E g modes associated with D and O, the deuterium ordering should occur near the three side planes of the Co tetrahedron in the structure. This ordering is strongly coupled with the lattice vibration modes involving the [Co 3 O(D)] units, and would bring out a structural transition, as is exemplified in the well-known ferroelectric KDP. However, the structural change in Co 2 (OD) 3 Cl should be exceptionally small or unusual, thus it was overlooked in previous structural studies. The present work shows that Co 2 (OD) 3 Cl can be viewed as a unique prototypical multiferroic compound combining the geometric frustration and deuterium ordering ferroelectricity. The present material should belong to the mixed-type ferroelectrics that an ordering arrangement of deuterium and an instability of the lattice vibration occur simultaneously, thus manifesting both the displacive-type and order-disorder type ferroelectric features. | 3,845.8 | 2015-07-01T00:00:00.000 | [
"Chemistry",
"Physics"
] |
Intrinsically Microporous Polymer Nanosheets for High-Performance Gas Separation Membranes
8) 30 min. Then, 20 mL of anhydrous DMF was added and the temperature was set at 65 ° C. After 24 h, the reaction mixture was highly viscous and 12 mL more solvent was added to the system to avoid premature termination of the reaction. The reaction was continued for a total of 48 h and then stopped by quenching the reaction product in deionized water and some very dilute HCl. Then, the precipitate was filtered off and dried very well under reduced vacuum (3 h at room temperature). The crude polymer was washed with acetone (200 mL) and methanol (200 mL), after which it was filtered and dried again under vacuum at room temperature. The reaction product then underwent overnight-reflux with different solvents in a sequence of DMF (400 mL, 163 ° C), THF (400 mL, 77 ° C), chloroform (400 mL, 71 ° C), acetone (400 mL, 66 ° C), and two times methanol (400 mL, 74 ° C). After each time refluxing with a solvent, the product was filtered while still hot, re-washed with fresh hot solvent, and then dried well under suction at room temperature for 2 h. The polymeric sample was washed with the next solvent before being refluxed again. Finally, the polymer was dried overnight under reduced pressure at 130 ° C to give 0.89 g of network-PIM-1 (yield 73%). Full characterization results are provided in the Supporting Information. Characterization Methods : For PIM-1, weight-average molecular weight ( M w ), number-average molecular weight ( M n ), and polydispersity index ( M w / M n ) were measured using multi-detector gel permeation chromatography (Viscotek GPCmax VE2001 solvent/sample module with TDA302 triple detector array), with two Polymer Lab mixed bead columns (PL Mixed B × 2). Measurements were performed using filtered chloroform
for CO 2 /CH 4 and CO 2 /N 2 were redefined [6] on the basis of data for some new PIMs. The quest for high-performance gas separation membranes has extended to the use of 2D materials, [7,8] such as graphene [9] and graphene oxide, [10] inorganic nanosheets including zeolites, [11] transition metal dichalcogenides [12] and MXenes, [13] metalorganic framework nanosheets, [14] and covalent organic framework nanosheets. [15,16] Membrane properties may be tailored by combining 2D materials or other fillers with processable polymers to form mixed matrix membranes (MMMs). [17] Recently, attention has turned to the formation of porous organic polymeric nanosheets through polymerization. [18] Here, we introduce a new type of nanosheet created as a highly crosslinked analogue of a linear PIM. The tetrafluoro-monomer utilized in the synthesis of the prototypical polymer of intrinsic micro porosity, PIM-1 (Figure 1a), was replaced with an octafluoro-monomer to form a tightly linked network polymer, network-PIM-1 (Figure 1b). The gas permeation behavior was investigated for MMMs of network-PIM-1 with PIM-1 itself. The original concept was to create highly compatible fillers for use in MMMs. Surprisingly, pronounced effects were observed at very low filler concentrations, analogous to the effects seen with 2D materials such as graphene. [19] Further studies revealed that the poly merization gave rise to a nanosheet morphology, as discussed below.
Elemental analysis of a fully reacted, ideal network-PIM-1 structure, C 56 H 40 N 2 O 8 , would be expected to give: C, 77.40, H, 4.65; N, 3.22 wt%. Experimental values for dried network-PIM-1 powder were: C, 71.04; H, 4.64; N, 3.38; F, 2.25 wt%. The residual fluorine shows that some of the biphenyl units from the octafluoro-monomer are not fully reacted. This is unsurprising in a kinetically controlled step-growth polymerization, given the steric hindrance at a site with such a high density of functional groups.
The C/N ratio from elemental analysis can provide an insight into the relative proportions of spiro and biphenyl units incorporated into the network-PIM-1 structure. For complete reaction of two spiro units for each biphenyl unit, the expected C/N weight ratio is 24.01. The experimental C/N weight ratio of 21.02 is consistent with a structure having Microporous polymer nanosheets with thicknesses in the range 3-5 nm and with high apparent surface area (Brunauer-Emmett-Teller surface area 940 m 2 g −1 ) are formed when the effectively bifunctional (tetrafluoro) mono mer used in the preparation of the prototypical polymer of intrinsic microporosity PIM-1 is replaced with an effectively tetrafunctional (octafluoro) monomer to give a tightly crosslinked network structure. When employed as a filler in mixed-matrix membranes based on PIM-1, a low loading of 0.5 wt% network-PIM-1 nanosheets gives rise to enhanced CO 2 permeability and CO 2 /CH 4 selectivity, compared to pure PIM-1.
Membrane technology offers the prospect of straightforward and energy-efficient gas separation processes. [1] Membranes are needed that exhibit good selectivity in combination with high permeability. Robeson [2] established the upper bounds of performance that could be achieved for industrially important gas pairs with the polymeric membranes available in 1991. A class of high free volume, glassy polymers introduced in 2004, referred to as polymers of intrinsic microporosity (PIMs), [3] contributed to a revision in 2008 of the upper bounds, [4] and a further revision in 2015 for some gas pairs. [5] Recently, the upper bounds about five spiro units for every three biphenyl units, as indicated in Figure 1b.
Solid-state 13 C NMR spectroscopy ( Figure S5, Supporting Information) and Fourier transform infra-red spectroscopy ( Figure S6, Supporting Information) of network-PIM-1 show essentially the same features as PIM-1 itself, confirming the chemical similarity of the two materials. The powder X-ray diffraction (PXRD) pattern ( Figure S9, Supporting Information) of network-PIM-1 was similar to that of PIM-1, which shows three peaks at 2θ values corresponding to d spacings of 6.7, 5.2, and 3.9 Å, superimposed on a smooth shoulder. [21,22] Images from atomic force microscopy (AFM) at two different resolutions are shown in Figure 2a dispersion in chloroform. Extended sheet-like structures are seen, with lateral sizes ranging from a few hundred nanometers to a few micrometers. The height profiles associated with some of the structures (represented by lines 1-4 in Figure 2b) are shown in Figure 2c. The thickness versus distance plots of lines 1-3, which may be attributed to single sheets of network-PIM-1, show thicknesses in the range 3-5 nm and lateral sizes of a few hundred nanometers. The height profile related to line 4 shows a jump in the thickness to around 15 nm, which may be related to the stacking of three or more layers. The AFM results suggest that network-PIM-1 is composed of nanosheets with a high aspect ratio (≈100) and thicknesses of a few nanometers.
Further evidence for a nanosheet morphology comes from transmission electron microscopy (TEM), operated in scanning transmission electron microscopy (STEM) mode, of network-PIM-1 deposited from chloroform onto a lacey carbon grid ( Figure 2d). Elemental mapping for C, N, O, and F by energy dispersive X-ray spectroscopy (EDX) ( Figure S8, Supporting Information) confirms the presence of organic sheet-like structures. It should be mentioned that Cu was also mapped during the EDX analysis, as it was one of the elements present in the substrate used for TEM/EDX. Additionally, a trace of K was detected in network-PIM-1, which might be due to a small quantity of potassium carbonate entrapped in the crosslinked structures during the polymerization. Scanning electron microscopy (SEM) images of network-PIM-1 are also presented in Figure S7, Supporting Information. These images suggest the presence of extended structures, which might be related to single or aggregated particles.
The question arises as to why network-PIM-1 has a nanosheet morphology. There is innate anisotropy in the monomers, so that reaction will give a structure in which there is a degree of orientational order, with the nitrile groups tending to point along the same axis. For linear PIM-1, the chain can bend and flex sufficiently that a preferred orientation is not maintained over its entire length. However, for network-PIM-1 with a high crosslink density, the necessity for multiple connections at biphenyl units leads to a large number of small macrocycles that maintain the rigidity of the structure. A molecular model of a feasible fragment of nanosheet structure is shown in Figure 1c,d. The side view in Figure 1c illustrates the preferred orientation of the biphenyl units (some are marked by mauve lines) and shows, as yellow squares, sites where the structure can be extended in a transverse direction. The top view in Figure 1d shows that there are no sites for reaction on that face. Thus, as the structure is built up during step-growth polymerization, it is relatively easy to extend in directions perpendicular to that defined by the orientation of the nitrile groups, but there are few options for extending out of that plane. Computer simulation studies are in progress to obtain a fuller understanding of nanosheet formation.
Although network-PIM-1, like PIM-1 itself, is essentially amorphous, the model shown in Figure 1c,d indicates a high degree of orientational order within a layered structure, akin to a smectic liquid crystal, albeit locked into a network rather than fluid as in a liquid crystal. Such a structure is expected to exhibit birefringence. Polarized light microscopy ( Figure S11, Supporting Information) of a membrane with 20 wt% network-PIM-1 filler, at which loading there is some agglomeration of filler particles, demonstrates that the filler particles are strongly birefringent, unlike the background of PIM-1 itself.
The N 2 adsorption/desorption isotherm at 77 K for network-PIM-1 is compared with that for a sample of conventional PIM-1 in Figure 3a. Both polymers show high uptake at low relative pressure, which is characteristic of a microporous material (pore size < 2 nm) as defined by IUPAC. [23] Network-PIM-1 shows slightly higher uptake of N 2 than PIM-1, reflected in a higher apparent surface area from Brunauer-Emmett-Teller (BET) analysis (940 ± 7 m 2 g −1 for network-PIM-1 compared with 780 ± 7 m 2 g −1 for PIM-1). CO 2 adsorption isotherms at 273 K (Figure 3b) similarly show higher uptake for network-PIM-1 than for PIM-1. This translates into a slight enhancement in CO 2 uptake when small amounts of network-PIM-1 are incorporated into a PIM-1 membrane (Figure 3c).
Macromol. Rapid Commun. 2020, 41, 1900572 Thermogravimetric analysis (TGA) of network-PIM-1 is compared with that of PIM-1 in Figure 3d. Under the conditions of the experiment, PIM-1 does not show any significant weight loss below 450 °C. Network-PIM-1 shows a modest weight loss in the temperature range 330-450 °C, which may indicate that there are some labile short branches in the structure. The monomers used to prepare network-PIM-1 show weight losses at lower temperatures than the polymer, as can be seen in Figure 3d.
Self-standing MMMs were prepared for gas permeation measurements with 0.027, 0.2, 0.5, 5, and 10 wt%, with respect to the total solids content, of network-PIM-1 in PIM-1. Pure PIM-1 membranes were also prepared for comparison. Membrane thicknesses were in the range 59-80 µm. Attempts to prepare MMMs with higher network-PIM-1 loadings resulted in excessively brittle membranes, but a sample with 20 wt% loading was utilized for polarized light microscopy ( Figure S11, Supporting Information). SEM images ( Figure S10, Supporting Information) show evidence of filler agglomeration at loadings of 5 and 10 wt%. Despite the apparent chemical similarity of the network-PIM-1 and PIM-1 structures, there is a tendency to segregation at higher filler loadings, which may be attributed, at least in part, to the nanosheet structure of the network polymer.
Membranes were immersed in methanol for 15 h and then dried prior to carrying out measurements. This procedure opens up free volume in the membrane, helps to flush out residual solvents, and reverses the effects of membrane history.
Mixed gas CO 2 /CH 4 (1:1, v/v) permeation data for methanol-treated membranes with network-PIM-1 loadings up to 10 wt% are shown in Figure 4a. Pure PIM-1 exhibited a CO 2 permeability of 5920 Barrer, within the range of values previously reported for PIM-1. This represents orders of magnitude higher permeability than is achieved for traditional membrane polymers.
At network-PIM-1 loadings of 0.2 and 0.5 wt%, there is an enhancement in gas permeabilities, the CO 2 permeability rising to 9780 Barrer for the 0.5 wt% MMM. Enhanced gas permeabilities at low filler loadings have previously been observed for MMMs of graphene in PIM-1, [19] which may be attributed, at least in part, to the effect of the sheet-like nanofiller on the packing of the PIM-1 polymer chains. At higher network-PIM-1 loadings, the permeabilities are in a similar range to PIM-1 alone, but with 10 wt% network-PIM-1 the CO 2 /CH 4 selectivity is enhanced. Unlike graphene, network-PIM-1 is a porous material through which gas permeation can occur, but the highly crosslinked structure may modify the selectivity to different gases. Gas permeation can often be understood in terms of a solution-diffusion model, in which the permeating species first undergo sorption or dissolution in the membrane on the feed side, then diffuse through the membrane, and finally desorb on the permeate side. In this model, the permeability coefficient, P, can generally be expressed as the product of a sorption or solubility coefficient, S, and a diffusion coefficient, D (Equation (1)).
P SD
For a binary system, selectivity is expressed as a ratio of permeabilities, and differences in selectivity may arise from differences in S and/or from differences in D. It was shown above that network-PIM-1 shows enhanced CO 2 sorption compared to PIM-1. The tightly linked structure is likely also to modify the diffusion coefficient.
It should be noted that most gas permeation studies in the literature are carried out with pure gases. Mixed gas permeation studies, as undertaken in the present work, are more realistic and can reveal permeation behavior different to that observed with pure gases, particularly for mixtures involving ), [2] 2008 ( ), [4] and 2019 ( ) [6] upper bounds, with data from this work for PIM-1 ( ) and MMMs with 0.5 wt% ( ) and 10 wt% ( ) network-PIM-1 3 days after methanol treatment, and for PIM-1 ( ) and the MMM with 0.5 wt% network-PIM-1 ( ) after 7 months aging; also shown are data from the literature for MMMs of PIM-1 with 24.2 wt% ZIF-8 (▸), [27] 0.5 wt% f-MWCNT (•), [28] 2 wt% SNW-1 (◂), [29] and 0.126 wt% rGO-OA (▾). [30] highly condensable gases such as CO 2 . The sorption coefficient for one gas may be reduced because of competitive sorption by the other, [24] or the diffusion of one gas may be hindered because of a "blocking" effect of the other. [25] In addition, the presence of highly soluble gases such as CO 2 may enhance the mobility of the polymer chains and bring about swelling of the polymer matrix, an effect referred to as plasticization. Swaiden et al. [26] previously investigated the pure and mixed gas CO 2 / CH 4 separation properties of PIM-1, and found that for CO 2 the mixed gas permeability was lower than the pure gas permeability (attributed to competition for CO 2 sorption sites by copermeating CH 4 ), while for CH 4 the mixed gas permeability was higher than the pure gas permeability (attributed to enhanced diffusion of CH 4 due to a plasticizing effect of CO 2 ). Both effects give rise to lower mixed gas CO 2 /CH 4 selectivity than expected from pure gas measurements.
Gas permeation data for different membrane materials may conveniently be compared on double logarithmic Robeson [2,4] plots of selectivity, for a pair of gases, versus the permeability of the fastest gas. Figure 4b shows that MMMs with 0.5 wt% and 10 wt% network-PIM-1 exceed Robeson's 2008 upper bound [4] and move toward the recently proposed 2019 upper bound for the CO 2 /CH 4 gas pair. [6] It is significant that a change in polymer topology from linear to network can have such a pronounced effect, and this is being explored further in ongoing research. For comparison, representative data from the literature are also shown for MMMs of PIM-1 with the zeolitic imidazolate framework ZIF-8, [27] functionalized multi-walled carbon nanotubes (f-MWCNT), [28] the covalent organic framework SNW-1, [29] and octyl-functionalized reduced graphene oxide (rGO-OA). [30] High free volume, glassy polymers such as PIMs are nonequilibrium systems that tend to lose free volume, and hence permeability, over time, in a process referred to as physical aging. [31] Permeation data after 7 months aging are included in Figure 4b for PIM-1 and for the MMM with 0.5 wt% network-PIM-1. As expected, both systems show a loss of permeability over time, accompanied by an increase in selectivity. The small loading of network in the MMM does not suppress aging, but it maintains an enhanced permeability relative to PIM-1.
The performance of membranes with 0.5 wt% network-PIM-1 was checked for three further gas mixtures: CO 2 /N 2 , H 2 /N 2 , and H 2 /CH 4 (all 1:1, v/v). Permeabilities and selectivities for all the gas mixtures are shown in Figure 5. The most pronounced effects were seen for the strongly sorbing gas CO 2 . As mentioned above, CO 2 adsorption experiments show that addition of network-PIM-1 to a PIM-1 membrane leads to an enhancement of CO 2 sorption (Figure 3c).
This work demonstrates a new route to the formation of porous polymer nanosheets and introduces a new class of nanofiller with potential for use in high-performance mixed matrix membranes. Promising results are obtained for carbon dioxide separations.
Experimental Section
Synthesis of PIM-1: PIM-1 (M w = 158 000 g mol −1 , M w /M n = 2.95) was synthesized by a variation of the high-temperature method proposed by Du et al. [32] and details are given in the Supporting Information.
Well-dried 4,4′-dicyano-2,2′,3,3′,5,5′,6,6′-octafluorobiphenyl (0.483 g, 1.4 mmol), 5,5′,6,6′-tetrahydroxy-3,3,3′,3′-tetramethyl-1,1′spirobisindane (TTSBI, 0.946 g, 2.8 mmol), and potassium carbonate (K 2 CO 3 , 3.073 g, 22.4 mmol) were added to a two-neck round bottom flask and the mixture was stirred under dry N 2 at room temperature for 30 min. Then, 20 mL of anhydrous DMF was added and the temperature was set at 65 °C. After 24 h, the reaction mixture was highly viscous and 12 mL more solvent was added to the system to avoid premature termination of the reaction. The reaction was continued for a total of 48 h and then stopped by quenching the reaction product in deionized water and some very dilute HCl. Then, the precipitate was filtered off and dried very well under reduced vacuum (3 h at room temperature). The crude polymer was washed with acetone (200 mL) and methanol (200 mL), after which it was filtered and dried again under vacuum at room temperature. The reaction product then underwent overnightreflux with different solvents in a sequence of DMF (400 mL, 163 °C), THF (400 mL, 77 °C), chloroform (400 mL, 71 °C), acetone (400 mL, 66 °C), and two times methanol (400 mL, 74 °C). After each time refluxing with a solvent, the product was filtered while still hot, re-washed with fresh hot solvent, and then dried well under suction at room temperature for 2 h. The polymeric sample was washed with the next solvent before being refluxed again. Finally, the polymer was dried overnight under reduced pressure at 130 °C to give 0.89 g of network-PIM-1 (yield 73%). Full characterization results are provided in the Supporting Information.
Characterization Methods: For PIM-1, weight-average molecular weight (M w ), number-average molecular weight (M n ), and polydispersity index (M w /M n ) were measured using multi-detector gel permeation chromatography (Viscotek GPCmax VE2001 solvent/sample module with TDA302 triple detector array), with two Polymer Lab mixed bead columns (PL Mixed B ×2). Measurements were performed using filtered chloroform as the eluent at a flow rate of 1 mL min −1 . 1 H and 13 C NMR spectra were collected with a Bruker DPX 400 MHz spectrometer at room temperature. Solid-state 13 C cross-polarization/ magic angle spinning (CP-MAS) NMR was conducted at room temperature using a Bruker AVANCE III 400 MHz instrument with a static wide line probe (Bruker, 40-163 MHz).
Infrared spectra of solids were recorded on a Thermoscientific Nicolet iS5, iD5 spectrometer annexed to a Whatman FTIR purge gas generator. The spectra were recorded in the attenuated total reflectance (ATR) mode, with a resolution of 0.25 cm −1 , a sensitivity of 1, and 16 scans in the range 4000-500 cm −1 .
STEM and EDX data were obtained using a FEI Tecnai G2 20 equipped with an X-Max EDX detector. The TEM specimen was prepared by drop casting onto a lacey carbon grid of the solution in chloroform.
Tapping mode AFM (Bruker Multimode) was used to analyze the size and thickness of network-PIM-1 particles obtained from a drop of an ultra-dilute dispersion in chloroform cast on a silicon wafer substrate. 2D surface scanning images were computed automatically using Nanoscope Analysis software. The AFM 2D images were then analyzed by Gwyddion 2.50 software to obtain the height profile of the particles.
PXRD was performed using a Philips X' Pert Pro Diffractometer with Cu Kα radiation (1.54060 Å) generated by 20 mA current and 30 kV voltage. The PXRD patterns were collected at room temperature with 2θ value ranging from 3° to 50°, at a scanning rate of 20.95 s per step and a step size of 0.016°. The intersegmental spacing between polymer chains (d-spacing) was estimated by Bragg's law (d = nλ/2sin θ).
Polarized light microscopy images were obtained using a Leica DM 2500M Materials Analysis Microscope. A sample of MMM with 20 wt% network PIM-1 was mounted on a clean glass slide and the images were obtained at room temperature and 10× magnification.
A Micrometrics ASAP 2020 sorption analyzer was used to obtain N 2 adsorption/desorption isotherms at 77 K and to measure the BET surface areas. Samples were accurately weighed and about 0.10 g of the polymer was degassed at 120 °C for 16 h under high vacuum (10 −5 bar) before starting the analysis. After cooling, degassed samples were reweighed, and placed in the analysis port. Nitrogen adsorption/desorption isotherms were undertaken at 77 K. Free space measurements were done after the sorption analysis and the obtained value was then used to correct the isotherms and the BET surface area. CO 2 adsorption up to 10 bar at 273 K was conducted using a Micromeritics ASAP 2050 sorption analyzer. After degassing the samples (≈100 mg) at 120 °C for 16 h, the dried samples were transferred to the analysis port where CO 2 was injected to the sample and the amount of adsorbed CO 2 from 0 to 9 bar was measured.
TGA was used to establish the thermal degradation of the monomers and the two polymers. A Perkin-Elmer TGA System was used and the samples were heated to 1000 °C at a rate of 10 °C min −1 under nitrogen atmosphere.
Membrane Preparation: MMMs were prepared with different loadings of network-PIM-1 in PIM-1. As an example, the procedure for the fabrication of an MMM containing 5 wt% of network-PIM-1 is as follows: PIM-1 (0.3 g) was dissolved in anhydrous chloroform (5 mL) by stirring the solution at room temperature for 12 h. A dispersion of network-PIM-1 (0.0159 g) in chloroform (5 mL) was prepared by stirring the mixture for 12 h at room temperature, followed by 10 min of sonication using a probe sonicator (Cole-Parmer Instruments, CPX 750, 750 watts). The PIM-1 solution was then added to the filler dispersion and the mixture was stirred magnetically for 1 day, followed by 10 min sonication. During the sonication, the mixture was kept in an ice bath and the sonication was done at intervals of 10 s to minimize the evaporation of the solvent. The homogenous mixture was then poured into an 8 cm diameter petri dish, which was covered and placed in a nitrogen cabinet for 48-72 h to allow for slow solvent evaporation. The formed membrane was then kept in a desiccator at room temperature for 2 days, followed by drying in a vacuum oven at 100 °C overnight to remove the remaining solvent.
Pure PIM-1 membranes were similarly prepared by casting a solution of PIM-1 (0.3 g) in anhydrous chloroform (10 mL).
Membranes were methanol-treated as follows: The films were slowly immersed in a glass petri dish filled with methanol and were kept there for 15 h, during which the methanol was refreshed two times. Then, the films were removed and kept in a desiccator for 2 days at room temperature, then dried in a vacuum oven at 100 °C overnight.
Mixed Gas Permeation Measurements: Mixed gas permeability measurements were carried out as follows: A binary feed mixture (25 mL min −1 of each gas) was used in a permeation apparatus employing the standard variable volume method. The total feed side pressure was set to ≈3 bar at T = 25 °C and the permeate side was at atmospheric pressure. Alicat Scientific mass flow controllers with the operating flow range of 0-100 ccm (cubic centimeter per minute) were used for the preparation of binary mixtures. Flat sheet membranes were masked between two aluminum-tape donuts and the membrane-aluminum interface was sealed using two-part potting epoxy (Araldite Rapid, Industrial MTCE Suppliers). Samples of 1 in. diameter were placed in the stainless steel permeation cell, where the two parts of the cell were sealed with rubber O-rings. Helium (60 mL min −1 ) and Argon (10 mL min −1 or 60 mL min −1 ) were used as the sweep gases for the analysis of permeates containing CO 2 and H 2 , respectively. The sweep gas was at atmospheric pressure and was used to dilute the permeate gases and direct them to a micro gas chromatograph (GC, Agilent technologies 490) for automated on-line analysis of the permeate composition. The GC had two columns, MolSieve 5A and PoraPLOT U (PPU), with thermal conductivity detectors (TCD). PPU column was used for the analysis of CO 2 containing mixtures and MolSieve 5A was used for the analysis of H 2 containing mixtures. After measuring the flux of each gas, the permeability of the membranes was calculated using Equation where P i is the permeability coefficient for component i in Barrer (1 Barrer = 10 −10 cm 3 [STP] cm cm −2 s −1 cmHg −1 = 3.35 × 10 −16 mol m m −2 s −1 Pa −1 ), N i is the steady-state flux of penetrant i (cm 3 cm −2 s −1 ), l is the membrane thickness (cm), and p i,1 and p i,2 are the partial pressures of component i in the feed (1) and permeate (2) side (in cm Hg). The selectivity was calculated as the ratio of the permeabilities for a pair of gases. The stage cut, the ratio of the flow rate of permeated gases (CO 2 and CH 4 ) to the flow rate in the feed, was less than 0.01 in all experiments. | 6,274.8 | 2019-12-17T00:00:00.000 | [
"Materials Science"
] |
Experimental Study on Km-Range Long-Distance Measurement Using Silicon Photomultiplier Sensor with Low Peak Power Laser Pulse
: Silicon photomultipliers (SiPM) have drawn considerable attention due to their superior sensitivity with a multi-pixel matrix structure. SiPM can be the choice of a detector for time of flight measurement which is one of the most promising applications in the field of light detection and ranging (LiDAR). In this work, we take advantage of SiPM and attempt to measure longer distances with a low peak power semiconductor laser under outdoor sunny and windy conditions. We achieved a long detection range of a few kilometers by using SiPM and a laser with a pulse energy of 9 µ j at 0.905 µ m and 3 dB enhancement in signal to noise ratio (SNR) by the implemented signal extraction algorithm. From the simulation performed, the minimum SNR value and detection probability were also determined for the outdoor field tests. prototype show that SiPMs along with low-power pulsed laser diode yield promise long-range LRF performance owing to their exceptional properties such as high sensitivity, multipixel architectures and relatively low-voltage operation. We achieved a long-detection range over 3.5 km by employing a relatively low power laser with a pulse energy of a few µ j at 0.905 µ m and 3 dB enhancement in SNR by the implemented signal extraction algorithm based on Wiener filtering. Our measurement resolution was not good because of using a 100 ns long laser pulse which corresponds to the uncertainty of 30 m. Although a LRF using a time-to-digital converter has better resolution, our uncertainty can be reduced if SNR is increased. In order to increase our measurement sensitivity, we need to have better SNR than those obtained. One way of doing this is to use a pulse coding scheme when sending laser light. Since we have implemented FPGA to control everything, this will be our future plan. Improvement can also be achieved by using proper optical design in the beam shaping of the laser output and also in the receiver FOV. Although SiPM could be vulnerable to stray light which results as an uncorrelated noise added to its intrinsic primary noise (related to dark count rate), our tests show that SiPM along with optimized optics and digital filtering promise to realize low-power and low-cost practical long-range LRF and LiDAR applications.
Introduction
Motivated by the plenty of applications such as laser remote sensing of the atmosphere [1,2], time of flight measurements [3][4][5][6] and visible light communication [7,8], light detection and ranging (LiDAR) has become one of the most versatile active remote measurement techniques. In particular, a rush to develop autonomous cars has led to a surge in the field of LiDAR based on time of flight (ToF) techniques. ToF techniques are the basis of LRF (laser rangefinder) systems which measures the time delay between the emission of the laser pulse and the detection of the back-scattered arrival of that pulse. The most commonly used laser types mainly operate at two spectrum bands of around 0.9 µm and 1.5 µm. It is well known that 1.5 µm wavelength is within the eye-safe band due to the fact that water absorption of 1.5 µm is 100 times more than that of 0.9 µm [9]. Therefore, it requires more power because longer wavelengths suffer more scattering from atmospheric moisture. On the other hand, when we consider Rayleigh scattering which states that scattering is inversely proportional to the fourth power of the wavelength, that means shorter wavelengths scatter more than longer wavelengths, which degrade the performance of laser rangefinder at shorter wavelengths. Also, it is well known that solar radiation is much less than 0.9 µm. Inevitably, cost is another issue when deciding the operational wavelength. Because 0.9 µm is compatible with silicon-based photodetectors (i.e., avalanche photodetectors (APDs) or photomultipliers), it is much more cost-effective than InGaAs detectors. The choice of laser wavelength has many aspects that one needs to consider carefully when designing laser rangefinders. efficiencies and high electric power consumption. On the other hand, semiconductor lasers, despite of their limited pulse energies (i.e., a few µjoules), promise many practical advantages such as low cost, small volume, ease of integration, high efficiency and low electrical consumption as well as the capability of high-speed modulation. Semiconductor lasers have also some inherent shortcomings such as elliptical beam shapes with fairly large divergence angles and high astigmatism, yet these issues can be managed by proper optic design such as using cylindrical lenses or anamorphic prisms in the Tx and Rx optics for long-range applications. Thus, semiconductor lasers can be used with SiPMs with appropriate optical design to enable a long-range LRF system with cost-effective and small size features as well as an eye-safe capability at 0.9 µm band owing to the capability of low power detection for SiPMs. Here, we report on such a LRF system using commercially available SiPM with multi-pixel architecture and peak power of 90 Watt at 1 kHz and 100 ns for a relatively long-range detection range of >1 km. An experiment showed that a 3 dB improvement in SNR was obtained by the help of a signal extraction algorithm.
In the past two decades, SiPMs have been extensively considered in highly sensitive detection applications due to their low operating voltage, high gain, high photon detection efficiency, photon number resolving capability. SiPMs have rapidly gained attention owing to their superior sensitivity, high gain along with multi-pixel architecture as well as ideal cost and size features. They were first aimed to be used as an alternative to a conventional PMT in nuclear applications [20,21]. The SiPM has its own unique performance characterized by the dark count rate (DCR), photon detection probability, hold-off time and after pulsing effects [13,22,23]. SiPMs have now been utilized for a wide range of applications such as LiDAR [24], fluorescence light detection in biology and physics [25,26], high-energy physics [27], quantum optics [28,29] and medical purposes [30][31][32].
The SiPM consists of a dense array of small microcells (SPADs) functioning in Geigermode, each one with its integrated passive quenching resistors. These cells are arrayed in a matrix form and connected in parallel, making a common anode and cathode [33]. When a microcell in the SiPM is activated by the absorbed photon, Geiger avalanche is initiated giving rise to a photocurrent to flow through the microcell. The sum of the photocurrents from each of these individual microcells combines to give an analog output and reading out from anode or cathode is referred to as the standard output [33]. When the SiPM is biased above breakdown, working in Geiger mode, it produces a photocurrent proportional to the number of cells activated which flows through the sensor from cathode to anode, either of which can be used as a standard output terminal. Reading out from the cathode will give a negative polarity [33]. In addition to the anode and cathode, a third terminal called the fast output has been developed by On Semiconductors. It is the sum of capacitively coupled outputs from each microcell. The fast output is used to provide information on the number of photons detected since its amplitude is proportional to the number of microcells that are activated. When photons arrive at a pixel, a pulse is generated at its output regardless of the number of photons. If two or more avalanches occur at the same time, the amplitude of the electrical output pulse is equal to the number of avalanches times the amplitude of a single avalanche. Therefore, the height of the output pulse may be said to be proportional to the number of detected photons assuming that noise is neglected [34]. Then, the SiPM detector signal is the summed output of that 2D array of microcells, providing great sensitivity improvement over APD and PIN diodes. In general, SiPMs are operated in Geiger-mode may provide high gain (i.e., >10 6 ) at moderate bias voltages (i.e.,~30 V). Operating (bias) voltage (V bias ) of SiPM is defined as the sum of breakdown voltage (V br ) and overvoltage (∆V). The gain of a SiPM sensor is defined as the amount of charge created for each detected photon, and is a function of overvoltage and microcell size and can be calculated from the overvoltage, the microcell capacitance C, and the electron charge, q [33]: One of our motivations is to investigate the long range capability of laser rangefinder based on 905 nm semiconductor laser and SiPM detector. These two combinations offer a very cost-effective solution for a few km laser rangefinders. Therefore, in this work we study the performance of SiPM based on this configuration.
Experimental Studies
The MICRORB−SMTPA−10020 pin adapter board made by SensL, was used in the receiver. Some important parameters for the SiPM detector used in this work are summarized in the Table 1. The printed circuit board (PCB) board houses the SiPM sensor and has through-hole pins to allow its use with standard sockets or probe clips [33]. This sensor was mounted to our designed amplifiers on the PCB board, forming a SiPM-based Rx for our experiments as shown in Figure 1. In the experiment, the optimum overvoltage in terms of gain and noise level is determined to be 10 Volt, and it remained fixed during the experiments. Therefore, the typical operating (bias) voltage is −33, see Table 1. In this work, we used a standard output signal which was connected to the amplifier circuit. The fast output was also utilized in order to provide information on the number of photons detected. Although fast output gives much better accuracy of the target on ranging, we consider that fast output signal is difficult to handle in readout electronics since it has both positive and negative sides.
= × ∆
One of our motivations is to investigate the long range capability of laser rangefinder based on 905 nm semiconductor laser and SiPM detector. These two combinations offer a very cost-effective solution for a few km laser rangefinders. Therefore, in this work we study the performance of SiPM based on this configuration.
Experimental Studies
The MICRORB−SMTPA−10020 pin adapter board made by SensL, was used in the receiver. Some important parameters for the SiPM detector used in this work are summarized in the Table 1. The printed circuit board (PCB) board houses the SiPM sensor and has through-hole pins to allow its use with standard sockets or probe clips [33]. This sensor was mounted to our designed amplifiers on the PCB board, forming a SiPM-based Rx for our experiments as shown in Figure 1. In the experiment, the optimum overvoltage in terms of gain and noise level is determined to be 10 Volt, and it remained fixed during the experiments. Therefore, the typical operating (bias) voltage is -33, see Table 1. In this work, we used a standard output signal which was connected to the amplifier circuit. The fast output was also utilized in order to provide information on the number of photons detected. Although fast output gives much better accuracy of the target on ranging, we consider that fast output signal is difficult to handle in readout electronics since it has both positive and negative sides.
Parameters
SiPM (MICRORB−SMTPA−10020) Microcell Size 20 µm × 20 µm Active Area 1 mm × 1 mm The laser used in this work was the OSRAM SPL PL90-3, operating at a wavelength of 905 nm and providing up to 90 W of peak power. Beam divergences parallel and perpen-Appl. Sci. 2021, 11, 403 5 of 13 dicular to the axis of propagation were 9 and 25 degrees, respectively. The driver board of the laser was designed by us that consists of a Gallium Nitride field-effect transistors for high-speed switching and discharging capacitors to supply necessary large pulse current. Measured energy at the output of the laser diode is approximately 9 µj at 100 ns pulse width and 1 kHz repetition rate. Note that at the output of the laser rangefinder we lose almost 70% of it because of the large divergence of the laser diode which overfills the aperture.
The experiment was performed by using our own prototype shown on the left side of Figure 2 and on the right is the representation of the setup. Both detector (SiPM) and laser were mounted to the platform which can be slightly adjusted for alignment. The Tx and Rx unit both had the same high precision aspheric lens with a focal length of 100 mm (AL50100-B, Thorlabs, Newton, NJ, USA) and its design wavelength was 780 nm. These lenses which have anti-reflection coating between 650 nm and 1050 nm are 50 mm in diameter with an f-number of 2. They are mounted such that their plain sides facing the laser and detector. Collimated laser beam is in line-rectangular shape and its long edge divergence is approximately 3 mrad (full angle). Receiver full angle field of view (FOV) is calculated as 10 mrad. When we consider the single pixel size, then we obtain instantaneous FOV of 0.2 mrad which corresponds to 20 cm × 20 cm area at 1 km distance for single pixel. In one of our measurement, we used a black wooden target of size 2 by 2 m. The measured distance for this target was 1880 m. Laser spot size on this target was about 5.5 m when the full angle divergence was taken. However, angular field of view of the receiver was 18 m which is larger than the target and the laser spot. In this case the background noise increased which degraded the SNR. Therefore, both transmitter and receiver optics needed to be optimized further. In the test area, direct sunlight and background infrared (IR) radiation degraded the performance of the receiver. Therefore, in front of the receiver, to effectively filter out background light, a band-pass (FL905-10, Thorlabs) and long-pass filters (FEL850-10, Thorlabs) were mounted as close as to each other. Then, the total transmittance of the filters drops to 56%.
of 905 nm and providing up to 90 W of peak power. Beam divergences parallel and perpendicular to the axis of propagation were 9 and 25 degrees, respectively. The driver board of the laser was designed by us that consists of a Gallium Nitride field-effect transistors for high-speed switching and discharging capacitors to supply necessary large pulse current. Measured energy at the output of the laser diode is approximately 9 µj at 100 ns pulse width and 1 kHz repetition rate. Note that at the output of the laser rangefinder we lose almost 70% of it because of the large divergence of the laser diode which overfills the aperture.
The experiment was performed by using our own prototype shown on the left side of Figure 2 and on the right is the representation of the setup. Both detector (SiPM) and laser were mounted to the platform which can be slightly adjusted for alignment. The Tx and Rx unit both had the same high precision aspheric lens with a focal length of 100 mm (AL50100-B, Thorlabs) and its design wavelength was 780 nm. These lenses which have anti-reflection coating between 650 nm and 1050 nm are 50 mm in diameter with an fnumber of 2. They are mounted such that their plain sides facing the laser and detector. Collimated laser beam is in line-rectangular shape and its long edge divergence is approximately 3 mrad (full angle). Receiver full angle field of view (FOV) is calculated as 10 mrad. When we consider the single pixel size, then we obtain instantaneous FOV of 0.2 mrad which corresponds to 20 cm × 20 cm area at 1 km distance for single pixel. In one of our measurement, we used a black wooden target of size 2 by 2 m. The measured distance for this target was 1880 m. Laser spot size on this target was about 5.5 m when the full angle divergence was taken. However, angular field of view of the receiver was 18 m which is larger than the target and the laser spot. In this case the background noise increased which degraded the SNR. Therefore, both transmitter and receiver optics needed to be optimized further. In the test area, direct sunlight and background infrared (IR) radiation degraded the performance of the receiver. Therefore, in front of the receiver, to effectively filter out background light, a band-pass (FL905-10, Thorlabs) and long-pass filters (FEL850-10, Thorlabs) were mounted as close as to each other. Then, the total transmittance of the filters drops to 56%.
In this work, for all experiments, the laser was fired at a repetition rate of 1 kHz with a 100 ns pulse width. As soon as the laser fired, we started acquiring data and the number of frames acquired can be controlled through the field programmable gate array (FPGA) board. In this work, for all experiments, the laser was fired at a repetition rate of 1 kHz with a 100 ns pulse width. As soon as the laser fired, we started acquiring data and the number of frames acquired can be controlled through the field programmable gate array (FPGA) board.
Data Acquisition
The data acquisition part of our prototype was configured as shown in the block diagram below, Figure 3. First, analog electrical signals from the photodetector were Appl. Sci. 2021, 11, 403 6 of 13 amplified by the 2-stage voltage amplifier whose circuit diagram is also shown in the Figure 4. The gain of the amplifier was calculated as 420.
Data Acquisition
The data acquisition part of our prototype was configured as shown in the block diagram below, Figure 3. First, analog electrical signals from the photodetector were amplified by the 2-stage voltage amplifier whose circuit diagram is also shown in the Figure 4. The gain of the amplifier was calculated as 420. When detecting low power optical signals, amplification of the standard output with band pass filtering was required to provide sufficient gain. To read out the SiPM from the standard output, the photocurrent generated on the detection of photons was first converted to the voltage by 50 Ω load resistor and then is amplified by using a voltage amplifier as depicted in Figure 4. LMH6624 is ultra-low noise op-amp with 1.5 GHz gain bandwidth product. The cut off frequency of the amplifier circuit was designed to be at 80 MHz as to be compatible with the pulse width for the maximum gain of approximately 420. The amplified and filtered signal was then fed into the high-speed ADC module (ADS42B49, Texas Instruments). It converted analog voltage to 14 bit parallel discrete digital data at a 100 MHz sampling rate. An FPGA module acquired the digital data and transferred the average of 1000 frames at 1 Hz to the computer via a USB port, continuously. Averaging processes were performed by summing each frame point by point and then divided by the total number of frames. Each frame had 4096 sampled data points with a corresponding data point interval of 10 ns. A signal extraction algorithm was developed in Labview platform, running in the computer. Second averaging was done in the algorithm. The number of averaging frame was selected by the user.
Data Acquisition
The data acquisition part of our prototype was configured as shown in the block diagram below, Figure 3. First, analog electrical signals from the photodetector were amplified by the 2-stage voltage amplifier whose circuit diagram is also shown in the Figure 4. The gain of the amplifier was calculated as 420. When detecting low power optical signals, amplification of the standard output with band pass filtering was required to provide sufficient gain. To read out the SiPM from the standard output, the photocurrent generated on the detection of photons was first converted to the voltage by 50 Ω load resistor and then is amplified by using a voltage amplifier as depicted in Figure 4. LMH6624 is ultra-low noise op-amp with 1.5 GHz gain bandwidth product. The cut off frequency of the amplifier circuit was designed to be at 80 MHz as to be compatible with the pulse width for the maximum gain of approximately 420. The amplified and filtered signal was then fed into the high-speed ADC module (ADS42B49, Texas Instruments). It converted analog voltage to 14 bit parallel discrete digital data at a 100 MHz sampling rate. An FPGA module acquired the digital data and transferred the average of 1000 frames at 1 Hz to the computer via a USB port, continuously. Averaging processes were performed by summing each frame point by point and then divided by the total number of frames. Each frame had 4096 sampled data points with a corresponding data point interval of 10 ns. A signal extraction algorithm was developed in Labview platform, running in the computer. Second averaging was done in the algorithm. The number of averaging frame was selected by the user. When detecting low power optical signals, amplification of the standard output with band pass filtering was required to provide sufficient gain. To read out the SiPM from the standard output, the photocurrent generated on the detection of photons was first converted to the voltage by 50 Ω load resistor and then is amplified by using a voltage amplifier as depicted in Figure 4. LMH6624 is ultra-low noise op-amp with 1.5 GHz gain bandwidth product. The cut off frequency of the amplifier circuit was designed to be at 80 MHz as to be compatible with the pulse width for the maximum gain of approximately 420. The amplified and filtered signal was then fed into the high-speed ADC module (ADS42B49, Texas Instruments). It converted analog voltage to 14 bit parallel discrete digital data at a 100 MHz sampling rate. An FPGA module acquired the digital data and transferred the average of 1000 frames at 1 Hz to the computer via a USB port, continuously. Averaging processes were performed by summing each frame point by point and then divided by the total number of frames. Each frame had 4096 sampled data points with a corresponding data point interval of 10 ns. A signal extraction algorithm was developed in Labview platform, running in the computer. Second averaging was done in the algorithm. The number of averaging frame was selected by the user.
Signal Extraction Algorithms
There are many noise reduction and signal extraction approaches reported in the literature. Signal accumulation technique [36] based on the assumption of zero mean random noise is widely used for noise reduction Coherent averaging, constant false alarm rate, wavelet and adaptive filters are also the most common methods. Since the signal is embedded in noise, coherent averaging has to be applied to obtain a meaningful signal [18]. When the laser power is very low, averaging should be done in multiples of 1000 depending on the distance. During the outdoor testing, the performance of our LRF, it has been observed that averaging process of up to 5000 frames is beneficial for noise reduction. At this level, the averaging process can be seen in Figure 5, where the noisy signal provides a Gaussian distribution.
Gaussian random noise signal with 4096 data point as to be compatible with an experimentally acquired signal. As known, the SNR of that noise is inversely proportional to the logarithmic of the variance of that signal. Therefore, we generate a noise signal whose SNR in linear scale (not dB) runs from 0 to 4.5 with an interval of 0.5, then interpolation is performed to obtain Figure 7. Here, we generate 1000 random different noise signals for each SNR value. For instance, we have 1000 different noise signal with an SNR of 3 (in linear scale). Second, we put a deformed square like signal representing the returning pulse somewhere inside the 4096 data point. The place of this artificially created signal in the data actually corresponds to the distance of 2000 m. Here, we have an artificial data signal which contains signal and noise with a known SNR. Next, this signal (XNx1 in Figure 5) goes into the algorithm. After the algorithm runs with this signal, the place of the filtered signal can be determined. Finally, threshold level based on the chosen probability of false alarm (Pfa = 10 −7 ) can be easily calculated by the computed standard deviation of the filtered signal as given in the equation below [39]. The distance can be determined by comparing the signal level with the threshold if the signal height is larger than the threshold. If the computed distance is correct with our previously defined distance, then this corresponds to the true case or wrong case if otherwise. In the case that the signal height is smaller than the threshold, this can be evaluated as a missed case. The Figure 7 shows the simulation result in terms of how effectively the algorithm runs. For instance, if the SNR is above 3 This situation provides flexibility in determining our signal extraction method. Since the averaging process takes a long time (1 s is required for 1000 frames), signal extraction should be started as soon as the data are acquired. The shape and pulse width of the detected pulse varies depending on the distance and attenuation rate. In addition, the detected signals are accompanied by the noises of all kind which can be classified into two different sources, optical such as background IR radiation, and electronic such as the noise of amplifiers. The SiPM itself also contributes to noise by means of dark current and excess noise. In the near-IR the excess noise of SiPMs appreciably increases even with low background noise [37]. For this reason, the use of the statistical method was preferred.
The Wiener-Hopf filter is the most popular statistical-based adaptive filter [38]. Figure 6 shows the basic outline of this filter which consists of averaging process, determining Wiener-Hopf filter coefficients according to the appearance of noise signal, filtering and the decision steps. The most challenging stage in Wiener filter application is determining the desired signal. In the averaging stage, coherent pulse integration was performed over the measured data signal (shown as X Nx1 ) which comes as an average of 1000 data. Here, we can choose any integer number to be averaged so, e.g., if we choose 5, we obtain data which is the average of the 5000 data frame. After normalization and zeroing the negative values, the signal (shown as R Nx1 ) enters the Wiener-Hopf process. Using the Wiener-Hopf equation, it is possible to extract the Wiener coefficients according to our desired signal (D Nx1 ) properties such as their shapes and positions from the noisy signal. The designed low-pass filter with these coefficients specifically belongs to both the noisy signal and desired signal. Therefore, these coefficients (W Nx1 ) need to be recomputed after each measurement. The number of coefficients (M) is also of great importance in terms of computational time and effectiveness of the filtering, as well. Therefore, they need to be optimized and this is done by trial and error. (linear, not dB), the probability of finding the true distance is 90%. This algorithm is implemented in our real experimental data to find the target distance, and they are shown in Figures 8-10. Figure 6. Algorithm used to extract the signal buried in noise. Figure 6. Algorithm used to extract the signal buried in noise.
The data acquired (X Nx1 ) contains 4096 points and data interval corresponds to 10 ns duration. This corresponds to the maximum distance that can be measured is 6144 m. D Nx1 is the filtered-out desired signal vector that contains 4096 data points. It is actually defined as all zero except the pulse representing the signal which is composed of 12 data point corresponding to 120 ns when SNR is larger than 3.5. Naturally, this gives an uncertainty in the position of the target which is 18 m. This single desired pulse is the analogy of laser pulse and approximately normalized Gaussian. The next step is to find the position of the pulse. The position of the pulse in the desired signal is determined by the cross correlation of the designed desired signal at the beginning with acquired noisy signal. This position depends on the SNR of a noisy signal and is not a final position yet. The form of that desired signal is roughly defined as the corrected desired signal. At this stage, Wiener filtering is ready to use for processing roughly corrected desired signal with the acquired noisy signal. The Wiener-Hopf equation written below depends on the cross-correlation of the noisy signal with the desired signal and auto-correlation of noisy signal. As a result of this equation, we obtain number of fifty different filter coefficients. During this process the mean square error (MSE), which shows the degree of success, can be found using these computed coefficients. MSE (shown as J m in the algorithm) changes between 0 which corresponds to the best result and 1 corresponding to the worst case. After the first computed MSE, we search for 0 or lowest MSE value by sliding the beginning of the roughly corrected desired signal pulse one by one. This search continues both ways until we find the best MSE. In the code, the number of sliding is 200 both ways which is usually enough to find the best MSE. Now, we reconstruct the desired signal with the new one according to the search result. Then we obtain new 50 filter coefficients with these reconstructed desired signals and acquired noisy signals using Wiener-Hopf processing.
In the third stage, filtering is performed by convolving noisy signal with computed filter coefficients. After that the top of the filtered signal (Y Nx1 ) can be used to find the position of the target. Figure 7 shows the success of this algorithm and it was explained in detail as below.
Results and Discussion
The test environment was barren land and tests were conducted on a clear day with mild winds. To view the targets in a wide perspective, the device was positioned on a higher hill than the targets' positions. We pointed our LRF to three different targets at different distances. As reference, those distances were measured with a commercial long distance LRF of 1064 nm laser with 8 mj energy and resolution of ±5 m. Figures 8-10 show the average of raw data and the processed data which was obtained with our LRF with a picture of the target taken with a monocular mounted on the top of our LRF (see the Figure 2). Figure 8 shows the first target which has the size of 2 by 2 m of a black painted wooden plane and measured distance is 1840 m. The second target in Figure 9 is a solitary tree in the barren land and measured distance is 2940 m. Our third target in Figure 10 is the small hill in the ground with measured distance of 3385 m. Those distances are measured with our reference laser rangefinder. Blue colors are the averaged raw data and the red colors are the processed data of the blue one using the algorithm shown in Figure 5. Although any number of averaging could be chosen, the number of averaged data in Figure 8 is 2000 and in Figures 9 and 10 4000.
For all cases, IFOV corresponding to those distances and the size of the laser spot are larger than the size of the target. This causes reduced SNR due to incoming unwanted radiation.
As the averaging increases, signal becomes more visible as the SNR increases with square root of N. Calculated SNR of raw data for Figures 8-10 In order to test the power of the algorithm above which is based on the Wiener-Hopf method, we run a Monte Carlo simulation and it is explained as follows. First, we generate Gaussian random noise signal with 4096 data point as to be compatible with an experimentally acquired signal. As known, the SNR of that noise is inversely proportional to the logarithmic of the variance of that signal. Therefore, we generate a noise signal whose SNR in linear scale (not dB) runs from 0 to 4.5 with an interval of 0.5, then interpolation is performed to obtain Figure 7. Here, we generate 1000 random different noise signals for each SNR value. For instance, we have 1000 different noise signal with an SNR of 3 (in linear scale). Second, we put a deformed square like signal representing the returning pulse somewhere inside the 4096 data point. The place of this artificially created signal in the data actually corresponds to the distance of 2000 m. Here, we have an artificial data signal which contains signal and noise with a known SNR. Next, this signal (X Nx1 in Figure 5) goes into the algorithm. After the algorithm runs with this signal, the place of the filtered signal can be determined. Finally, threshold level based on the chosen probability of false alarm (Pfa = 10 −7 ) can be easily calculated by the computed standard deviation of the filtered signal as given in the equation below [39].
V th = std(signal) * (−2 * ln(P f a). The distance can be determined by comparing the signal level with the threshold if the signal height is larger than the threshold. If the computed distance is correct with our previously defined distance, then this corresponds to the true case or wrong case if otherwise. In the case that the signal height is smaller than the threshold, this can be evaluated as a missed case. The Figure 7 shows the simulation result in terms of how effectively the algorithm runs. For instance, if the SNR is above 3 (linear, not dB), the probability of finding the true distance is 90%. This algorithm is implemented in our real experimental data to find the target distance, and they are shown in Figures 8-10. . Average raw data (top) and processed data (bottom). The range found with our own LRF is 2952 m. The number of averaged raw data frame, N is 4000. Figure 9. Average raw data (top) and processed data (bottom). The range found with our own LRF is 2952 m. The number of averaged raw data frame, N is 4000. Figure 10. Average raw data (top) and processed data (bottom). The range found with our own LRF is 3418 m away from the LRF. The number of averaged raw data frame, N is 4000.
Conclusions
A portable long-range laser rangefinder performance was investigated based on commercially available silicon photomultipliers (SiPM) with multi-pixel architecture as the detector for time-of-flight (ToF) measurements. Experimental results based on our own prototype show that SiPMs along with low-power pulsed laser diode yield promise long-range LRF performance owing to their exceptional properties such as high sensitivity, multi-pixel architectures and relatively low-voltage operation. We achieved a longdetection range over 3.5 km by employing a relatively low power laser with a pulse energy of a few µj at 0.905 µm and 3 dB enhancement in SNR by the implemented signal extraction algorithm based on Wiener filtering. Our measurement resolution was not good because of using a 100 ns long laser pulse which corresponds to the uncertainty of 30 m. Although a LRF using a time-to-digital converter has better resolution, our uncertainty can be reduced if SNR is increased. In order to increase our measurement sensitivity, we need to have better SNR than those obtained. One way of doing this is to use a pulse coding scheme when sending laser light. Since we have implemented FPGA to control everything, this will be our future plan. Improvement can also be achieved by using proper optical design in the beam shaping of the laser output and also in the receiver FOV. Although SiPM could be vulnerable to stray light which results as an uncorrelated noise added to its intrinsic primary noise (related to dark count rate), our tests show that SiPM along with optimized optics and digital filtering promise to realize low-power and lowcost practical long-range LRF and LiDAR applications.
Results and Discussion
The test environment was barren land and tests were conducted on a clear day with mild winds. To view the targets in a wide perspective, the device was positioned on a higher hill than the targets' positions. We pointed our LRF to three different targets at different distances. As reference, those distances were measured with a commercial long distance LRF of 1064 nm laser with 8 mj energy and resolution of ±5 m. Figures 8-10 show the average of raw data and the processed data which was obtained with our LRF with a picture of the target taken with a monocular mounted on the top of our LRF (see the Figure 2). Figure 8 shows the first target which has the size of 2 by 2 m of a black painted wooden plane and measured distance is 1840 m. The second target in Figure 9 is a solitary tree in the barren land and measured distance is 2940 m. Our third target in Figure 10 is the small hill in the ground with measured distance of 3385 m. Those distances are measured with our reference laser rangefinder. Blue colors are the averaged raw data and the red colors are the processed data of the blue one using the algorithm shown in Figure 5. Although any number of averaging could be chosen, the number of averaged data in Figure 8 is 2000 and in Figures 9 and 10 is 4000.
For all cases, IFOV corresponding to those distances and the size of the laser spot are larger than the size of the target. This causes reduced SNR due to incoming unwanted radiation.
As the averaging increases, signal becomes more visible as the SNR increases with square root of N. Calculated SNR of raw data for Figures 8-10 are 3.7 dB, 4.2 dB and 4.3 dB, respectively, then after signal processing, SNRs become 7.7, 7.3 and 7.7 decibels, respectively. Using the Wiener filtering algorithm, 3 dB enhancement in SNR for Figure 8 and 2.5 dB enhancement in SNR for other figures are obtained. Our LRF data after the algorithm correctly found the position of the signal with an average error of approximately 30 m. This can be due to the delay which can be corrected by the proper calibration.
Conclusions
A portable long-range laser rangefinder performance was investigated based on commercially available silicon photomultipliers (SiPM) with multi-pixel architecture as the detector for time-of-flight (ToF) measurements. Experimental results based on our own prototype show that SiPMs along with low-power pulsed laser diode yield promise longrange LRF performance owing to their exceptional properties such as high sensitivity, multipixel architectures and relatively low-voltage operation. We achieved a long-detection range over 3.5 km by employing a relatively low power laser with a pulse energy of a few µj at 0.905 µm and 3 dB enhancement in SNR by the implemented signal extraction algorithm based on Wiener filtering. Our measurement resolution was not good because of using a 100 ns long laser pulse which corresponds to the uncertainty of 30 m. Although a LRF using a time-to-digital converter has better resolution, our uncertainty can be reduced if SNR is increased. In order to increase our measurement sensitivity, we need to have better SNR than those obtained. One way of doing this is to use a pulse coding scheme when sending laser light. Since we have implemented FPGA to control everything, this will be our future plan. Improvement can also be achieved by using proper optical design in the beam shaping of the laser output and also in the receiver FOV. Although SiPM could be vulnerable to stray light which results as an uncorrelated noise added to its intrinsic primary noise (related to dark count rate), our tests show that SiPM along with optimized optics and digital filtering promise to realize low-power and low-cost practical long-range LRF and LiDAR applications. | 9,272.2 | 2021-01-04T00:00:00.000 | [
"Physics"
] |
On orbital angular momentum conservation in Brillouin light scattering within a ferromagnetic sphere
Magnetostatic modes supported by a ferromagnetic sphere have been known as the Walker modes, each of which possesses an orbital angular momentum as well as a spin angular momentum along a static magnetic field. The Walker modes with non-zero orbital angular momenta exhibit topologically non-trivial spin textures, which we call \textit{magnetic quasi-vortices}. Photons in optical whispering gallery modes supported by a dielectric sphere possess orbital and spin angular momenta forming \textit{optical vortices}. Within a ferromagnetic, as well as dielectric, sphere, two forms of vortices interact in the process of Brillouin light scattering. We argue that in the scattering there is a selection rule that dictates the exchange of orbital angular momenta between the vortices. The selection rule is shown to be responsible for the experimentally observed nonreciprocal Brillouin light scattering.
I. INTRODUCTION
The coupling between electron spins in solids and light is in general very weak. This is because the coupling is inevitably mediated by the orbital degree of the electrons and is realized through spin-orbit interaction for orbits and spins and electric-dipole interaction for orbits and light, respectively 1 . Although it is possible to coherently (non-thermally) manipulate collective excitations of spins in spin-ordered materials by means of ultrafast optics, where the electric field density of an optical pulse is high both temporally and spatially [2][3][4][5] , an attempt to realize coherent optical manipulation of magnons in the quantum regime is hindered by the weakness of the spin-light coupling 6 . Given the encouraging development of circuit quantum magnonics, where microwave photons and magnons are strongly coupled, enabling a coherent energy exchange at the single-quantum level 7-9 , the similar energy exchange between optical photons and magnons has been anticipated.
To overcome the weakness of the spin-light interaction, cavity optomagnonics has been investigated [10][11][12][13][14][15][16] . In cavity optomagnonics, the density of states of optical modes are engineered with an optical cavity to enhance spinlight interaction. In particular, spheres of ferromagnetic insulators supporting whispering gallery modes (WGMs) for photons and a spatially uniform magnetostatic mode, called the Kittel mode, for magnons are used as a platform of the cavity optomagnonics. With spheres made of typical ferromagnetic insulator, yttrium iron garnet (YIG), the pronounced sideband asymmetry [11][12][13] , the nonreciprocity 11 , and the resonant enhancement 12,13 of magnon-induced Brillouin scattering have been demonstrated.
In this context, it is interesting to examine the behavior of magnetostatic modes beyond the simplest Kittel mode. The magnetostatic modes residing in a ferromagnetic sphere under a uniform static magnetic field are known as the Walker modes 17,18 . They exhibit, in general, topologically non-trivial spin textures about the axis along the applied magnetic field and might be called magnetic quasi-vortices. The magnetic quasi-vortices can be characterized by their orbital angular momenta along the symmetry axis 19,20 . Photons in optical whispering gallery modes possess not only spin angular momenta but also orbital angular momenta, too, which echoes the concept known as optical vortices 21 . Within the ferromagnetic sphere, the optical vortices can interact with the magnetic quasi-vortices in the course of the Brillouin light scattering. The total orbital angular momentum is then expected to be conserved as long as the symmetry axis of the WGMs coincides with that of the Walker modes, imposing a selection rule on the Brillouin scattering processes.
In this article, the Brillouin scattering hosted in a ferromagnetic sphere is theoretically investigated putting a special emphasis on the orbital angular momentum exchange between the optical vortices and the magnetic quasi-vortices. We establish a selection rule imposed by the orbital angular momentum conservation for the Brillouin scattering hosted in a ferromagnetic sphere. The experimentally observed Brillouin scattering by various Walker modes reported in the accompanying paper 22 , which reveals that the scattering is either nonreciprocal or reciprocal depending on the orbital angular momentum of the magnetic quasi-vortices, is then analyzed with the theory developed here and found to be explained well. The result would provide a new area for chiral quantum optics 23 and topological photonics 24,25 based on optical vortices and magnetic quasi-vortices.
II. ORBITAL ANGULAR MOMENTA
The schematics of the cavity optomagnonic system we investigate is shown in Fig. 1, where the Walker mode Here the distribution of the transverse magnetization of the (4, 0, 1) Walker mode on the equatorial plane is shown as an example. The Walker modes and the WGMs are assumed to share the symmetry axis (z-axis) along a static magnetic field H. and the WGMs share the symmetry axis (z-axis) along a static magnetic field H. The Walker modes and the WGMs generally exhibit nonzero orbital angular momenta. In this section we analyze the orbital angular momenta of these modes.
A. Orbital angular momenta of Walker modes
The orbital angular momentum density l (mmag) z of a magnon along the static magnetic field H ( z-axis) can be deduced from the dependence of the transverse magnetizations, M x (t) and M y (t), on the azimuthal angle φ as 19,20 where M ⊥ (t) = M 2 x (t) + M 2 y (t). As for the Walker mode with the index (n, m mag , r) 17,18 the orbital angular momentum L (mmag) z can be given by the volume integral z = 0, and L (0) z = 1, corresponding to the winding numbers of the respective spin textures of the Walker modes. Note that the magnetic field is applied parallel to z axis. of l (mmag) z over the entire sphere and depends on the index m mag , that is, While the Kittel mode [(1, 1, 0) mode] has no orbital angular momentum, L (1) z = 0, (4, 0, 1) and (3,1, 1) modes, for instance, have L (0) z ≈ 1 and L (−1) z ≈ 2, respectively. The approximation in the last line of Eq. (2) is due to the dipolar interaction with broken axial symmetry. As the applied static magnetic field H approaches infinity, the Zeeman energy becomes dominant over the dipole interaction energy, and thus "≈" becomes "=" in Eq. (2). Note also that for the Walker modes with n = m mag and n = m mag + 1, Eq. (2) is exact. We call the Walker modes with non-zero L (mmag) z as magnetic quasi-vortices. The prefix "quasi-" emphasizes the fact that the orbital angular momentum we defined in Eq. (2) is the approximated one and the fact that magnons are quasi-particle with finite lifetime. Figure 2 shows the spatial distributions of the transverse magnetizations for the representative Walker modes (1, 1, 0), (3,1, 1), (3, 1, 1), and (4, 0, 1). The modes having non-zero L z [e.g., (3,1, 1) and (4, 0, 1) in Fig. 2] exhibit the topologically non-trivial spin textures. Note that the orbital angular momentum L z here plays a similar role as the winding number or the skyrmion number in other literature 26 .
B. Orbital angular momentum of WGMs
The electric field of the WGM in an axially symmetric dielectric material has been extensively studied 27 . Now, for simplicity, we focus on the azimuthal mode index m which characterizes the azimuthal profile of the electric field of the fundamental WGM. In the spherical ba- the electric field of the WGMs of the counterclockwise (CCW) orbit can be written as where E (TE) and E (TM) correspond to the transverse electric (TE) and the transverse magnetic (TM) WGMs, respectively, and φ is the azimuthal angle. Note that the time-dependent electric field as a whole is written as For the clockwise (CW) orbit, the electric fieldsĒ (TE) andĒ (TM) can be written as E i (E o ) in Eqs. (4) and (7) shall be called the inner (outer ) component of the TM mode. To see this, Fig. 3(a) shows the radial intensity distributions of two components |E i | 2 and |E o | 2 (magenta and green dotted lines) along with the intensity profiles of the transverse for the TM electric field of a WGM. We can see that |E i | 2 has its maximum in the inner part of the resonator compared to |E o | 2 . The shift of the "centers of gravity" of the two components, |E i | 2 and |E o | 2 is a manifestation of the spin-Hall effect of light 28,29 , which originates from the spin-orbit coupling of light 30 .
From the dependence of the electric field on φ, the orbital angular momentum L z of the WGM, that is, the optical vortex 21 , can be straightforwardly deduced. First, let us consider the CCW orbit. As for the TE mode with the azimuthal mode index m = m TE , since there is no spin angular momentum, the orbital angular momentum is given by As for the TM mode with m = m TM , however, the spinorbit coupling of light has to be taken into account 30 . For the CW orbit, the similar argument leads us to the following: and the total angular momentum J (CW,TM,mTM) = −m TM is again well-defined. Note that for the CW orbit the outer (inner) component of TM mode is associated with σ + (σ − ), that is opposite to that for the CCW orbit. The orbital angular momenta of the WGMs can be visualized by sketching the trajectory of the head of the polarization vector of the electric fields [Fig 3(b)]. When the mode index is 10, the orbital angular momentum reads 10, 9 and 11 for the TE, inner TM, and outer TM components, respectively.
A. Magnetic Quasi-Vortices-Optical Vortices Interaction
Let us now see that the total orbital angular momentum is conserved in the Brillouin scattering process. The thorough treatment of the Brillouin scattering by magnons in WGMs can be found in Ref. [16]. In the following, we emphasize the role of orbital angular momenta in the Brillouin scattering process. The interaction Hamiltonian representing the Brillouin scattering is where the integrand E is the energy flux density and the integral runs over infinity in time t and the volume V of the WGM, E 1 (t) = E 1 e −iω1t and E * 2 (t) = E * 2 e iω2t are the input and scattered electric fields of WGMs, respectively. Here, the permittivity tensorǫ can be written in the Cartesian basis as 31 The interaction between the magnetic quasi-vortices and optical vortices in the course of the Brillouin scattering process can be understood best in the spherical basis. In this basis the permittivity tensor can be written as Here the term ǫ 0 ǫ r M 0 in Eq. (15) has been neglected. Henceforth, the term f M s M z in Eq. (16) is also ignored for it is independent of time and give no contribution to the Brillouin scattering. Here ω m /2π is the resonant frequency of the concerned Walker mode with the azimuthal mode index of m mag .
In the spherical basis the time-dependent transverse magnetization is given by Here note that the creation (annihilation) of a magnon decreases (increases) the spin angular momentum. As we shall show, the Brillouin scattering stems from the term with M + (M − ) representing the Stokes-scattering (anti-Stokes-scattering) associated with the creation (annihilation) of a magnon. Since the TE-to-TM or TM-to-TE transition process changes the spin angular momentum of magnon, these transitions give nonzero contributions to the Brillouin scattering given the conservation of the spin angular momentum. We shall see this more clearly in Sec. III B.
B. Selection rules
Since the interaction depends on the direction of the input field and its polarization, let us first suppose that the input field is the CW TE mode with mode index of m TE , that is, E 1 (t) = E (mTE) e −imTEφ e −iω1tê * 0 . In this case the Brillouin scattering results in producing photons in the CW TM mode as seen in the following. We can straightforwardly extend the argument to other cases, e.g., the TM mode input or the input to the CCW orbit.
With the CW TE mode as the input field, the energy flux density E in Eq. (14) reads where The first (second) term in the right-hand side of Eq. (18) represents the Stokes (anti-Stokes) scattering. The possibility of the scattered light being the CCW WGM is denied given the fact that we are concerned only with cases where L for the Stokes scattering and for the anti-Stokes scattering. Since the optical densities of states are modified in the presence of the WGMs, the probabilities of the scattering processes are affected by them, too. Furthermore, because of the axial symmetry of the system, the conservation of the total angular momentum is expected. The designated WGM of the Brillouin scattering can then be specified by the selection rule obtained by the conservation of the orbital angular momentum. To see this, we integrate E in Eq. (14) over the azimuthal angle φ as a part of the volume integral. From the first Stokes term in Eq. (18) As for the second anti-Stokes term in Eq. (18), the selection rule is and with Eqs. (2), (11), and (13), we have Next, let us briefly describe the results when the laser light is injected into the CCW-TE mode. The Stokes (anti-Stokes) scattering process gives the same conditions of the energy conservation, Eq.
that is, the same selection rule as Eq. (24). As for the Stokes scattering, represents the orbital angular momentum conservation, yielding that is, the same selection rule as Eq. (26). These selection rules regarding the orbital angular momentum are the main result of this paper. With the geometric birefringence 32-34 and densities of states of WGMs, these selection rules dictate the Brillouin light scattering by Walker-mode magnons hosted in a ferromagnetic sphere as shown below. In the next section we employ the selection rules to explain the experiment reported in the accompanying paper 22 , which reveals that the Walker-mode-induced Brillouin light scattering is either nonreciprocal or reciprocal depending on the orbital angular momentum of the magnon in the relevant Walker mode, that is, the magnetic quasi-vortex. | 3,318 | 2017-11-26T00:00:00.000 | [
"Physics"
] |
Field Theory of Dissipative Systems with Gapped Momentum States
We develop a field theory with dissipation based on a finite range of wave propagation and associated gapped momentum states in the wave spectrum. We analyze the properties of the Lagrangian and the Hamiltonian with two scalar fields in different representations and show how the new properties of the two-field Lagrangian are related to Keldysh-Schwinger formalism. The proposed theory is non-Hermitian and we discuss its properties related to $\mathcal{PT}$ symmetry. The calculated correlation functions show a decaying oscillatory behavior related to gapped momentum states. We corroborate this result using path integration. Interestingly, we find a new effect in the interaction potential which becomes oscillatory due to the lower momentum bound and discuss analogies with Friedel oscillations. Finally, we observe that the proposed field theory represents a departure from the harmonic paradigm and discuss the implications of our theory for the Lagrangian formulation of hydrodynamics.
The basic assumptions and results of statistical physics are related to introducing, and frequently exploiting, the concept of a closed or quasi-closed system or subsystem. This includes, for example, most of the central ideas of a statistical or thermal propagates. This approach draws on recent understanding of phonon propagation in liquids and associated dissipation of these phonons [21][22][23].
No dissipation takes place when a plane wave propagates in an ideal crystal where the wave is an eigenstate. However, a plane wave dissipates in systems with structural and dynamical disorder such as glasses, liquids or other systems with strong anharmonicities because its not an eigenstate in those systems [28] (see, e.g., Refs. [24][25][26][27] for recent field theory applications of related effects in amorphous and disordered systems).
We note that the overall system (liquid in our case) is conservative and does not lose or gain energy. Similarly, collective excitations in a disordered system such as glass or liquid, generally defined as eigenstates in that system, do not decay either [28]. (We note that calculating these excitations presents an exponentially complex problem because it involves a large number of strongly-coupled non-linear oscillators [21].) In our consideration, a decaying object that loses energy is the harmonic plane wave (phonon) propagating in a disordered system where its not an eigenstate. Indeed, plane waves constantly evolve in a disordered system, e.g. decay into other waves and emerge anew due to thermal fluctuations. Accordingly, an open system in our consideration is the harmonic collective excitation, the plane wave, operating in a system where its not an eigenstate.
An important effect related to wave dissipation is the emergence of the gap in k-or momentum space in the transverse wave spectrum, with the accompanying decrease of the wave energy due to dissipation [21][22][23]. This gap (a) shrinks the range of k-vectors where phonons can propagate and (b) reduces the energy of the remaining propagating phonons.
It has been realized that in addition to liquids, gapped momentum states (GMS) emerge in a surprising variety of areas [29], including strongly-coupled plasma, electromagnetic waves, non-linear Sine-Gordon model, relativistic hydrodynamics and holographic models.
The field theory developed here describes dissipation on the basis of GMS. GMS is a well-specified effect and is naturally suited for describing the dissipation in a field theory because the field theory is deeply rooted in the harmonic paradigm involving the propagation of plane waves [30]. Despite its specificity, this effect and the proposed field theory are generally applicable to a wide range of physical phenomena in interacting systems where collective excitations propagate.
In the next section II, we briefly review the emergence of gapped momentum states in Maxwell-Frenkel theory and their properties. We subsequently recall the two-field Lagrangian which gives rise to gapped momentum states and expand on different formulations, solutions and properties of this Lagrangian in section III. This includes the discussion of the Hamiltonian and energy and their lower bounds in different regimes. We also show how two new properties of the two-field Lagrangian are related to results from Keldysh-Schwinger formalism in section III C. In the following section IV, we address the non-Hermiticity of the proposed Lagrangian and Hamiltonian operators as well as their PT symmetry and its breaking. We calculate the correlation functions in section V and find that they show a decayed oscillatory behavior, with frequency and decay related to GMS. We corroborate this result using path integration. In section VI, we observe a new effect: the oscillatory behavior of the interaction potential related to the lower momentum cutoff set by dissipation and draw the analogy of this effect with Friedel oscillations. Finally, we discuss other implications of the proposed field theory, including the ways in which it departs from the harmonic paradigm (section VII A) and its implications for the field-theoretical description of hydrodynamics (section VII B).
II. DISSIPATION AND GAPPED MOMENTUM STATES IN THE MAXWELL-FRENKEL THEORY
We start with recalling how liquid transverse modes develop gapped momentum states (GMS) and how this effect can be represented by a Lagrangian. We note that a firstprinciples description of liquids is exponentially complex and is not tractable because it involves a large number of coupled non-linear oscillators [21]. At the same time, liquids have no simplifying small parameters as in gases and solids [1]. However, progress in understanding liquid modes can be made by using a non-perturbative approach to liquids pioneered by Maxwell and developed later by Frenkel. This program involves the Maxwell interpolation: where s is shear strain, η is viscosity, G is shear modulus and P is shear stress. Eq. (1) reflects Maxwell's proposal [31] that shear response in a liquid is the sum of viscous and elastic responses given by the first and second right-hand side . Eq. (1) serves as the basis of liquid viscoelasticity.
Frenkel proposed [32] to represent the Maxwell interpolation (1) by introducing the operator A = 1 + τ d dt and write Eq. (1) as ds dt = 1 η AP. Here, τ is the Maxwell relaxation time η G . Frenkel's theory has identified τ with the average time between consecutive molecular jumps in the liquid [32]. This has become an accepted view [33]. Frenkel's next idea was to generalize η to account for liquid's short-time elasticity as 1 η → 1 η 1 + τ d dt and use this η in the Navier-Stokes equation where v is velocity, ρ is density and d dt = ∂ ∂t + v∇. We have carried this idea forward [21] and, considering small v, wrote: where v is the velocity component perpendicular to x, η = Gτ = ρc 2 τ and c is the shear wave velocity. In contrast to the Navier-Stokes equations, Eq.(2) contains the second time derivative and hence gives propagating waves. We solved Eq. (2) in Ref. [21]: seeking the solution as v = v 0 exp (i(kx − ωt)) gives with the complex solutions where The absence of dissipation in (2) corresponds to setting τ → ∞ in (6) and to an infinite range of propagation of the plane shear wave, as in the a ideal ordered crystal. A finite τ implies dissipation of the wave in a sense that it acquires a finite propagation range. Indeed, the dissipation takes place over time approximately equal to τ according to (5). τ sets the physical time scale during which we consider the dissipation process: if an observation of an injected shear wave starts at t = 0, time t ≈ τ is the end of the process because over this time the wave amplitude and energy appreciably reduce.
An important property is the emergence of the gap in k-space or GMS: in order for ω in (6) to be real, k > k g should hold, where increases with temperature because τ decreases. The value of k-gap (7) is related to the finite propagation range of transverse waves. Indeed, if τ is the time during which a shear stress can exist in a liquid, the liquid elasticity length d el = cτ [34] gives the propagation range of the shear wave. A wave is well-defined only if the wavelength is smaller than the propagation range. This corresponds to k > 1 cτ , or approximately to k > k g with k g given by (7).
Recently, in Ref. [22], detailed evidence for GMS was presented on the basis of molecular dynamics simulations.
The GMS is interesting. Indeed, the two commonly discussed types of dispersion relations are either gapless as for photons and phonons, E = p (c = 1), or have the energy gap for massive particles, E = p 2 + m 2 , where the gap is along the Y-axis. On the other hand, (6) implies that the gap is in momentum space and along the X-axis, similar to the hypothesized tachyon particles with imaginary mass [35]. Fig.1 illustrates the different dispersion relations including the dispersion relation with the k-gap. The k-gap case displays a non-trivial imaginary part and the presence of a nonhydrodynamic mode with damping Im(ω) = −1/τ [18]. For small frequency and momentum, the dispersion relation of the lowest mode is purely diffusive and hydrodynamic.
How large can the gap in (7) get? In condensed matter systems and liquids in particular, k g is limited by the UV scale: the interatomic separation a and corresponding k point comparable to 1 a . This can be seen in (7) by using the shortest value of τ comparable to the Debye vibration period τ D . Using τ = τ D in (7) gives the maximal value of k g as 1 2a , where we used Top curve shows the dispersion relation for a particle with mass m. Middle curve shows gapless dispersion relation for a massless particle (photon) or a phonon in solids. Bottom curve shows the dispersion relation (6) with the gap in k-space, k g , illustrating the results of Ref. [22]. The k-gap case displays a non-trivial imaginary part (dashed lines) and the presence of a non-hydrodynamic mode with damping Im(ω) = −1/τ [18]. Below k g , the dispersion relation of the lowest hydrodynamic mode is purely diffusive. a = cτ D . This corresponds to the shortest wavelength in the system to be 2a, as expected on general grounds. We note that τ in liquids depends on pressure and temperature. Hence the condition τ = τ D giving the maximal k g gives a well-defined line on the phase diagram. This line is the Frenkel line (FL) separating the combined oscillatory and diffusive molecular motion from purely diffusive motion [21,36,37]. The FL corresponds to qualitative changes of system properties in liquids and supercritical fluids and is ultimately related to the UV cutoff. Close to the FL, where the k-gap is maximal, liquids acquire an interesting universality of properties: for example, the liquid viscosity becomes minimal and represents a universal quantum property governed by fundamental physical constants only [38] which seems at work even in exotic states of matter such as the quark gluon plasma [39].
Differently from liquids, k g increases without bound in scalefree field theories discussed below due to the absence of an UV regulator. In these theories, the UV cutoff and the Frenkel line do not exist.
III. TWO-FIELD LAGRANGIAN, ITS SOLUTIONS AND PROPERTIES
A. Two-field Lagrangian An important question from the field-theoretical perspective is what Lagrangian gives the spectrum given by Eq. (6) and the associated GMS? The challenge is to represent the viscous term ∝ τ −1 in (2) in the Lagrangian. The viscous energy can be written as the work W done to move the liquid. If s is the strain, W ∝ F s, where F is the viscous force F ∝ η ds dt . = ∂φ ∂t . Another way to see this is note that the viscous term is simply a total derivative, φ dφ dt ∝ d dt φ 2 . To circumvent this problem, we proposed to operate in terms of two fields φ 1 and φ 2 [23,40]. We note that a two-coordinate description of a localised damped harmonic oscillator was discussed earlier [41,42]. Two fields also emerge in the Keldysh-Schwinger approach to dissipative effects, describing an open system of interest and its environment (bath) [29].
We constructed the dissipative term as the antisymmetric combination of φ dφ dt [23], namely as Taking into consideration this new term, the Lagrangian density involving two scalar fields φ 1 and φ 2 and the dissipative term (8) reads [23]: where we consider only one spatial direction for simplicity. The scalar fields φ 1 , φ 2 are real, and we verify the existence of real solutions later in this section. In real space, hermiticity or self-adjointness coincide with the invariance under the transposition operator since complex conjugation acts trivially. Defining the vector Φ ≡ (φ 1 , φ 2 ), we can write down the Lagrangian as: where T indicates the transposition operation. Then, the Lagrangian in Eq. 9 is not Hermitian in the sense that L T L. However, we will see later than the Lagrangian (9) is PT symmetric.
Applying the Euler-Lagrange equations to (9) gives two decoupled equations for φ 1 and φ 2 : where the equation for φ 1 is the same as (2). These equations have different solutions depending on whether k is above or below k g = 1 2cτ . For k > k g , the physically relevant real solutions of (11) are: where ω R = c 2 k 2 − 1 4τ 2 (13) Figure 2. The solutions for φ 1,2 (t,x) for k > k g . In the time direction there is a wave propagating together with an exponential decay for the φ 1 field and an exponential increase for the φ 2 field.
has the form of (6) predicting the GMS. Without the loss of generality, we can take the constants φ 1 =φ 2 = 1 since the equations are decoupled and linear in the fields. The solutions are shown in Fig. 2.
In the fluid regime 1 , k < k g , where no transverse modes propagate, the real solutions are: These solutions are not periodic in time as illustrated in Fig.3 but respectively decay and grow exponentially.
The time dependence of φ 1 and φ 2 in (12) can be interpreted as energy exchange between waves φ 1 and φ 2 : φ 1 and φ 2 appreciably decrease and grow over time τ, respectively. This Figure 3. The solutions for φ 1,2 (t,x) for k < k g . In the time direction there is no wave propagating but a simple exponential decay for the φ 1 field and an exponential increase for the φ 2 field. process is similar to the phonon scattering in crystals due to defects or anharmonicity where a plane-wave phonon (φ 1 ) decays into other phonons (represented by φ 2 ) and acquires a finite lifetime τ as a result. After the next time interval τ, the newly created phonon φ 2 decays itself, transferring the energy to other phonons, and the process repeats. The time scale over which we consider and describe the dissipation process in (12) is τ because the phonon with the k-gap dissipates after time comparable to τ (5).
This energy exchange can be represented by a generic approach to dissipation where the Lagrangian is written as [9]: The interaction term L [1,2] in (16) represents dissipation as the energy transfer from the degrees of freedom "1" to the degrees of freedom "2". We keep track of the degrees of freedom "1" related to dissipation but not the degrees of freedom "2", either because they are not of interest or are too complicated to account for. L int [1,2] couples the two sectors and represent the energy exchange between them.
In the language of theories studying the open systems and non-Hermitian Hamiltonians (see next section), φ 1 and φ 2 in (12) are analogous to the "loss" and "gain" subsystems of a composite system [3], although in our case these subsystems are propagating waves suited for field-theoretical description rather than localised oscillators discussed earlier.
The parameters τ and k in the dispersion relation (13) are subject to UV cutoffs in condensed matter phases, including in liquids where GMS emerge as discussed in the previous section. The high-temperature limit of τ is given by the shortest time scale in the system on the order of Debye vibration period τ D . When τ → τ D , k g = 1 2cτ → 1 2cτ D ≈ 1 a , or k D , where a is the inter-particle separation and k D is Debye wavevector. Therefore, the limits of k and τ at the UV cutoff are The limits (17) apply to the field theory describing condensed matter phases with a well-defined UV regulator, e.g. lattice spacing. More generally, the field theory discussed here may involve UV cutoffs of different nature depending on the physical object it describes.
B. An alternative formulation of the two-field Lagrangian In this section, we further elaborate on the origin of the dissipative Lagrangian discussed in the previous section. This will enable us to make a correspondence with the effective Lagrangian emerging in the Keldysh-Schwinger formalism discussed in the next section.
The first two cross terms in our initial Lagrangian (9) follow from the standard scalar field theory using the standard transformation: In terms of the fields ζ 1 and ζ 2 , the Lagrangian (9) reads We note that in terms of ζ fields, the non-hermiticity of Lagrangian (20) has a more standard meaning of L † ζ L ζ . Applying the Euler-Lagrange equations to (23) gives two coupled equations for ζ 1 and ζ 2 as These equations can be de-coupled by using the same transformation (19): using (19) in (21) gives the system of two equations for φ 1 and φ 2 . Adding and subtracting these equations gives (11). The solutions of (20) and (21) are generally complex. Representing these fields in the Lagrangian can be done using complex field conjugates [46,47]. However, this introduces an ambiguity in the equations of motion derived by applying the Euler-Lagrange equations to the Lagrangian. The ambiguity can be removed by selecting the solutions related by PT symmetry [46,47] (see next section).
We note that taking real solutions φ 1 and φ 2 in (12), together with (19), implies that ζ 1 is real and ζ 2 is purely imaginary. In order to have a clearer formulation of our field theory, we continue our Lagrangian formulation in terms of real fields, similarly to (12) and define new real fields ψ 1 and ψ 2 as ζ 1 = ψ 1 and ζ 2 = −iψ 2 . Then, (19) becomes where all the fields involved in this transformation are real valued.
In the next section, we will see that this transformation is the same as the "Keldysh rotation" used in the Keldysh-Schwinger formalism.
In terms of the fields ψ, the Lagrangian (9) reads The Hamiltonian based on (9) or (23) is non-Hermitian due to the presence of the anti-symmetric last term ∼ 1/τ, but it is PT invariant (see Ref. [48] for a similar case). As compared to the free-field part of (20), the free term for ψ 2 in (23), − ∂ψ 2 ∂t 2 + c 2 ∂ψ 2 ∂x 2 , has the opposite sign. In the next section, we show that this is related to the result following from Keldysh-Schwinger formalism. The opposite sign is not an issue from the point of view of system's energy because the kinetic matrix is not diagonal due to the coupling ∼ 1 τ . As explicitly shown in the next section, the system is stable and the Hamiltonian has a well-defined lower bound.
Using (12) and (22), the solutions in terms of ψ 1 and ψ 2 for k > k g are For k < k g , the solutions are In the limit τ → ∞, solutions (12) for k > k g and (15) for k < k g give φ 1 = φ 2 , and the Lagrangian (9) becomes the free-field Lagrangian for the single field φ 1 = φ 2 . Moreover, φ 1 = φ 2 implies ψ 2 = 0 according to (22), and the Lagrangian (20) similarly becomes the free-field Lagrangian for the single field ψ 1 . Hence, in the absence of dissipation, we have This is an important point for two reasons. First, it shows that the number of degrees of freedom is halved in the absence of dissipation at τ = ∞. The meaning of the additional degree of freedom will become clear in the Keldysh-Scwhinger formalism in section III C. Second, the remaining single degree of freedom is a plane wave with the dispersion relation ω = ck. This ensures that the system reduces to the canonical situation in the limit τ → ∞.
C. The Lagrangian from Keldysh-Schwinger formalism
In the previous sections, we discussed how describing dissipation necessitates a two-field Lagrangian. We have earlier noted that the Keldysh-Schwinger (KS) formalism similarly involves two fields, and that the Green function operator contains the first time derivative which can be related to GMS [29]. Here, we make a stronger and more specific assertion. We show that two new important features of our dissipative Lagrangian (23) and emerging GMS appear in the KS formalism: (a) the new dissipative term of the form (8), ψ 2 and (b) the opposite sign of the free-field term of ψ 2 in L ψ (third and fourth terms in (23)).
The description of non-equilibrium effective field theories involves the doubling of the degrees of freedom [7]. Let us consider the simple case of one scalar field, ψ 1 . The action of a dissipative system depends on the initial state of the system and, accordingly, on the choice of initial time. The averaging operation is not defined in this case and, as a consequence, the statistical theory can not be formulated. To get around this problem, the KS formalism uses the following approach: consider a copy of our system with the same transition amplitude and the field in the replica system ψ 2 . Recall that both fields are identical, hence ψ 1 (0)|ψ 2 (0) = 1. Using these two fields, we reverse (invert) time in the second system and close the integration contour at t = ∞. Then we can write the system's path integral as where ξ 1,2 are source terms associated with fields ψ 1,2 . Importantly, the term related to the copy ψ 2 has the opposite sign, meaning that it propagates backward along the Keldysh-Schwinger contour [7,8]. Therefore, we can interpret the field ψ 2 as the additional degree of freedom required to describe an open system and whose dynamics is reversed with respect to the arrow of time (see Fig. 4). The KS formalism involves introducing r,a variables (retarded/advanced), defined as: where variable a is related to the real field dynamics, and variable r related to dissipation and quantum fluctuations. This is the same transformation as (22) which we used earlier to find the relation between fields ψ and φ. By comparing the KS tranformation with (22), we see that φ 2 plays the role of ψ a which corresponds to dissipation. As we will later find, φ 2 φ 2 = 0. This implies unitarity of our field theory, ensured by the PT invariance of the action [49].
We now make this more precise and elaborate on the details. Let us consider an out-of-equilibrium system represented by a continuous field whose energy dissipates with time. We assume that at t = 0, the system is out of equilibrium and is in the state |Φ 0 . It evolves to its final state, Φ ∞ | with energy is E ∞ = 0. In order to describe the system's non-equilibrium dynamics, we use the KS technique [50]. We first write the transition probability from the initial state to the final one as follows: whereΦ is the field conjugated to Φ, τ is the characteristic time and the Lagrangian is given by For details of this derivation we refer the reader to Ref.
[29]. As discussed earlier, this probability depends on the initial state of the system and, accordingly, on the choice of the initial time. The averaging operation is not defined in this case and, as a consequence, the statistical theory can not be formulated. In order to get around this problem, the KS approach [50] introduces a copy of the system with the same transition probability. We denote the field in the initial system as Φ + and in the copy as Φ − . This is the same field, hence Φ − 0 , 0|Φ + 0 , 0 = 1. Using the two fields, we close the integration contour in point t = ∞ (see Fig. 4) and write After the Wick rotation t → it, we obtain Therefore, the effective Lagrangian of the theory is given by We now perform Keldysh rotation: which is the same transformation we used earlier (22), and find where we use the commutation relation for bosonic operators Settingφ 1 = φ 1 , we observe that (33) coincides with the dissipative Lagrangian we started with in (9) (up to a factor of 2 in front of τ).
It is remarkable that the dissipative Lagrangian (9) and, therefore, the gapped momentum states effect appear to be related to a mature technique such as Keldysh-Schwinger formalism. We note an important caveat of this relation. The KS formalism does not contain the relaxation time τ. Instead, the timescale in the KS approach is set by the Planck constant. We have introduced τ as the relaxation time of the system on top of the standard KS formulation [29], similarly to how τ is introduced in the Maxwell-Frenkel interpolation in (1)-(2), where it is assigned the meaning of the time between molecular rearrangement in the liquids [32]. In this sense, Lagrangian (31) is not a derivation of our dissipative Lagrangian (23) from the KS formalism. However, it backs up two new and important features of our dissipative Lagrangian (23). First, it contains the term of the form ∝ φ 1 ∂t . This is the same term (8) featuring in our Lagrangians (9) and (23) which is required to obtain GMS and which enters with the time scale set by τ. Second, the third and fourth terms describing the free-field contribution of the second field enter (31) with the sign opposite to that of the first field: . This is the same as in our dissipative Lagrangian (23).
D. The Hamiltonian
The Hamiltonian of our composite system consisting of fields φ 1 and φ 2 is where L φ is given in (9) and where the conjugate momenta are This gives The terms with τ re-appear in the Hamiltonian once the Hamiltonian is written in terms fields and momenta, as discussed in the next section. We now compute the energy of our system directly using the solutions derived in the previous sections. The results are obviously independent of the choice of variables such as φ or ψ.
Using the solutions for φ in (12), the Hamiltonian for k > k g above the k-gap is Below the k-gap, we have: At k = k g , ω R = 0, and the two results coincide: The Hamiltonian is displayed in Fig. 5 in both regimes. The Hamiltonian oscillates both in time and space for k > k g and decays with time for k < k g . The lower bound of (37) is H l = ω 2 R − c 2 k 2 , or − 1 4τ 2 , according to (13). The lower limit of (38) is H l = −c 2 k 2 . Given that k < k g in this regime, H l of (38) is −c 2 k 2 g . Combined with k g = 1 2cτ from (13), the lower bound of (38) is H l = − 1 4τ 2 , the same as the lower bound of (37). Therefore, H l has a finite value in both regimes for a finite τ. We recall that the UV cutoff for τ in condensed matter systems is given by τ D in (17). The limit τ → 0 corresponds to the infinite gap k g ∝ 1 τ and, therefore, non-propagating waves which our Lagrangian formulation is not designed to describe.
We now perform time and space average of the Hamiltonians (37) and (38) and find H = ω 2 R > 0 for k > k g (40) in agreement with the earlier calculation [23], and (41) is consistent with the fact that there are no propagating waves below the k-gap.
To summarise, we find that the Hamiltonian of the composite gain-loss system is stationary in the propagating wave regime k > k g . In this regime, the energy has a lower bound and a positive average value. In the non-propagating regime k < k g , the system energy similarly has a lower bound and zero average energy as expected.
IV. NON-HERMITICITY AND PT SYMMETRY
As mentioned earlier, the Lagrangian of our theory, (9) or (23), is not Hermitian. However, we will see that both the Lagrangian and Hamiltonian in our theory are PT symmetric. We first recall how non-Hermiticity arises in theoretical approaches to dissipation.
The effect of dissipation can be generally represented by a complex energy spectrum, with imaginary term setting the lifetime of the state (see, e.g., [2,6,51,52]). This is similarly discussed in the context of resonances (see Ref. [53] for a recent discussion and a review) in which the complex energy plane is considered. Resonances are derived from complex poles of the form: which necessitates a non-Hermitian model. The width of the resonances or, equivalently, their lifetime, is due to dissipation. To illustrate how non-Hermiticity is related to dissipation and a finite relaxation time, it is instructive to consider a simple quantum mechanical system in the Heisenberg picture [54]. Given a generic operator O, its time dependence is given by: The dynamics of such operator is: We observe that a Hermitian Hamiltonian H † = H implies the conservation of this operator. On the contrary, the non-Hermiticity introduces a finite relaxation time: The energy spectrum of a Hermitian Hamiltonian are real, however one of the central points of the discussion of symmetry Figure 6. The gain-loss mechanism typical of non-Hermitian systems. One system is dissipating at a rate γ, while the other is absorbing at the same rate. If the coupling between the two systems g is large enough, PT symmetry is unbroken and the eigenvalues are real. under parity and time transformations (PT symmetry) is that a Hermiticity can be replaced by a weaker condition: a non-Hermitian but PT -symmetric Hamiltonian may still result in real spectra. This follows from an assertion that PT -symmetric Hamiltonians have secular equations with real coefficients so that some of the eigenvalues can be real depending on parameters [3,5] The discussion of the PT symmetry [3] starts with noting that a realistic physical system is an open non-isolated system with accompanying flux of probability flowing in or out. Theoretical description of this system is a long-standing problem, both classically and quantum-mechanically [2,58]. The proposal to address this problem is to treat an open system as a subsystem and add another, time-reversed, subsystem with the opposite net flux of probability, so that the composite system had no net gain or loss of probability flux and is closed. The composite system exhibits the PT symmetry, where T is the time-reversal operator and P is the generic parity operator that interchanges the two subsystems [3].
Although the two subsystems are not stationary and are not in equilibrium separately, the stationary state of the composite system can be achieved by coupling the subsystems. The eigenvalues of the composite system are real, provided the coupling parameter is large enough, corresponding to the stationary state of the system and unbroken PT symmetry [3]. This process can be illustrated by a system two coupled localised oscillators with gain and loss discussed earlier (see Fig. 6). The equations of motions for two coupled oscillators areẍ + ω 2 x + γẋ = gy andÿ + ω 2 y − γẏ = gx, where x and y are coordinates, γ is the friction coefficient and g is the coupling parameter. The coupling term enters the Hamiltonian as H c = −gxy, and the total Hamiltonian is PT -symmetric. There are three regimes: weak, intermediate and strong coupling corresponding to no real solutions (frequencies), four real solutions and two real 2 It was observed that "The reality of the spectrum of H implies the presence of an antilinear symmetry (which is not necessarily PT ). Moreover, the spectrum of H is real if and only if there is a positive-definite inner-product on the Hilbert space with respect to which H is Hermitian or alternatively there is a pseudo-canonical transformation of the Hilbert space that maps H into a Hermitian operator" [55][56][57].
solutions, respectively. The state where all solutions are real corresponds to unbroken PT symmetry, whereas complex solutions correspond to broken symmetry [3]. There are several interesting similarities and differences between the above system discussed in the context of PT symmetry and the system in our theory. First, φ 1 and φ 2 describe fields, rather than localised oscillators and correspond to propagating waves in the solutions. This is required in order to describe the k-dependence and gapped momentum states in particular. Second, the φ 1 and φ 2 in (12) can be viewed as two subsystems with opposite fluxes of probability, similarly to the discussion of PT symmetry above. Third, the coupling term between φ 1 and φ 2 (ψ 1 and ψ 2 ) is different and involves the coupling between one field and the derivative of the other field (see Eqs. (8), (9) and (23)) rather than between the fields themselves as in the model used in the above discussion of PT -symmetry.
Let us look at the properties of our system in more detail. The easiest way is to define the doublet: Parity P and time reversal T transformations act on the coordinates as: Their action on the field doublet can be written in matrix form as: The latter coincides with the statement that a PT transformation swaps the source and the sink [3], i.e. φ 1 ↔ φ 2 . Given these definitions, we observe that the Lagrangians (9) and (23) are invariant under the transformations involving fields swapping and change of time sign and, therefore, are PT -invariant. However, a Lagrangian is not a physical observable (unlike a Hamiltonian), and its unclear whether the PT -symmetry of the Lagrangian is related to real energy spectrum. To study the energy spectra, we write the Hamiltonian (36) in terms of fields and momenta as The PT transformation involves changing the sign of momenta and swapping two fields. We observe that this gives PT H = H, implying that H in (49) is PT -symmetric and [PT , H] = 0. However, this is not a sufficient condition to ensure real eigenvalues. The caveat is that the time reversal T is an antilinear operator. Given the eigenvectors of the Hamiltonian and PT operators: H |n H = n |n H , PT |n PT = ε n |n PT (50) the two eigenvectors do not necessarily coincide: This last criterion defines two different phases of the system (see Fig.7): the PT unbroken phase and the PT broken phase. The first is distinguished from the second by the fact that the two sets of eigenvectors are equivalent. This implies: PT unbroken phase : real eigenvalues, Im(ω n ) = 0 PT broken phase : pairs of complex eigenvalues The second phase can be viewed as the phase where coupling between the source and the sink cannot be balanced [3], corresponding to a proper open system [2,58]. The separation between the two phases is called the "exceptional point" and is characterized by interesting properties such as a the halving of the degrees of freedom and unparticle physics [59,60]. In the context of non-Hermitian theories and dissipation, the exceptional point was discussed in Ref. [61].
The phase diagram of our system can be discussed using the eigenfrequencies of the system (4). They have the same form as (42): The solutions of the form (52) are called "quasinormal modes" and are discussed in several fields, including dissipative open systems, holography [62], hydrodynamics [63] and gravitational waves dynamics [64,65]. In these areas, it is well recognised that the finite imaginary part of these modes determines the relaxation times of the excitations and governs the late-time dynamics of the physical system. For a finite τ, our system is in the PT -broken phase because, according to Eq. (4), the spectrum always contains an imaginary term. The eigenvalues in our theory, given by Eq. (4), become real in the absence of dissipation and τ → ∞. This implies that τ → ∞ corresponds to the exceptional point. Fig. (7) illustrates this point.
As discussed in section III, the number of degrees of freedom is halved in the absence of dissipation when τ → ∞. This is reminiscent of the exceptional point which separates the PT broken and unbroken phases. In our case, the exceptional point is at infinity and the system is always in the PT broken phase, in which the eigenvalues are complex.
It would be interesting to deform our Lagrangian (9) or (23) by adding a new scale that allows the system to cross over between two regimes in the phase diagram shown in Fig. 7 as in simpler field theories of [66][67][68].
V. CORRELATION FUNCTIONS
Using Lagrangian (9), the equations of motion can be written in matrix form as: where K ab is the kinetic (matrix) operator, which in Fourier space is: We define the matrix of Green's functions as with the inverse: Then, the correlation functions read Taking the Fourier transform gives time dependence of these functions as where is the frequency related to GMS as in (13). To find the correlation functions for fields ψ fields, we use the inverse transformation of (22): resulting in Interestingly, the trace of the Green's function matrix vanishes as follows from ψ 1 ψ 1 = − ψ 2 ψ 2 above and from (56): Combining (57) and (60) gives Taking the Fourier transform gives time dependence of these functions as which also follows from combining (58) and (60). For k > k g when ω R is real and positive, the correlators of both fields φ and ψ show a damped oscillatory behavior with two important features. First, the oscillation frequency of the correlation functions is set by ω R in (59), the frequency that sets gapped momentum states as discussed throughout this paper. This frequency features in the poles of calculated correlation functions (see, e.g., Eqs. 58 and 62). Second, the decay time of the correlation functions is set by the relaxation time τ.
For k < k g in the fluid-mechanics regime, the oscillatory behaviour disappears, and the late time dynamics is exponentially decaying. This is illustrated in Fig. 8 where we plot the correlation function ψ 1 ψ 1 (62) in three different regimes.
The behavior of correlation functions in (58) and (62) is expected and is physically reasonable. It shows that the non-Hermitian field theory with dissipation proposed here yields physically sensible results in terms of correlation functions and their frequency and time behavior. This is important in view of previous problems of formulating a Lagrangian-based field theory with dissipation.
The same results for correlation functions can be obtained using path integration. The path integral has the following form: where Dφ = V k = V −1 is the system's volume in k-space. If the Lagrangian has the form of (9) then As a specific example, let us consider the calculation of the φ 1 φ 2 correlation function: Using functional derivation, the correlation function can be written as where α 1 and α 2 are the sources. After integrating over φ 1 and φ 2 , we obtain This is the same result as φ 1 φ 2 in (57). The other correlators can be obtained using the same method. This shows that the path integral formulation of our theory is sensible and gives consistent results.
VI. INTERACTION POTENTIAL
To calculate the interaction potential between particles in our field theory, U(r), we consider the static limit (ω = 0) in the propagator and take its Fourier transform [30]. The transform needs to be taken above k g = 1 2cτ because the solution of our field theory gives the spectrum with gapped momentum states according to Eq. (13). In other words, there is no propagating force-mediator below k g . The interaction potential for our system is given by: and can be calculated as: resulting in The second term in Eq. (70) represents the modification to the Coloumb potential due to the effect of the k-gap. The modification is given in terms of the sine integral, the integral of the sinc function. The calculated U(r) in (70) is shown in the top panel of Fig. 9 for different values of k g . At k g = 0, U(r) ∝ 1/r as expected. Interestingly, a finite k g results in the emergence of oscillations of U(r). The oscillation frequency is 2π k g , as the middle panel of Fig. 9 illustrates for k g = 1. The oscillations decay in space as ∼ 1 r . With the mass term m present in the Lagrangian, the potential takes the form: resulting in The calculated U(r) in (72) is shown in the bottom panel of Fig. 9. The effect of the mass is to (a) slightly modify the periodicity of oscillations and (b) modify the power law decay from ∼ 1 r to faster Yukawa-type decay ∼ 1 r e −mr as expected. We therefore find that the presence of dissipation and k-gap in particular results in the emergence of oscillations in the interaction potential.
We note that the decayed oscillatory potential ∼ 1 r 3 cos(2k F r), where k F is the Fermi wavevector, appears as a result of charge screening and electron-electron interactions in the free electron gas, and is known as Friedel or Rudderman-Kittel oscillations [69]. The oscillation frequency of this potential is set by k F . This is analogous to k g setting the oscillation The potential for k g = 1 illustrating the periodicity 2π/k g = 2π using the gridlines. Bottom: the interaction potential (72) for zero and finite mass. The effect of the mass is to change the decay from power-law ∼ 1/r (red line) to exponentially-decaying and Yukawa-like (black line). The inset shows that the oscillations do not disappear for large m but are exponentially damped.
frequency of U(r) in Eq. (70). A further analogy is that (a) k g sets the lower bound for wavevectors of collective excitations (waves or phonons) and (b) k F sets the lower bound for wavevectors of thermally excited electrons because the lowerlying levels are filled. It may be interesting to explore these analogies further in future work.
VII. FURTHER DISCUSSION
A. Departure from the "harmonic paradigm" Introducing the quantum field theory and its Lagrangian L, Zee writes [30]: The first two terms in (73) describe a harmonic theory and propagating plane waves, giving the starting point of the theory. The nonlinear terms describe scattering of plane waves originating from the harmonic part of the Lagrangian and production of new particles. The nonlinear terms need to be small compared to the harmonic term in order for the perturbation theory to converge and produce sensible results.
Zee observes [30] that the subject of the field theory remains rooted in this "harmonic paradigm". Characterising this state of affairs as limited, he wonders about ways beyond the paradigm. Notably, our approach and in particular the Lagrangian (23) (or (9)) represents a departure from the harmonic paradigm in two important respects.
First, the elastic or harmonic (Klein-Gordon) term in (23) is not necessarily a starting point of the system description, with the viscous dissipative term added on top as is the case in the harmonic paradigm of the field theory based on (73). Indeed, both elastic and viscous ∝ 1 τ term are treated in (23) on equal footing. The same applies to elastic and viscous terms in the Maxwell-Frenkel interpolation (1) where they are similarly treated on equal footing, and on which our Lagrangian formulation is based.
The combined effect of elastic and viscous terms is interestingly related to the widely-used term "viscoelasticity" and the area known as generalized hydrodynamics [21,70]. The central effort in this area is to start with hydrodynamic equations such as Navier-Stokes equation and subsequently modify it to include the elastic response. The term and approach are related to the everyday observation that liquids flow and therefore necessitate a hydrodynamic approach as a starting point, with the elastic properties accounted for as a next step. However, we recently showed [23] that the same Eq. (2) that follows from this Lagrangian can also be obtained by starting with a solidlike equation for a non-decaying wave and by subsequently generalizing the shear modulus to include the viscous response using Maxwell interpolation (1). Therefore, "elastoviscosity" is an equally legitimate term to describe Eq. (1) and (2) as well as Lagrangians (9) or (23). This is apparent in our Lagrangian (23) which gives no preference as to the starting point and treats elastic and viscous terms on equal footing.
Second and differently from (73) where nonlinear terms need to be small in order for the perturbation theory to converge, the dissipative ∝ 1 τ term in (23) is not small in general. As discussed in the next section, large dissipative term (small τ) results in purely hydrodynamic viscous regime where no shear waves propagate, completely negating the effect of the harmonic elastic term. In this sense, our approach and Lagrangian (23) is essentially non-perturbative.
We observe that all the nonlinear terms in (73) can be thought to be incorporated in the dissipative ∝ 1 τ term in Lagrangian (23). At a deeper level, this is tantamount to stating that the introduction of liquid relaxation time τ by Frenkel [32] accounted for the (exponentially) complex problem of treating strongly-coupled nonlinear oscillators [21,71].
B. Implications for a Lagrangian formulation of hydrodynamics
As discussed earlier, the treatment of dissipative systems using a formal field theory has been a long-standing problem. A related open problem is formulating hydrodynamics, the area with a long history, using the field-theoretical description based on a Lagrangian. We note here that hydrodynamics in a broad sense is an effective field theory description valid at large wavelengths and long times. In this sense it is applicable to all systems, including crystals [44]. In a different context, "hydrodynamics" is used as an equivalent to "fluid-mechanics"and applies to liquids only [43]. To avoid confusion, we will refer to hydrodynamics in a broad sense and to fluid dynamics in the second, more restrictive, sense.
One general approach to this problem was to use Keldysh-Schwinger-based techniques discussed earlier in this paper and out-of-time-order contours [7,10,[72][73][74] and more recently holography [75,76]. Despite the action being typically non-Hermitian (i.e. containing a finite but positive imaginary part, Im(S e f f ) > 0), a unitary evolution is ensured by the KMS constraint [7]. In the regime where dissipation is slow, τ/T 1, an interesting phenomenological formalism (not derived from an action formalism) known as quasi-hydrodynamics [77] has been proposed and verified explicitly in several holographic constructions [17][18][19][20].
Our description of dissipation and gapped momentum states involves two fields in the Lagrangian (9) or (23) and in this sense is similar to the Keldysh-Schwinger approach where the two fields are introduced to close the integration contour (see section III C). For convenience, we re-write (9) and (11): The Lagrangian and equations of motions have two parameters, c and τ. This suggests that the Lagrangian can give rise to different regimes depending on c and τ. Below we show that the constructed Lagrangian indeed has three welldefined regimes: (a) purely elastic non-dissipative and nonfluid regime, (b) mixed regime where transverse modes propagate above the k-gap and (c) purely fluid-dynamics regime where no transverse modes propagate.
As discussed earlier, the most general solution describes propagating transverse modes above the k-gap according to Eqs. Figure 10. Illustration of different regimes described by our field theory. The field theory correctly describes a fluid system with diffusive modes only at length scales d > 2cτ. At smaller distances d < 2cτ, the field theory predicts a solid-like non-hydrodynamic behaviour with propagating shear modes. (12) and (13). This is the mixed regime (b) above. The purely elastic Lagrangian, and regime (a) above, readily follows from setting τ → ∞, in which case φ 1 = φ 2 , according to (12), and we are left with a standard propagating Klein-Gordon field. A non-propagating regime follows from considering the condition at which fluid mechanics applies: ωτ 1 [32,43]. Considering time dependence of fields φ 1,2 ∝ exp(iωt), we see that the terms with second and first time derivative in (75) are ∝ ω 2 τ 2 and ∝ ωτ, respectively. Therefore, the second time derivative term can be neglected in the regime ωτ 1, and we find the "loss" subsystem describing the Navier-Stokes equation predicting non-propagating waves, c 2 ∂ 2 φ 1 ∂x 2 = 1 τ ∂φ 1 ∂t , and its gain counter-part, ∂t . The different regimes also follow without bringing the frequency of external probe, ω, into consideration. The product of two parameters c and τ in the Lagrangian (74) gives the length scale cτ. We now recall that in the fluid mechanics regime, now transverse modes operate [43]. It is easy to see our Lagrangian describes this regime at distance Indeed, (74) results in no propagating modes when the frequencies (4) do not have a real part. This corresponds to k < k g , or λ > 2cτ for wavelengths (see Eq. (13)). We also recall that cτ is the wave propagation range, and that a wave, in order to be well-defined, must not have a wavelength longer than the propagation range. Hence, (76) follows, as illustrated in Fig. 10. We note that hydrodynamics and fluid mechanics are often stated to describe the medium at small k. The novelty here is that the field theory proposed gives a specific range of k based on the parameters of the theory (c and τ) where the fluid-mechanical description operates.
We note that conditions (76) and k < k g are consistent with the condition of applicability of fluid mechanics discussed earlier, ωτ < 1. Indeed, combining the dispersion relation with the k-gap (13) with ωτ < 1 gives k < 5 2 1 cτ ≈ 1 cτ , or approximately k < k g .
Increasing τ decreases the range of length scales where the hydrodynamic regime operates. At τ → ∞, this range shrinks to zero, consistent with removing the dissipative term in our lagrangian. On the other hand, small τ increases the hydrodynamic range. In this process, there is an interesting difference between the scale-free field theories and the field theory describing condensed matter phases with the UV cutoff. Unlike in scale-free field theories, τ can not decrease without bound in condensed matter phases and is bound by the shortest, Debye, vibration period, τ D . When τ approaches τ D , cτ becomes cτ D and is approximately equal to the shortest distance in condensed matter phases set by the interatomic separation a (see (17)).
It is interesting to recall that τ = τ D at the UV cutoff corresponds to the Frenkel line separating the combined oscillatory and diffusive components of liquid dynamics from purely diffusive motion [21,36,37]. τ = τ D corresponds to k g approaching the zone boundary, at which point all transverse waves disappear from the system spectrum. This, in turn, corresponds to purely hydrodynamic Navier-Stokes solutions as discussed above.
We note that below the k-gap, Eq. (4) gives two solutions. One of them is the diffusive mode representing the diffusive hydrodynamic shear flow: The second mode is and is not present in the standard formulation of fluidmechanics description [43]. The second gapped mode is related to GMS, which emerges due to the collision between the diffusive and gapped modes. In a more general framework, this gapped mode can be captured by improved setups such as generalized hydrodynamics [77]. The diffusive mode operates in the limit ωτ 1 as in standard fluid mechanics, as is illustrated in Fig. 11.
C. Implications for liquid theory
In addition to the general importance of formulating a field theory with dissipation, our results have more specific and practical interest in areas where decaying excitations are either experimentally measured or are obtained for modelling and need to fitted and analyzed. One example is the area of liquids where the measured inelastic structure factor needs to be fitted in order to extract phonon frequencies. Traditionally, the results of generalized hydrodynamics [21,70] are used to fit experimental spectra. Generalized hydrodynamics starts with the hydrodynamic equations and subsequently modifies them to account for solid-like non-hydrodynamic effects such as propagating transverse waves. Traditionally, this was supported by our experience that liquids flow and hence require a hydrodynamic theory as a starting point. However, more recent experiments show that even simple low-viscous liquids such as Na, Ga, Cu, Fe and so on are not hydrodynamic but, similarly to solids, support transverse waves with frequencies approaching the highest (Debye) frequency and wavelengths approaching the interatomic separation [21]. A hydrodynamic Figure 11. Different regimes of our system in relation to hydrodynamic description. The red region corresponds to solid-like propagating modes. The region below k g does not have propagating modes and we label it as the "fluid region". The blue area is the hydrodynamic regime ωτ 1 , kcτ 1 which is smaller than the fluid region. The red star indicates the breakdown of the hydrodynamic perturbative framework.
Navier-Stokes equation does not predict these waves [32,43]. Therefore, describing real liquids necessitates the presence of an elastic component in the equations of motion such as Eq.
(2) which, in turn, follows from the viscoelastic Maxwell-Frenkel theory. As discussed earlier, this elastic component is manifestly present in the Lagrangian (23) in the form of the Klein-Gordon fields and enters the Lagrangian on equal footing with the hydrodynamic dissipative term. This discussion therefore revisits the point discussed in the earlier section related to the correct starting point of liquid description involving both hydrodynamic and elastic terms.
Returning to the generalized hydrodynamics approach, there are issues related to its phenomenological nature and, consequently, approximations used to fit liquid spectra [78,79]. These can affect the reliability and interpretation of experimental data. On the other hand, a Lagrangian formulation of combined effects of elasticity and dissipation is free from these complications. Moreover, the full range of field-theoretical methods can be applied to the Lagrangian to calculate different correlation functions of relevance in the liquid theory as well as other theories where dissipation plays a central role. In this respect, it is interesting to note that the functional form of the denominator of (61) is similar to that obtained in generalized hydrodynamics for correlation functions [70].
VIII. CONCLUSIONS
In summary, we developed a field theory of dissipation based on gapped momentum states and using the non-Hermitian two-field theory with broken PT symmetry. The calculated correlation functions show decaying oscillatory behavior with the frequency and dissipation related to gapped momentum states. We found a new effect in the interaction potential which becomes oscillatory due to the lower momentum bound and discussed analogies with Friedel oscillations. We observed that the proposed field theory represents a departure from the harmonic paradigm theory and discussed the implications of this theory for the Lagrangian formulation of hydrodynamics.
Our theory is relatively simple as compared to more complicated setups [7] and is therefore suitable for practical and tractable calculations, providing an optimal formulation to study dissipation using field theory more generally and beyond the well-known phenomenological approaches. It would be interesting to extend our theory by adding new relevant fields and types of interaction and apply the theory to a wider range of systems of interest including, for example, electromagnetic and electron waves. | 13,235.6 | 2020-04-28T00:00:00.000 | [
"Physics"
] |
Regulation of CRE-Dependent Transcriptional Activity in a Mouse Suprachiasmatic Nucleus Cell Line
We evaluated the signalling framework of immortalized cells from the hypothalamic suprachiasmatic nucleus (SCN) of the mouse. We selected a vasoactive intestinal peptide (VIP)-positive sub-clone of immortalized mouse SCN-cells stably expressing a cAMP-regulated-element (CRE)-luciferase construct named SCNCRE. We characterized these cells in terms of their status as neuronal cells, as well as for important components of the cAMP-dependent signal transduction pathway and compared them to SCN ex vivo. SCNCRE cells were treated with agents that modulate different intracellular signalling pathways to investigate their potency and timing for transcriptional CRE-dependent signalling. Several activating pathways modulate SCN neuronal signalling via the cAMP-regulated-element (CRE: TGACGCTA) and phosphorylation of transcription factors such as cAMP-regulated-element-binding protein (CREB). CRE-luciferase activity induced by different cAMP-signalling pathway-modulating agents displayed a variety of substance-specific dose and time-dependent profiles and interactions relevant to the regulation of SCN physiology. Moreover, the induction of the protein kinase C (PKC) pathway by phorbol ester application modulates the CRE-dependent signalling pathway as well. In conclusion, the cAMP/PKA- and the PKC-regulated pathways individually and in combination modulate the final CRE-dependent transcriptional output.
Introduction
Transcriptional activation in response to an elevation of intracellular adenosine-3 ,5 -(cyclic)monophosphate (cAMP) is a widespread phenomenon depending, among other factors, on the dissociation of PKA into regulatory and catalytic subunits and transport of the catalytic subunit of PKA from the cytosol to the nucleus [1,2]. In the suprachiasmatic nucleus (SCN) of the hypothalamus cAMP/PKA-dependent phosphorylation of cAMPregulated-element-binding protein (CREB) has been shown to be involved in the amplitude and phase shift of circadian rhythms [3]. The SCN was one of the first neuronal systems in which CREB and CRE (TGACGCTA) regulated transcriptional activity have been shown to play a physiological role, namely clock genes induction and phase shift of their circadian expression [3].
In the SCN, as well as in other cells and tissues, the second messenger cAMP is also regarded as critical for the transcriptional activation of many genes containing a CRE or similar regulatory elements [4][5][6].
In the SCN, in vivo cAMP levels vary with a diurnal (light-dark dependent) and circadian ("free running") rhythm that has a phase length of approximately 24 h. However, not all neurons inside the SCN display circadian rhythms. In the non-circadian cells of the SCN, cAMP may be regulated by neurotransmitters and hormones, and these cells may
Characterization of SCNCRE Cells
SCNCRE cells were derived from an immortalized mouse hypothalamic suprachiasmatic nucleus cell line [13]. Using an antibody against "vasoactive intestinal peptide" (VIP) in immunocytochemical (ICC) staining, most SCNCRE cells displayed VIP-positive granular material in the cytoplasm ( Figure 1A,B). These cells were strongly immunopositive for the neuropeptide VIP but only very weakly positive for arginine vasopressin (AVP) (as shown in Figure 1A,B), suggesting that SCNCRE cells represent a subpopulation of VIP-expressing parvocellular neuronal cells from the SCN. This is underscored by our finding that SCNCRE displays a strong signal for the native, unprocessed form of the vasoactive intestinal peptide, proVIP (17 kDa Figure S2). The astrocyte marker glial fibrillary acidic protein (GFAP) was, as expected, present in the SCN ex vivo extracts, but not in SCNCRE cell extracts (Supplementary Figure S2).
Elevation of cAMP in SCNCRE Cells
Application of the adenylate cyclase activator forskolin (10 µM) elevated extracellular cAMP levels more than 100-fold over basal (control) levels in two separate experiments performed on a 96-well and a 24-well plate (p ≤ 0.0001, n = 5, ANOVA with Bonferroni post-test; Figure 2) against vehicle controls. Cell culture medium and vehicle control cAMP levels were not significantly different. In an additional experiment, forskolin (1 µM) elevated intracellular cAMP levels significantly only after 30 min and 2 h of forskolin application in comparison to a time-matched control. After 4-, 6-and 12-h cAMP levels were not significantly different between control and forskolin-treated SCNCRE cell cultures (Supplementary Figure S6).
Characteristics of the CRE-Luciferase Response in SCNCRE Cells
As stated above, SCNCRE cells are stably expressing a CRE-luciferase reporter gene (CRE-luc) and the luminescence output produced by this CRE-luc reporter is displayed in relative luminescence units (RLU). Figure 3A shows that application of forskolin (1µM) to cultures containing 25.000 cells per well of a 96-well plate leads to an elevation of luciferase activity over untreated controls ( Figure 3A) which depends on the concentration of luciferin in the cell culture medium. A stable relation between forskolin (1 µM) and control activity is reached at luciferin concentrations above 200 µM. This forskolin-induced elevation of CRE-dependent luciferase activity also depends on the number of cells plated and reaches a stable forskolin-treated to untreated control relation above a cell number of
Characteristics of the CRE-Luciferase Response in SCNCRE Cells
As stated above, SCNCRE cells are stably expressing a CRE-luciferase reporter gene (CRE-luc) and the luminescence output produced by this CRE-luc reporter is displayed in relative luminescence units (RLU). Figure 3A shows that application of forskolin (1µM) to cultures containing 25.000 cells per well of a 96-well plate leads to an elevation of luciferase activity over untreated controls ( Figure 3A) which depends on the concentration of luciferin in the cell culture medium. A stable relation between forskolin (1 µM) and control activity is reached at luciferin concentrations above 200 µM. This forskolin-induced elevation of CRE-dependent luciferase activity also depends on the number of cells plated and reaches a stable forskolin-treated to untreated control relation above a cell number of 10.000 cells per well with a luciferin concentration fixed at 500 µM ( Figure 3B). Figure 3C shows the dose-dependent increase of CRE-dependent luciferase activity upon forskolin treatment with 25.000 cells per well and a luciferin concentration of 250 µM. Besides cell number plated, luciferin-and forskolin-concentration, the timing of the response onset, maximum and offset of activity are other important parameters to consider. At a constant cell number of SCNCRE cells per well, the maximum response to forskolin (10 µM) was approximately an hour later than the response to forskolin (1 µM), and the maximum of forskolin (0.1 µM) was even earlier ( Figure 3D). Thus, the higher the applied concentration of forskolin, the later the maximal response time. For the following experiments, the number of cells plated out was fixed to 25.000/well and the final luciferin concentration to 250 µM if not indicated otherwise. To evaluate if the observed CRE-luciferase elevation is mediated by the suspected signal transduction proteins, we next tested the influence of the adenylyl cyclase inhibitor MDL12.330A ( Figure 4A). MDL12.330 (10 µM) showed significant inhibition of the maximum response of forskolin (1 µM) ( Figure 4A). However, MDL12.330 applied alone displayed drastically lower basal RLU values compared to the vehicle controls, which indicates a toxic effect. This presumably toxic effect is also seen in Figure 4B, where forskolin (0.1 µM) is nearly fully inhibited by MDL12.330 but only compared to the vehicle control, not to MDL12.330 (10 µM) alone. One conclusion from these data could be that MDL12.330 at 10 µM is not inhibiting specifically adenylyl cyclase but is most probably toxic to the cells. The next level of regulation is cAMP-activated protein kinase (PKA). A well-established class of PKA inhibitors are the equatorial diastereomers of 3 ,5 -cyclic adenosine phosphorothioate. In particular, the Rp-cAMPS analogue, Rp-8-Br-cAMPS, has been shown to be an efficient inhibitor of PKA. Figure 5A shows that the SCNCRE cell response to forskolin The next level of regulation is cAMP-activated protein kinase (PKA). A well-established class of PKA inhibitors are the equatorial diastereomers of 3′,5′-cyclic adenosine phosphorothioate. In particular, the Rp-cAMPS analogue, Rp-8-Br-cAMPS, has been shown to be an efficient inhibitor of PKA. Figure 5A shows that the SCNCRE cell response to forskolin (1 µM) was inhibited by approximately 50% by Rp-8-Br-cAMPS (1 mM), and the response to forskolin (0.1 µM) was nearly abolished ( Figure 5B). Another important protein class relevant to the regulation of CRE-luc activity are the 3′,5′-cyclic adenosine phosphodiesterases (PDE). Many PDEs catalyze the degradation of cAMP to 5′-AMP (or cGMP to 5′-GMP), but some also bind cAMP or cGMP in a separate site. In the presence of a PDE inhibitor in a cell expressing PDEs, the concentration of cAMP rises. A widely used PDE inhibitor exhibiting a broad inhibition spectrum across the 11 described PDE families is isobutyl-methyl-xanthine (IBMX) [19]. Here, the Another important protein class relevant to the regulation of CRE-luc activity are the 3 ,5 -cyclic adenosine phosphodiesterases (PDE). Many PDEs catalyze the degradation of cAMP to 5 -AMP (or cGMP to 5 -GMP), but some also bind cAMP or cGMP in a separate site. In the presence of a PDE inhibitor in a cell expressing PDEs, the concentration of cAMP rises. A widely used PDE inhibitor exhibiting a broad inhibition spectrum across the 11 described PDE families is isobutyl-methyl-xanthine (IBMX) [19]. Here, the application of IBMX (10 µM) showed robust induction of CRE-luc activity in SCNCRE cells with a maximum after approximately four hours ( Figure 6A). When co-incubated with forskolin (1 µM; which peaks later), the resulting activation curve in SCNCRE cells showed an intermediate maximum of CRE-luc activity. The onset was slower than under treatment with IBMX alone and the maximum time was nearly identical to the maximum time of forskolin alone. A similar result was seen with IBMX (10 µM) and forskolin (0.1 µM) combined ( Figure 6B). Another cellular system of potential relevance for cAMP-mediated CRE-luc activity is the organic anion exchanger (OAE). Under the influence of high intracellular cAMP levels (like when cells are incubated with strong cAMP-elevating agents like forskolin or IBMX), OAE enables the release of cAMP from the cell into the extracellular space. A well-established inhibitor for OAE is probenecid, an established medical compound which serves to reduce the excretion of organic ions from the kidney. Probenecid (10 µM) had no significant additional effect on CRE-luc activity in SCNCRE cells when co-applied with forskolin (1 µM) ( Figure 7A), however at lower forskolin (0.1 µM) concentration probenecid elevated the reaction to forskolin significantly. However, compared to the impact of IBMX, this approximate 20% further elevation appears to be of rather minor importance. luciferase activity induced by 1 µM and 0.1 µM forskolin (A,B). IBMX application displayed significant activation if applied alone which is further elevated when co-applied with forskolin. IBMX displays an earlier maximal response compared to forskolin (approximately 2 h earlier). (Shown are the means values ± SD; ANOVA with Bonferroni post-test; n = 5).
Another cellular system of potential relevance for cAMP-mediated CRE-luc activity is the organic anion exchanger (OAE). Under the influence of high intracellular cAMP levels (like when cells are incubated with strong cAMP-elevating agents like forskolin or IBMX), OAE enables the release of cAMP from the cell into the extracellular space. A wellestablished inhibitor for OAE is probenecid, an established medical compound which serves to reduce the excretion of organic ions from the kidney. Probenecid (10 µM) had no significant additional effect on CRE-luc activity in SCNCRE cells when co-applied with forskolin (1 µM) ( Figure 7A), however at lower forskolin (0.1 µM) concentration probenecid elevated the reaction to forskolin significantly. However, compared to the impact of IBMX, this approximate 20% further elevation appears to be of rather minor importance. As mentioned above, besides concentration and mechanisms of action, we observed the timing of the SCNCRE luciferase responses. To further evaluate this, we applied the PKA agonists SpcAMPS and SpcDBIMPS and the EPAC activator (EPAC-A) in addition to forskolin (Figure 8). Next, we compared the onset and maximum activity of CRE-luciferase activity for forskolin (1 µM), SpcAMPS, SpcDBIMPS and EPAC-A (all 100 µM). SpcAMPS displayed both the fastest onset and earliest significant elevation over control levels (p < 0.001 over control at 1 h). SpcAMPS is followed by SpcDBIMPS and forskolin. EPAC-A did not significantly elevate SCNCRE luciferase activity at any time point. The As mentioned above, besides concentration and mechanisms of action, we observed the timing of the SCNCRE luciferase responses. To further evaluate this, we applied the PKA agonists SpcAMPS and SpcDBIMPS and the EPAC activator (EPAC-A) in addition to forskolin (Figure 8). Next, we compared the onset and maximum activity of CREluciferase activity for forskolin (1 µM), SpcAMPS, SpcDBIMPS and EPAC-A (all 100 µM). SpcAMPS displayed both the fastest onset and earliest significant elevation over control levels (p < 0.001 over control at 1 h). SpcAMPS is followed by SpcDBIMPS and forskolin. EPAC-A did not significantly elevate SCNCRE luciferase activity at any time point. The CREluc activity increase in response to SpcAMPS application remained the highest until after 6 h of incubation. SpcAMPS, SpcDBIMPS and forskolin reached a similar maximal plateau, at which the RLU values did no longer increase and were not significantly different (Figure 8). Another class of protein kinases which was shown to be able to phosphorylate CREB and thereby activate pCREB/CRE-dependent transcriptional responses are the protein kinases C (PKC). The classical PKCs (α, β, γ) are activated by a class of substances called phorbol esters. In contrast to forskolin (10 µM), the phorbol ester PMA (1 µM) did not change cAMP levels ( Figure 9A). However, PMA did elevate pCREB levels significantly higher than Forskolin and as high as the combination of both PMA and forskolin ( Figure 9B) when compared by Western blot analysis. In the CRE reporter gene activity assay after one hour, the RLU levels under PMA treatment did not differ from vehicle control, whereas the forskolin RLU was significantly elevated and the combination of forskolin and PMA ( Figure 9C). The complete time course presented in Figure 9D shows that PMA elevated CRE-dependent RLU values with an early and low maximum around 3-4 h after onset, an acceleration of the onset in combination with forskolin and a more than additive maximum ( Figure 9D). Another class of protein kinases which was shown to be able to phosphorylate CREB and thereby activate pCREB/CRE-dependent transcriptional responses are the protein kinases C (PKC). The classical PKCs (α, β, γ) are activated by a class of substances called phorbol esters. In contrast to forskolin (10 µM), the phorbol ester PMA (1 µM) did not change cAMP levels ( Figure 9A). However, PMA did elevate pCREB levels significantly higher than Forskolin and as high as the combination of both PMA and forskolin ( Figure 9B) when compared by Western blot analysis. In the CRE reporter gene activity assay after one hour, the RLU levels under PMA treatment did not differ from vehicle control, whereas the forskolin RLU was significantly elevated and the combination of forskolin and PMA ( Figure 9C). The complete time course presented in Figure 9D shows that PMA elevated CRE-dependent RLU values with an early and low maximum around 3-4 h after onset, an acceleration of the onset in combination with forskolin and a more than additive maximum ( Figure 9D).
Discussion
The suprachiasmatic nucleus (SCN) of the mouse consists of a number of different cell types [7]. Among the larger neuronal populations of the SCN are cells containing the neuropeptide vasoactive intestinal peptide (VIP) [20]. In the VIP-positive population, some cells apparently do not display circadian expression of clock genes. One theory is that these cells serve as "input sensors" for external stimuli, perceive these and modulate the neighbouring rhythmic cells [13,21].
From the SCN cell line made available by the group of David Earnest, we extracted cells which did not display any detectable luciferase output. These cells were stably transfected with a CRE-luciferase construct (CRE-luc) and further characterized. The clones stably expressing CRE-luciferase and named SCN-CRE (SCNCRE) were strongly VIP-
Discussion
The suprachiasmatic nucleus (SCN) of the mouse consists of a number of different cell types [7]. Among the larger neuronal populations of the SCN are cells containing the neuropeptide vasoactive intestinal peptide (VIP) [20]. In the VIP-positive population, some cells apparently do not display circadian expression of clock genes. One theory is that these cells serve as "input sensors" for external stimuli, perceive these and modulate the neighbouring rhythmic cells [13,21].
From the SCN cell line made available by the group of David Earnest, we extracted cells which did not display any detectable luciferase output. These cells were stably transfected with a CRE-luciferase construct (CRE-luc) and further characterized. The clones stably expressing CRE-luciferase and named SCN-CRE (SCNCRE) were strongly VIP-positive. Like the original cell line, they seem to consist of two morphologically different populations, large flat cells rapidly forming a dense monolayer and small, round cells located on top of the large cells forming long protrusions and establishing connections to each other under prolonged cultivation duration [13].
We tested a series of marker proteins to evaluate the neuronal nature of the SCNCRE cells and their developmental stage. Interestingly, although SCNCRE is an immortalized cell line, they expressed in the confluent stage two makers for mature neurons, ßIII-tubulin and "microtubule-associated-protein-2B" (MAP2B), no marker for immature (Nestin) or maturing neurons (Doublecortin). Taken together, SCNCRE cells express neuronal markers suggestive of rather mature neuronal phenotype cells but do not express GFAP.
SCNCRE cells displayed an elevated CRE-luc activity after the application of forskolin, a diterpene secondary metabolite from the Indian foul tree, Coleus forskolii [22]. Forskolin is widely used to induce cAMP elevation [23]. In the data presented here, cAMP-synthesis by adenylate cyclase (AC), cAMP-degradation by 3 ,5 -phosphodiesterase (PDE) and cAMPexport via organic anion exchangers (OAE) affected CRE-dependent signalling. Besides the various signalling pathway components involved, differential timing of cAMP-production, -degradation and -export processes are important for the latency time of serine 133 pCREB phosphorylation, CRE-dependent luciferase activity onset and maximum reaction, especially when interacting with other parallel pathways like the protein kinase C (PKC) pathway.
Regarding the type of adenylate cyclase present in SCNCRE cells, data are inconclusive. In our experiments, MDL12330 became toxic around the concentrations where it should inhibit AC and SQ22536, another presumed AC inhibitor, did not inhibit forskolin-mediated CREluc activity in SCNCRE cells (Supplementary Figure S7). Thus, the type and regulation of the AC in SCNCRE cells remain to be investigated.
SCNCRE also reacted to the application of the PDE-resistant cAMP analogues, SpcAMPS and SpcDBIMPS, with SpcAMPS being the faster elevator of CRE-luc activity. This finding may be explained by SCNCRE cells predominantly expressing PKA regulatory subunit isoforms IIα and Iiβ for which SpcAMPS is a better activator than SpcDBIMPS, which displays a strong selectivity for PKA I isoforms [24]. SpcAMPS was also the agent with the fastest CRE-luc response, already elevating levels significantly over basal after 60 min, followed by SpcDBIMPS and forskolin.
EPAC-A selectively activates the EPAC proteins (EPAC1 and EPAC2, also known as Rap guanine nucleotide exchange factor 3, GEF3) representing a family of intracellular sensors for cAMP, which function as nucleotide exchange factors for the Rap subfamily of RAS-like small GTPase [25]. Here, the EPAC-activator (EPAC-A) did not exert any significant change in CRE-luc activity compared to controls. EPAC-A does not activate PKA, nor does it significantly influence AC, PDE or OAE activity [25]. We conclude that EPAC plays no significant role in CRE-luciferase activity modulation.
Another finding of relevance is the shift of onset and the estimated time point of maximum when agents were combined. The onset of CREluc activity in SCNCRE cells is faster for IBMX than for forskolin. When both are applied in combination the onset of activity is not significantly slower than that of IBMX alone. However, the maximal response of the combination is at a time point similar to the maximal time response to the forskolin application. Thus, the combination response behaves similar to the faster substance (IBMX) at the onset of activity and similar to the slower substance (forskolin) at the maximum time. The effect that the higher the dose of forskolin, the later the maximal response time also applies for the combination of forskolin with IBMX in that forskolin determines at what exact time point this maximum occurs. Thus, our data support the interpretation that the extent of the temporal shift of the maximum time depends on the dose of forskolin.
Beside PKA, several other protein kinases have been shown to be able to phosphorylate CREB at serine-133 [26]. One of these "CREB-kinases" is protein kinase C (PKC) which represents a family of fifteen isozymes in humans [27]. The classical PKCs (α, β, γ) can be activated by a class of substances called phorbol esters, like the cell-permeable substance phorbol-12-myristat-13-acetat (PMA) [28]. PKCs are known to activate other protein kinases like the p42/44-MAP-kinases, which can also be present inside the cell nucleus or act via shuttle systems like the one involving pp90RSK [29]. Since PMA and forskolin combination is neither simply additive nor synergistic or antagonistic on CRE-dependent transcription activity, the kinases involved in the PMA-activated pathway at least partly compete with those involved in the forskolin-induced pathway.
In contrast to forskolin, PMA did not modulate cAMP levels in SCNCRE cells in our experiments. However, PMA did elevate pCREB levels after one-hour incubation, as shown by Western blot analysis. Under PMA treatment, pCREB levels were higher than under forskolin treatment and as high as the combination of both PMA and forskolin. However, after one-hour CRE-luc activity under PMA treatment did not differ from vehicle control but rose significantly over vehicle control levels after approximately two hours, whereas forskolin significantly elevated CRE-luc activity already after one hour. Thus, neither cAMP levels nor CREB phosphorylation at serine 133 after one hour is a reliable marker for the maximum or the timing of maximal induction of CRE-dependent transcriptional activity in SCNCRE cells.
It is widely assumed that in the SCN in vivo, different populations of parvocellular neurons located in different regions exert very different tasks with respect to rhythm generation, as well as input and output signalling [8][9][10][11][30][31][32][33][34][35]. We used SCNCRE cells, a VIP-expressing transformed cell population derived from the mouse SCN, to investigate the factors determining the cAMP/PKA/CRE-mediated transcriptional response of such cells.
Our conclusion from the experimental data presented here is that there is a doseand time-sensitive cAMP-mediated transcriptional response that is mostly depending on AC-activation and PDE-expression and -inhibition and, to a lesser degree and only at lower stimulant concentration, on the egress of cAMP through OAG. This cAMP-dependent pathway can interact with PKC-signalling but does not or only marginally depend on other cAMP-target proteins like EPAC.
For the SCN in situ, these data suggest a strong coupling and interaction of the different neuronal cell populations of which those that are non-rhythmic should not be neglected regarding their potential influence on input-and phase-regulation and output functions of other cell populations inside the SCN.
Cell Culture
Immortalized mouse suprachiasmatic nucleus cells (200.000 per well in a 6-well plate; kindly supplied by Prof. David J. Earnest PhD, Texas A&M University, Bryan, TX, USA [13] devoid of spontaneous (or basal) luminescence activity were cultivated in Dulbecco's Modified Eagle's Medium (DMEM; Sigma, Deisenhofen, Germany) supplied with 10% fetal bovine serum (FBS), penicillin/streptomycin (100 U/mL) and GlutaMax (Life Technologies, Darmstadt, Germany). This preparation is from here on called complete medium, while the preparation without FBS is called serum-free medium.
These cells were transfected using FuGene HD (Roche, Mannheim, Germany) and a commercially available CRE-luciferase plasmid (pGL4.29[luc2P/CRE/Hygro]) from Promega (Heidelberg, Germany). After maintaining the cells with the transfection reagents overnight, the medium was supplemented with Hygromycin (250 µg/mL) and left for at least three days. The cells were then washed three times with sterile Hank's Balanced Salt Solution (HBSS; Gibco, Life Technologies, Darmstadt, Germany). Those cells still attached to the cell culture plate were enzymatically detached from the cell culture substrate using Accutase-Solution (Accutase; Sigma, Deisenhofen, Germany), counted (manually or by using Scepter 2.0, Merck-Millipore, Darmstadt, Germany) and supplied with medium containing the antibiotic selection agent Hygromycin (50 µg/mL; Enzo Lifescience GmbH, Lörrach, Germany). The surviving (Hygromycin-resistant therefore CRE-reporter-positive) cells were plated out for a selection of stably transfected clones. Mixed clones showing stable induction of CRE-luc-activity induced by forskolin application (10 µM; more than four-fold elevated luminescence in the presence of forskolin over vehicle control (1% DMSO)) were expanded and frozen at a density of 1.5 million/vial at −80 • C in freezing medium (IBIDI, Planegg, Germany). The resulting cell line was named SCNCRE. SCNCRE cells thawed from these preparations were given passage number 1 and used up to passage 13 without detectable changes in control experiments comparing forskolintreated with untreated cells. Cells were passaged once a week at a density of 1 million cells per 75 cm 2 flask.
After incubation with the first antibody, the membranes were washed four times for 2 min with TBS-T and incubated with the appropriate secondary HRP-coupled antibodies against rabbit (1:50.000; Santa Cruz Biotechnology, Heidelberg, Germany) or mouse (1:50.000; DAKO, Hamburg, Germany) in Rotiblock for 1 h at room temperature. Membranes were washed with TBS-T four times for 2 min and once for 5 min. Signal detection was performed using the chemiluminescent substrate Luminata forte (Millipore, Darmstadt, Germany) or AceGlow TM Ultrasensitive (PeqLab, Munich, Germany) and a CCD cameraequipped luminescence analysis system (Quantity One, ChemiDoc XRS, Bio-Rad, Hercules, CA, USA; or a Fusion XL system from PeqLab, Munich, Germany).
Immunocytochemistry
5.000 or 25.000 SCNCRE cells were plated on poly-L-lysine-coated glass coverslips (10 mm diameter) and treated with 10 µM forskolin or left untreated (control/1% DMSO) for one hour. For fixation, the medium was removed at the end of each experiment and replaced with phosphate buffer (0.1 M) containing 4% (w/v) paraformaldehyde (Morphisto, Frankfurt, Germany) for at least 15 min at room temperature. Samples were washed with 0.1 M phosphate-buffered saline (PBS) for 15 min and blocked for 45 min at room temperature using 5% (v/v) normal goat serum (both from Sigma-Aldrich, Darmstadt, Germany) PBS containing 0.3% (v/v) Triton-X-100 (blocking buffer). The cells were incubated overnight with primary antibodies in a blocking buffer (Benz et al., 2010). The primary antibodies used were anti-β-actin (1:10.000; Sigma-Aldrich, Deisenhofen, Germany) and anti-phospho-CREB (1:500) (Cell Signaling, Bad Nauheim, Germany). Diaminobenzidin (DAB) staining was performed according to a standard protocol as described [37,38]. For fluorescence staining, samples were washed three times for 10 min in PBS and incubated in fluorochromecoupled secondary antibodies against rabbit (Alexa-568; 1:2.500, Invitrogen) and mouse (Alexa-488; 1:500; Active Motif, Rixensart, Belgium) in blocking buffer. Coverslips were washed three times for 10 min in PBS, mounted on slides using VectaShield HardSet Antifade mounting medium with DAPI (Vector Laboratories, Newark, CA, USA) and stored at 4 • C. Intracellular distribution and fluorescence intensity of immunolabeled proteins was determined by fluorescence microscopy (Axio, Zeiss, Göttingen, Germany).
cAMP ELISA
Extracellular cAMP was determined in SCNCRE cells using serum-free, undiluted cell culture supernatant and a commercial ELISA (Cayman, Ann Arbor, MI, USA; Item no. 581001) according to the supplier's protocol as described before [36]. In brief, SCNCRE cells were plated either at 25.000 cells per well on a 96-well plate or 400.000 cells per well on a 24-well plate, left overnight in serum-free medium and exposed with the indicated substances for one hour. Subsequently, the medium was harvested and either frozen at −20 • C for later processing or directly subjected to the sample plate provided in the cAMP ELISA kit. The cAMP ELISA procedure was performed according to the supplier's manual, as previously described [36].
Determination of Luminescence Activity
If not indicated otherwise, 25.000 cells per well of a 96-well plate were plated in 100 µL volume and left in the incubator overnight in order to promote adhesion. Experiments were performed in 200 µL medium/well containing 0.25 mM Luciferin (unless indicated otherwise) and measured in a luminometer (BMG Lumistar; BMG, Ortenberg, Germany) or Berthold Centro LB960 (Berthold Technologies, Bad Wildbad, Germany) at 35 • Celsius for 0.1 s per well. Luminescence data are displayed as relative luminescence units (RLU). Cells were measured after different times of incubation (e.g., every 15 min) with and without chemical agents potentially influencing CRE-luciferase signalling unless indicated otherwise.
Image Analysis and Statistics
Images of protein bands were digitized either using a Bio-Rad Universal Hood equipped with a CCD camera, Quantity One and ChemiDoc XRS software (BioRad, München, Germany) or a Fusion system (Vilber/PeqLab; PeqLab/VWR, Erlangen, Germany). Signal intensities of the digitized images were analyzed using online open access ImageJ software (https://imagej.net, accessed on 27 July 2022) [39]. Each area/density value for a specific protein band was normalized against the corresponding β-actin signal of each extract. Statistical significance between groups was analyzed using one-way ANOVA, followed by the Tukey post-hoc test. The criterion of significance was p ≤ 0.05, with analysis performed using GraphPad Prism 8.4 (GraphPad, San Diego, CA, USA).
SCN Ex Vivo Sample Treatment
Mice were held under a schedule of 12 h of darkness and 12 h of light with unlimited food and water supply according to the veterinary laws of Germany. Animals were sacrificed at Zeitgeber time (ZT)10 (ten hours after lights on) and ZT14 (2 h after lights off. The brains were excised, and the SCNs were punched out with a hollow needle. The punches were immediately mixed with two times concentrated sample buffer homogenized by sonification and treated as described above for the SCNCRE cell extracts for Western blot analysis.
Informed Consent Statement: Not applicable.
Data Availability Statement: All raw data and calculations are available from the senior author. | 6,776 | 2022-10-01T00:00:00.000 | [
"Biology"
] |
TST R : Target Similarity Tuning Meets the Real World
Target similarity tuning (TST) is a method of selecting relevant examples in natural language (NL) to code generation through large language models (LLMs) to improve performance. Its goal is to adapt a sentence embedding model to have the similarity between two NL inputs match the similarity between their associated code outputs. In this paper, we propose different methods to apply and improve TST in the real world. First, we replace the sentence trans-former with embeddings from a larger model, which reduces sensitivity to the language distribution and thus provides more flexibility in synthetic generation of examples, and we train a tiny model that transforms these embeddings to a space where embedding similarity matches code similarity, which allows the model to remain a black box and only requires a few matrix multiplications at inference time. Second, we how to efficiently select a smaller number of training examples to train the TST model. Third, we introduce a ranking-based evaluation for TST that does not require end-to-end code generation experiments, which can be expensive to perform.
Introduction
Code generation from natural language utterances is an important and useful ability of large language models (LLMs).Experienced developers can save time, and less experienced users can use natural language to perform data transformation tasks that they would otherwise have to carry out manually (Liu et al., 2023).Improving the code generation capabilities of LLMs is a popular research area (Wang et al., 2021).
Target similarity tuning (TST) was proposed as a method for selecting relevant examples to exploit the in-context learning ability of LLMs and improve performance (Poesia et al., 2022).* First author Split the value in ColumnA into new rows using a comma as delimiter Split the column "output" in Table1 into two columns, using a comma as the delimiter and treating the values as CSV Split the values in the column "Value" of the table "Table1" into two rows.TST improves the alignment between sentence embeddings of utterances by fine-tuning their cosine similarities to match the similarity of their associated code snippets.Sentence-BERT (Reimers and Gurevych, 2019) is used as embedding model.Especially for rare programming languages, the model benefits from seeing relevant code (+3% for SQL versus +16% for SMCalFlow using GPT-3).
Example. Figure 1 shows an example of how TST improves over default embeddings by teaching the model which parts of the utterance are important.The embeddings focus heavily on the "into rows" part of the utterance (where the user might have made a mistake).With TST, we can teach it to focus on the "delimiter" part by focusing on the similarity between code snippets.This paper addresses four limitations of TST when applying it in the real world: (1) sensitivity to language, (2) inference with transformer models, (3) dataset curation and (4) evaluation.
Limitations (1) and ( 2) are due to the sentence embedding model.Training utterances and real utterances often come from different distributions, for example, from users with different skill levels, and smaller models might be unable to capture this variation.When hosted, third-party LLMs are used for code generation, performing inference with transformer models might not be possible, making TST hard to use in production.
We address both these challenges by replacing the sentence transformer with embeddings from a hosted, third-party model and training a fully connected neural network (FCNN) to transform the embeddings to capture the code similarity.The large model provides stronger embeddings and the FCNN only requires a (few) matrix-vector multiplication during inference.
Dataset curation (3) is important, as given n (utterance, code) pairs, we can sample n(n − 1)/2 pairs to create training examples for TST, most of consist of irrelevant code pairs.Since we care about distinguishing the best examples, these irrelevant pairs are not desired.We address this challenge by selecting positive and negative examples close to the important decision boundary and create a smaller dataset that yields better performance and is much faster to train on.
Our method proposed method of training the FCNN on top of frozen embeddings on a relevant set of examples is called TST R (tastier), where R stands for real world.
Finally, optimizing hyperparameters of the TST model is expensive to evaluate when LLM calls are required.We show that an evaluation based on ranking of examples close to the decision boundary matches the end-to-end performance, providing a cheap way to evaluate TST models.
We make the following contributions: (1 + 2) We show that training a small model on top of frozen embeddings makes TST R easier to train and use, and less sensitive to variations in language.
(3) We show that selecting examples close to the important decision boundary allows us to train a TST model with much fewer examples.
(4) We show that ranking (train, test) utterance pairs correlates to the performance of end-to-end code generation, providing a cheap way to evaluate TST models.
Related Work
Code generation from natural language is a popular area of research (Le et al., 2022;Li et al., 2022).Instead of starting from scratch, fine-tuning a pretrained natural language understanding model to generate code is a popular approach, for example, CodeBERT (Feng et al., 2020) was trained from BERT, CodeT5 (Wang et al., 2021) was trained from T5 and Codex (Chen et al., 2021) was trained from GPT-3.
A powerful method to generate code from natural language is prompting large language models (Chen et al., 2021).As opposed to fine-tuning, this does not require large training datasets and expensive compute.Few-shot prompting consistently improves the performance of LLMs across a variety of tasks (Brown et al., 2020).Besides helping the model pick the correct programming language (Athiwaratkun et al., 2023) the provided few-shots can teach the model about specific functions or parameters and contextualization.
One way of selecting relevant examples is by using sentence embeddings (Liu et al., 2021).In some cases, however, similar natural language does not correspond to similar code, and vice versa.Synchromesh (Poesia et al., 2022) introduced target similarity tuning (TST) to address this challenge and fine-tunes the sentence embedding similarity to match the associated code similarity.
This work builds on the concept of TST and improves on important implementation details for training (selecting examples and allowing synthetic data generation), evaluating (cheap evaluation with a proxy metric) and deploying (API call and small FCNN do not have hardware requirements) TST in practice.
TST R
We briefly recap TST, how that transfers to TST R and how examples closer to the relevant decision boundary are selected to improve training
TST
Given two (utterance, code) pairs (u 1 , c 1 ) and (u 2 , c 2 ), vanilla TST fine-tunes a semantic textual similarity (STS) model S m to minimize with S c a similarity between code pairs.The STS model is SBERT, which pools BERT tokens and fine-tunes pooled embeddings to capture similarity between pairs of sentences.TST then transforms the embedding to capture properties of utterances that make their associated code similar.
TST with Embeddings
We decouple the embedding from the similarity and compute with cos the cosine similarity between vectors, m a d-dimensional embedding model (such as SBERT) and t θ : R d → R d ′ a trainable transformation.The parameters of m are frozen.To keep t θ simple, we use a fully connected network with tanh activation.
Training
The training data consists of (u 1 , u
Evaluation Setup
This section describes the datasets, metrics, models and hyperparameters used in our experiments.1
Datasets
We evaluate TST R on three NL-to-code datasets across different low-resource languages.For each language, we also report the evaluation metric and code similarity S c .
Power Query M
The Power Query M language (or M) is used for transforming data in Power Query.We use the data from Khatry et al. (2023) ) is computed as the normalized (Levenshtein) edit similarity between the ground truth and generated code snippets after masking constants (strings and numbers) and identifiers (column names).We use sketch match as S c .
SMCalFlow
SMCalFlow is a task-oriented dialogue dataset of user-agent conversations, where each user query is annotated with a program in a domain-specific language that facilitates a dialogue over a dataflow graph (Andreas et al., 2020).In line with previous work (Poesia et al., 2022) 2022) and use the normalized edit similarity for both evaluation and S c .
Bash
The nl2bash dataset consists of bash code snippets, each with an expert-curated natural language description (Lin et al., 2018).The train and test sets contain 8090 and 606 examples, respectively.We use the template match metric proposed in the original paper for both evaluation and S c .
Models and Hyperparameters
We use text-embedding-ada-002 (ada) and text-davinci-003 (GPT-3) (both from OpenAI) as the embedding and code generation models.In TST R , we use two fully connected layers with 512 parameters (see Section 5.2).To prevent overfitting, we apply dropout (0.3) between the embedding and the fully connected layer.λ k and λ s are set to 4.
Baselines
Across experiments, we use the following baselines for example selections with embeddings.For each baseline, we select eight examples.
• TST (Poesia et al., 2022) trained on examples selected according to our selection strategy • A hybrid approach with frozen SentenceBERT embeddings instead of ada (called TST f ).
Evaluation
We perform experiments to compare TST R against baseline embedding retrieval methods (5.1), we show that ranking relevant examples serves as a proxy metric to optimize hyperparameters without LLMs (5.2), we evaluate how embeddings from large models (ada) are more robust with respect to variations in language (5.3), and we show the effect of selecting relevant examples to train TST R (5.4).
Performance
Table 1 results of TST R and baselines, as well as a static prompt with eight randomly selected examples.TST R consistently performs better (+1%) over vanilla embeddings.Surprisingly, the original TST approach to fine tune SentenceBERT hurts performance on M (-1%) and Bash (-2%).This may be attributed to overfitting on the language of the training set, and not being able to relate new variations in language to the code similarity (see Section 5.3).
Standalone Evaluation
We create a pairwise ranking dataset to evaluate TST R without performing end-to-end code generation and evaluate this approach on M.
Each test point consists of a triplet (u r , u p , u n ) where u r is a reference utterance from the testing dataset, u p and u n are candidate utterances from the training dataset, and S c (c p , c r ) > S c (c n , c r ).We consider two ways of sampling u p and u n and thus create two testing datasets: at random (⋆) or close to the relevant decision boundary, similar to how the training dataset is created (•).We count proportion of correct pairwise decisions.
We compare the execution match (end-to-end) and pairwise ranking evaluation for different embedding-based example selection strategies in Figure 2.Besides baselines, we also consider the theoretical maximum for a given similarity using the code-code similarity.
Our ranking evaluation captures the alignment of the TST model with relevant examples, the ones that are the most similar to a target code snippet, observed by the distinct relation between the trained TST models (•) and the theoretical maximum.This relation does not hold when considering randomly sampled negative examples (⋆).Embeddings rank poorly for relevant examples, but very good for random examples.These observations highlight the need to select relevant examples for standalone ranking: some nuances of similarities in natural language should be unlearned.
Figure 3 shows end-to-end and ranking results for different configurations of TST R on the • benchmark.A model with too few parameters does not learn enough, and too large models (likely) overfit.More interesting is the relation between ranking performance and execution match, where we can use the former as a proxy to determine the number of parameters of TST R . (
Variation in Language
We show how TST R handles variations in language by creating three different testing datasets, with u r Results on • are shown in Table 2.We see that TST R is significantly less sensitive to language that it has not seen during training (test-train).TST performs best when the samples are from the same distribution as the training corpus (train-train).This shows that the model overfits on the training distribution, as performance does not carry over to other language distributions.
Conclusion
We introduce TST R as a practical improvement of TST for selecting relevant examples in code generation from natural language.TST R replaces a fine-tuned SentenceBERT model with a small, trainable transformation on top of a frozen embedding model, and provides a strategy for selecting better training examples.Additionally, we show that TST can be evaluated on pairs of utterances from the training set that are ranked with respect to a reference utterance from the testing set, which does not require end-to-end code generation.
Our experiments show that TST R outperforms classical TST when the language distribution of the example bank does not match that of the tests, that selecting examples closer to the relevant decision boundary improves performance, and that a pairwise ranking evaluation correlates to end-to-end code generation performance.
Limitations
TST assumes that similar code makes for good examples, and this assumption directly transfers to TST R .When the code is similar overall, but specific details are omitted, this can still result in suboptimal examples.
An additional call to an embedding model or endpoint is required to select relevant examples.Whereas embedding calls are generally cheap3 , the network overhead can cause lower latency than inference with a small transformer.
Figure 1 :
Figure 1: Example of a target utterance and associated code, the examples selected by TST and by relying on default embeddings.
Figure 2 :
Figure 2: Relation between execution match (top-1) and our pairwise ranking evaluation with random (⋆) and relevant (•) negative examples on the M dataset.Ranking with relevant examples shows a relation with code generation performance.
Figure 3 :
Figure 3: Relation between execution match (top-1) and our pairwise ranking (•) for different fully connected layer configurations of TST R on the M dataset.There is a clear relation between both metrics.
Table .
FromRows(List.Split(...)) 2 , S c (c 1 , c 2 )) triplets.Instead of randomly sampling (u 1 , c 1 ) and (u 2 , c 2 ) pairs, we aim to find examples close to the relevant decision boundary.That is, we care about examples for which: (1) Sc (c 1 , c 2 ) is high, or (2) S c (c 1 , c 2 ) is low but cos(m(u 1 ), m(u 2 )) is high-that are similar in the original embedding space but have dissimilar code.In other words, we care about examples with properties that we need to learn and that we need to unlearn.For each pair (u i , c i ) we therefore rank all other (u j , c j ) by S c (c i , c j ) and select the top-λ k best ones.We then skip λ s examples to ensure that code similarity is not too high, rank the remaining examples by S c (m(u i ), m(u j )) and again select the top-λ k best ones in this new ranking.λ k and λ s are hyperparameters.
(Poesia et al., 2022;ippets sourced from StackOverflow (test) and the Power Query Community Forum 2 (train and test).The testing set contains 500 snippets annotated by experts.The training set includes 8000 snippets annotated via an LLM (text-davinci-002).We report execution match and sketch match, two standard metrics for code generation(Poesia et al., 2022; Singh et al., 2022).
Table 1 :
TST R performance across languages on endto-end code generation task.We find that TST easily overfits on the language distribution of the training data, but TST R does not.
Table 2 :
Evaluating influence of variations in language.TST f uses a FCL on top of frozen sentence embeddings.Selecting positive samples based on code similarity improves performance-the system sees more desired examples during training.Selecting relevant negative examples, which are close to the relevant decision boundary, shows the model what to forget and improves training of TST.
Table 3 :
Influence of sampling u p and u n for training. | 3,761.8 | 2023-10-26T00:00:00.000 | [
"Computer Science"
] |
Compelling Evidence of Oscillatory Behaviour of Hadronic Multiplicities in the Shifted Gompertz Distribution
Study of charged particle multiplicity distribution in high-energy interactions of particles helps in revealing the dynamics of particle production and the underlying statistical patterns, by which these distributions follow. Several distributions derived from statistics have been employed to understand its behaviour. In one of our earlier papers, we introduced the shifted Gompertz distribution to investigate this variable and showed that the multiplicity distributions in a variety of processes at different energies can be very well described by this distribution. The fact that the shifted Gompertz distribution, which has been extensively used in diffusion theory, social networking and forecasting, has been used for the first time in high-energy physics collisions remains interesting. In this paper, we investigate the phenomenon of oscillatory behaviour of the counting statistics observed in the high-energy experimental data, resulting from different types of recurrence relations defining the probability distributions. We search for such oscillations in the multiplicity distributions well described by the shifted Gompertz distribution and look for retrieval of additional valuable information from these distributions.
Introduction
The simplest observable in high-energy interactions is a count of charged particles produced in a collision and its mean value. Its distribution measured in full or partial phase space forms both a tool for studying models and a probe for particle dynamics. A large number of statistical probability distribution functions (PDF) have been used to understand its behaviour. These include Koba, Nielsen, and Olesen (KNO) scaling [1], Poisson distribution [2,3], binomial and negative binomial [4][5][6] distributions, lognormal distribution [7], Tsallis distribution [8,9], Weibull distribution [10], modified forms of these, and several other distributions. NBD has been one of the most extensively used. It was very successful until the results from UA5 collaboration [11,12] were published. A shoulder structure was observed in the multiplicity distribution in p p collisions, showing its violations. It is also well established by various experimental results that NBD fails with increasing deviations with the growing number of charged particles produced. In order to improve the agreement with data, 2-component or 3component NBD fits [13,14] were also used.
In one of our recent papers, we introduced the shifted Gompertz distribution [15], henceforth named as SGD, to investigate the multiplicities in various leptonic and hadronic collisions over a large range of collision energies. The distribution was first introduced by Bemmaor [16] as a model of adoption of innovations. The two nonnegative fit parameters define the scale and shape of the distribution. This distribution has been widely studied in various contexts [17][18][19]. In our earlier work [15], we proposed to use the SGD for studying the charged particle multiplicities in high-energy particle collisions and showed from a detailed study for collisions in full phase space and also in limited phase space that this distribution explained the experimental data very well in high-energy particle collisions using leptons and hadrons as probes. Subsequently, we also used it to calculate the higher moments of a multiplicity distribution which also serve as a powerful tool to unfold the characteristics and correlations of particles [20]. We also used 2-component shifted Gompertz distribution, named as modified shifted Gompertz (MSGD), to successfully improve the agreement between data and fit. The details are given in our paper [15].
Wilk and Wlodarczyk, in one of their recent publications [21,22], pointed out that the 2-component or multicomponent fits improve the agreement only at large N (number of charged particles) but not at small N. They showed that the ratio data/fit deviates significantly from unity for small N. In a pursuit of retrieving additional information from measured probability of producing N particles PðNÞ, they have proposed the multiplicity distribution (MD) by a recurrence relation between the adjacent distributions PðNÞ and PðN + 1Þ. This corresponds to the assumption of a connection existing only between the production of N and N + 1 particles: The multiplicity distribution is then determined by the function form of gðNÞ, the simplest being a linear relation: where µ and ν are the parameters of the linear dependence. The more general form of recurrence relation introduced in Reference [21,22] which connects the multiplicity N + 1 with all smaller multiplicities has the form All multiplicities are then connected by means of some coefficients C j , which redefine the corresponding PðNÞ in the way such that the coefficients C j connect the probability of particle N + 1 with probabilities of all the N − j previously produced particles. These coefficients can then be directly calculated from the experimentally measured PðNÞ by exploiting the relationship. It is shown that C j shows a very distinct oscillatory behaviour which gradually diminishes with increasing N and nearly vanishes. The details are given in Section 3.
In the present work, we use shifted Gompertz distribution and its modified forms using the data at high energies from p p and pp interactions to understand the existence of such oscillatory behaviour and to check if we obtain the results consistent with the ones from [21,22].
In Section 2, we provide the essential formulae for the probability distribution function of the shifted Gompertz distribution and modified 2-component shifted Gompertz distributions, in brief. A very brief description of how the oscillations have been estimated in the multiplicity distributions by Wilk and Wlodarczyk [21,22] is included for the sake of completeness.
Section 3 presents the analysis of experimental data, the fitted shifted Gompertz distributions, the fitted modified shifted Gompertz, and the distributions giving out the oscillatory behaviour. Discussion and conclusion are presented in Section 4.
Shifted Gompertz Distribution (SGD)
Let X be any nonnegative random variable having the shifted Gompertz distribution with parameters b and ζ, where b > 0 is a scale parameter and ζ > 0 is a shape parameter. The value of the scale parameter determines the statistical dispersion of the probability distribution. The larger the value of the scale Advances in High Energy Physics parameter, the more the distribution spread out, and the smaller the value, the more concentrated the distribution. The shifted Gompertz density function can take on different shapes depending on the values of the shape parameter ζ. It is a kind of numerical parameter which affects the shape of a distribution rather than simply shifting it or stretching or shrinking it. The multiplicity distribution is measured as the probability distribution of a number of particles being produced in a collision at a particular energy of collision and follows certain phenomenological and statistical models. The probability distribution function of X is given by The mean value ðE½XÞ of shifted Gompertz distribution is given by where γ ≈ 0:5772156 stands for the Euler constant (also referred to as the Euler-Mascheroni constant). It is well established that at high energies, the most widely adopted, negative binomial distribution [4][5][6], fails and deviates significantly for the high multiplicity tail, from the experimental data. To extend the applicability of NBD, another approach was introduced by Carruthers and Shih [4][5][6]. In this case, a weighted superposition of two independent NBDs, one corresponding to the soft events (events without minijets) and another to the semihard events (events with minijets), is obtained. These distributions combine merely two classes of events and not two different particle-production mechanisms. We used the same method to obtain the superposed distribution and call it 2-component shifted Gompertz distribution (2-component SGD) as given by equation (6). The multiplicity distribution of each component is independent SGD. The concept of superposition originates from purely phenomenological considerations. The two fragments of the distribution suggest the presence of the substructure. Each component distribution has two fit parameters, namely, scale and shape parameters. The best fit overall distribution to the experimental data, with optimised parameters, also gives an estimate of fraction, α, of the soft collisions, at a given c.m.s. energy. The dynamics of particle production is understood in terms of weighted superposition of soft and semihard contributions. Though these superimposed physical substructures are different, the weighted superposition mechanism is the same. The physical substructures are described by the same SGD multiplicity distributions and corresponding correlation functions, which are QCD inspired genuine self-similar fractal processes [4][5][6]. Same as NBD, SGD allows to describe the multiplicity distribution on purely phenomenological grounds. This may help in differentiating between different phenomenological models. Details are included in our earlier publication [15]: where α is the fraction of soft events and ðb 1 , ζ 1 Þ and ðb 2 , ζ 2 Þ are, respectively, the scale and shape parameters of the two distributions.
Modified Forms of Shifted Gompertz Distribution.
In this paper, we adopt a different approach and investigate what 3 Advances in High Energy Physics kind of changes in the structure of the multiplicity distribution described by the SGD is necessary in order to describe the same data by a single SGD, with accordingly modified parameters b and ζ. To describe data using only a single SGD, we allow the parameter b to depend on the multiplicity N, as suggested by Wilk and Włodarczyk [21,22]. To obtain an exact fit of the distribution to the experimental data, a nonmonotonic dependence of b on N is introduced. This way, the scale parameter b remains the same in nature but varies in accordance with the number of particles produced. Such a change means that we preserve the overall form of the SGD: where a 1 , d, and c are parameters. This leads to the modification of SGD (equation (4)) which describes the data very well. We call this as the modified-SGD1 (MSGD1). When another nonlinear term with a coefficient a 2 is added [21,22] to bring improved agreement with the data: we call this second modification as MSGD2. Further, we investigate the possibility of retrieving some additional information from the measured PðNÞ.
Analysis and Results
Equation (3) can be reversed, and a recurrence formula can be obtained for the coefficients C j for an experimentally measured multiplicity distribution PðNÞ, as below: The errors on the coefficients C j are calculated from the variance: Since the coefficients C j are correlated, the last term of equation (10) introduces dependence of the error in C j on the errors of all coefficients with i < j. This leads to a cumulative effect with a large increase of errors with increasing rank j. However, despite such large errors, the values of hNiC j lie practically on the curve and the points do not oscillate in the limits of errors. Hence, the errors can be estimated reasonably well, by neglecting this cumulative effect.
In the present work, calculations are performed using the data from different experiments and following two collision types: (i) pp collisions at LHC energies ffiffi s p = 900, 2360, and 7000 GeV [23] are analysed in five rapidity windows, jηj < 0:5 up to jηj < 2:4 (ii) p p collisions at energies ffiffi s p = 200, 540, and 900 GeV [11,12] are analysed in full phase space as well as in rapidity windows, jηj < 0:5 up to jηj < 5:0 The charged hadron multiplicity experimental distributions are fitted with the SGD (equation (4)), the 2component SGD (equation (6)), MSGD1 (equation (7)), and MSGD2 (equation (8) Table 1 gives the χ 2 /ndf for all fits at different energies and rapidities. In case of 2-component SGD, the α values are taken from Reference [15]. Table 2 gives χ 2 /ndf for all fits at different energies and rapidities. It may be observed in the cases of pp collisions; MSGD2 fits the data well in comparison with other distributions, particularly at higher energies. However, for the case of p p collisions, in most of the cases, 2-component SGD improves the fits and explains the Figure 5: Ratio R = P data ðNÞ/P SGD ðNÞ for the p p data shown in Figure 2 (red circles) and of the corrected ratio R = P data ðNÞ/P MSGD2 ðNÞ (black squares). 6 Advances in High Energy Physics data well. For a comparison between pp and p p collisions at the same ffiffi s p = 900 GeV, the trend is nearly the same and MSGD2 fit the data best.
In Figures 3 and 4, we show the ratio plots for multiplicity dependence of the ratio R = P data ðNÞ/P fit ðNÞ for the pp data shown in Figure 1 obtained from the fits SGD and MSGD2. Figure 5 shows similar ratio plots for multiplicity dependence of the ratio for the p p data shown in Figure 2. As can be seen from Figures 3 and 5, there are systematic deviations from the fits of SGD from the data at low and high multiplicities. The deviations get enhanced with increasing energy and high multiplicity values, as can also be observed in Figures 1 and 2. In addition, a structure at smaller multiplicities can also be observed. In order to understand this structure, the modified forms of SGD have been introduced as MSGD1 and MSGD2 in equations (7) and (8). The ratio R calculated with MSGD2 becomes closer to unity in all the cases, though the deviations are still present. For the possibility of retrieving some additional information from experimental multiplicity distribution, the recurrence relation given in equation (9) is used to calculate the coefficients C j . In some cases, the 2-component SGD fits exceptionally well leading to the R value around unity, as shown in Figure 4.
The coefficients C j are calculated for the pp and p p data at different centre-of-mass energies and for various pseudorapidity windows. Figure 6 shows C j for pp data in jηj < 2:4 and for the p p data for jηj < 3:0. The figures show a very distinct oscillatory behaviour in both the cases. For the case of pp interactions, oscillations occur with amplitude decreasing with the rank j at all energies. It shows that the effect of an increase in centre-of-mass collision energy has minimal effect on the amplitude and the period of the resulting oscillations. However, for the p p interactions, the trend is reversed, with the amplitude of oscillations growing with the rank j and decrease in collision energy. This intriguing property has also been observed by Rybczyński et al. [24]. The way C j oscillates between pp and p p collisions is clearly different and may be a characteristic of matter-antimatter collision. Abramovsky and Radchenko in their paper [25] have described the particle production in inelastic collisions in terms of quark and gluon strings. They have described the multiplicity distributions in terms of 2-NBD and 3-NBD and have shown how the pp and p p collisions are fundamentally different, which may lead to the observed differences. In another interesting study by Ang et al. [26], similar differences have been observed in p p (UA5) and pp (ALICE) data. Figure 7 shows the coefficients C j calculated for the pp collision data at 7000 GeV c.m. energy and for p p collisions at 200 GeV, for different pseudorapidity windows. They all show the distinct oscillatory behaviour with amplitude increasing with the pseudorapidity window for both pp and p p collisions. It is also observed that the oscillations die out with increasing rank j for all jηj bins for pp collisions, whereas for p p collisions, the oscillations grow stronger with rank j with increasing jηj bin size and somewhat random only in jηj < 5:0 bin. Similar observations are also observed by Rybczyński et al. [24] in the CMS and ALICE data [23,27]. In Figures 6 and 7, the errors on the data points are not shown for the reason that the error bars intermingle and blur the figures.
The coefficients C j are evaluated by fitting the SGD, 2component SGD, MSGD1, and MSGD2 distributions to the data. The variation of these coefficients with j is shown in Figure 8 for pp data in one pseudorapidity window for different energies. We find that C j evaluated from the SGD fit do not show this oscillatory behaviour, as compared with the data. However, with the 2-component fit, they start showing the oscillatory pattern, which further gets enhanced with MSGD1 and MSGD2 fits, following the data closely. In case of MSGD2 fits, coefficients C j follow almost exactly the oscillatory behaviour of C j obtained directly from the data at ffiffi s p = 7000 GeV. For ffiffi s p = 2360 GeV, it is MSGD1, and for ffiffi s p = 900 GeV, the 2-component SGD follow the experimental values better. Similar results are obtained by analysing the data for different pseudorapidity windows both of Figure 6: Coefficients C j obtained from (i) the CMS data of pp collisions at different energies for one pseudorapidity window jηj < 2:4 (a) and (ii) the UA5 data of p p collisions at different energies for pseudorapidity window jηj < 3 (b). 7 Advances in High Energy Physics pp and p p collisions. However, we show the results for 7000, 2360, and 900 GeV pp collisions for only jηj < 2:4 and similarly for 900, 540, and 200 GeV p p collisions for jηj < 1:5, in Figure 9. It may be observed that none of the fits consistently follow the p p data trends. This is also seen for other η windows. To avoid too many similar figures, we present only the representative figures.
The coefficients C j evaluated from equation (9) depend on Pð0Þ. In the experimental data from complex detectors, such as CMS at the LHC, the probability Pð0Þ is very large as compared to Pð1Þ. Due to large experimental uncertainties associated with this bin, Pð0Þ is often omitted for the conventional fits to the data. However, Pð0Þ is the only bin which is very sensitive to the acceptance as explained in References [21,22]. To show the sensitivity to the value of Pð0Þ, we show in Figure 10 the coefficients calculated by using the values P ð0Þ ± δ for the pp data at ffiffi s p = 900 GeV for jηj < 2:4, where δ is the error on Pð0Þ measurement. The coefficients vary with different periods of oscillations, around the values calculated from Pð0Þ, as shown in the figure. Figure 11 shows the oscillatory behaviour when Pð0Þ is not considered; C j are calculated starting with Pð1Þ. Coefficients C j still show Advances in High Energy Physics the oscillatory behaviour but with much reduced oscillation amplitude, with oscillations dying out quickly. In equation (9), the coefficients C j connect each probability, with every other probability. For example, PðN + 1Þ connects to PðN − jÞ, the probabilities of particles produced earlier. The most important feature of this recurrence relation is that C j can be directly calculated from the experimentally measured PðNÞ. In an interesting case study, starting with the SGD, we make changes in successive probabilities by 2%: we put Pð10Þ = P SGD ð10Þ + Δ and Pð11Þ = P SGD ð11Þ − Δ with Δ = 0:02P SGD and study the variation of C j as a function of j. The results are shown in Figure 12 for pp collisions at different energies but within the same jηj bin. Similarly, Figure 13 shows the plots for p p collisions at ffiffi s p = 900, 540, and 200 GeV for jηj < 3. The apparently insignificantly small changes in probability resulted in rather dramatic spikes occurring on the original P SGD and with rapidly falling amplitudes. This points to the sensitivity of the coefficients C j . Such a change is then provided by the MSGD, whereby spike influences then the consecutive coefficients C j and brings them to agreement with those obtained from the experimentally measured PðNÞ. With increasing value of j, smaller are the values of C j and hence weakly influencing
Conclusion
In this paper, we show and reaffirm that the MDs possess a fine structure which can be detected experimentally and analysed in terms of a suitable recurrence relation, such as the one in equation (9). The coefficients C j in the recurrence relation, which are directly connected with the combinants, give a compelling evidence that phenomenon of oscillatory behaviour of the modified combinants exists in the experimental data on multiplicities. The coefficients C j have been calculated from the shifted Gompertz distribution and its modified forms: weighted superposition of 2-component 10 Advances in High Energy Physics shifted Gompertz parametrizations and modified shifted Gompertz distributions including nonlinearity to two different orders, equations (7) and (8). The shifted Gompertz distribution, which we introduced in our publication [15], does not show any oscillatory behaviour. However, its modified forms show the oscillatory behaviour and agree with the data very well. The oscillations are large at low multiplicities for the pp data and tend to die out at large multiplicities. In case of p p collisions, the oscillations follow a reverse pattern. The behaviour of oscillations observed in present studies is very similar to what is observed in the case of negative binomial distribution (NBD), by the authors who pioneered the concept.
Data Availability
All the data used in the paper can be obtained from the references quoted or from the authors.
Conflicts of Interest
The authors declare that there is no conflict of interest regarding the publication of this article. | 4,956 | 2019-11-10T00:00:00.000 | [
"Physics"
] |
Autophagy and Diabetic Encephalopathy: Mechanistic Insights and Potential Therapeutic Implications
Diabetic Encephalopathy (DE) is one of the complications of diabetes mellitus (DM) in the central nervous system. Up to now, the mechanisms of DE are not fully discussed by the field. Autophagy is an intracellular degradation pathway crucial to maintain cellular homeostasis by clearing damaged organelles, pathogens, and unwanted protein aggregates. Increasing evidence has demonstrated that autophagy might play an essential role in DE progress. In this review, we summarize the current evidence on autophagy dysfunction under the condition of DE, and provide novel insights of possibly biological mechanisms linking autophagy impairment to DE, as well as discuss autophagy-targeted therapies as potential treatments for DE
Diabetes mellitus (DM) adversely affects multiple organs due to its long-term course of disease, and the brain is one of its major targets. Early in 1922, W.R. Miles and H.F.Root conducted cognitive behavioral tests on 40 diabetic patients, which confirmed that DM caused cognitive impairment [1]. Subsequently, the effects of DM on the central nervous system (CNS) are taken seriously. According to epidemiologic evidence, patients with both type 1 diabetes mellitus (T1DM) and type 2 diabetes mellitus (T2DM) have shown mild-to-moderate reductions in cognitive function as measured by neuropsychological testing compared to non-diabetic controls [2]. In order to promote researches in this field and enhance the understanding of the disease, DeJong first introduced the concept of Diabetic Encephalopathy (DE) [3].
However, as the interaction between DM and CNS is likely to be complex and multifactorial, the mechanisms of DE still remain poorly characterized. Macro-autophagy (herein referred to as autophagy) is a conserved mechanism that cells utilize to degrade intracellular longlived proteins and organelles through lysosome-mediated degradation. Dysregulation of autophagy has been reported to be linked to a variety of human diseases [4][5][6]. According to the latest numerous studies, autophagy is also found to be impaired in some regions of brain such as hippocampus and hypothalamus in the condition of DM and deficits in autophagy is likely to involved in the development of DE [7][8][9][10][11].
In this study, we begin with an overview of normal functions of autophagy, and then review the evidence of autophagy dysregulation in DE, followed by the discussion of potential mechanisms associated with autophagy in the pathogenesis of DE. In the end, we enumerate some therapeutic strategies that may be effective in the treatment of DE.
Autophagy: overview
Autophagy, a catabolic process that removes cell molecules such as protein aggregates and damaged organelles through lysosomal digestion, is essential for intracellular balance [12,13]. There are three major types of autophagy: macro-autophagy, micro-autophagy and chaperone-mediated autophagy (CMA). Macroautophagy has been regarded as a non-selective cellular process; however, this autophagy controls the quality of cellular contents via selective execution (e.g., long-lived proteins, aggregated proteins, damaged organelles, and intracellular pathogens) [14]. The present review focuses on the mammalian macro-autophagy (hereafter referred to as autophagy).
There are two main pathways involved in the regulation of autophagy. The most well studied pathway is mTOR-dependent signaling pathway, including the AMP-activated protein kinase (AMPK)/mTOR and phosphoinositide 3 kinase (PI3K)/protein kinase B (Akt)/mTOR pathways etc. mTORC1 (mammalian target of rapamycin complex 1) is a complex that mediates the classic functions of mTOR [17,18]. mTORC1 regulates autophagy by controlling the activity of the ULK1 complex. Whenever mTORC1 is activated, autophagy is inhibited due to mTORC1-mediated inhibitory phosphorylation of ULK1. Under diverse cellular stresses, mTORC1 activity is inhibited, thereby promoting ULK1 complex activity and inducing autophagy [19]. mTORC1 can be regulated by diverse signals arising from growth factors (such as insulin), various cytokines, WNT proteins, cellular energy levels [20] etc. Furthermore, autophagy also can be initiated by mTOR-independent signaling pathway, such as Ca 2+ signal [21], trehalose [22], Ca 2+ release channel Transient Receptor Potential calcium channel MucoLipin subfamily member 1 (TRPML1)mediated pathway [23] and so on.
Moreover, microtubule-associated protein 1 light chain 3 (LC3) and sequestosome 1 (p62) are commonly regarded as autophagy-related markers. One approach is to detect LC3 conversion (LC3-I to LC3-II), as the amount of LC3-II is clearly correlated with the number of autophagosomes, LC3-II/LC3-I ratio is generally assumed to be positively correlated with autophagy function. p62 becomes incorporated into the completed autophagosome through its direct binding to LC3 and is subsequently degraded in the autolysosomes; thus, the total cellular expression levels of p62 inversely correlate with autophagic activity [24].
Evidence of autophagy dysregulation in DE
Multiple lines of evidence indicate autophagy is dysregulated in the context of DM. db/db mice, a monogenic model of T2DM with extreme obesity and hyperglycemia caused by abnormal transcription of leptin receptor protein encoded. In addition, the inbred Goto-Kakizaki (GK) rat is a unique model of spontaneous T2DM caused by naturally occurring genetic variants that have been selectively isolated from an outbred colony of Wistar rats. Above genetic T2DM animal models, showed significantly decreasing abilities in learning and memory as well as impaired autophagy function in the hippocampus, which manifested as a reduction of LC3-II/I ratio and a distinct augment of P62 levels [25][26][27]. Similar results were obtained in high-fat diet (HFD)/streptozotocin (STZ) injection-induced T2DM C57B/L mice model. Except for performance on behavioral tests was compromised, the level of p62 was increased while the LC3-II/I ratio was decreased in the hippocampus, striatum and hypothalamus of T2DM C57B/L mice [8,9,28]. Moreover, autophagosomal markers (ATG5 and ATG7) which mediate the formation of the autophagosome were decreased in T2DM C57B/L mice, indicating the formation of autophagosome was impaired [28]. Besides, a number of studies showed that T1DM models exhibited autophagy impairment as well. The expression of p62 protein was remarkably elevated while LC3-II/I ratio was abated in the hippocampus of T1DM group, suggesting dysfunction of autophagy flux [7,29,30,31,32]. In vitro studies, compared with the control group, high glucose incubated HT22 cells and primary neurons also showed autophagy was weakened [26,30]. By conducting mRFP-GFP-LC3 puncta analysis, Li et al. [33] demonstrated that autophagic flux was suppressed by high glucose due to impaired autophagosome synthesis.
Interestingly, autophagy dysregulation in the context of DM has been proved playing an important role in DE development. 3-methyladenine (3-MA), a kind of autophagy inhibitor, could further aggravate cognitive impairment in STZ-induced diabetic mice, including exacerbation of anxiety-like behaviors and aggravation in spatial learning and memory, especially the spatial reversal memory [31]. However, other treatments that target autophagy enhancement could alleviate cognitive function in DE models. Study demonstrated that treatment with liraglutide alleviated the learning and memory deficits in diabetic GK rats, particularly in the high-dose liraglutide group, which turns out that liraglutide works by enhancing autophagy [27]. Guan et al. [25] reported administration of granulocyte colony-stimulating factor (G-CSF) significantly improved cognitive function in elderly db/db diabetic mice, and this change was likely related to the improvement of autophagy.
In summary, a number of studies support the argument that autophagy is impaired in DE and based on which, autophagy inhibition can further aggravate cognitive impairment while enhanced autophagy will alleviate symptoms in animal models of DE. Undeniably, autophagy dysfunction plays a crucial role in DE development, we should further explore the potential mechanisms linking autophagy to DE.
AD-like pathology and autophagy in DE
Extracellular amyloid plaques formed by β-amyloid peptides (Aβ) and intracellular neurofibrillary tangles (NFTs) consisting of hyperphosphorylated tau protein (p-Tau) are two major pathological hallmarks of Alzheimer's disease (AD). Interestingly, no matter in post-mortem brains of T2DM patients or induction of experimental T2DM models exhibited extracellular Aβ aggregation and intracellular p-Tau deposition [7,34,35,36,37]. Aβ has been demonstrated to be involved in several physiological processes, and an excess accumulation in the brain will lead to neuronal loss and consequently memory deficits [38][39][40]. In addition, the degree of tau phosphorylation is inversely proportional to tau's affinity for microtubules and can result in neuronal cytoskeleton destabilization and impaired axonal transport, which in turn can lead to synaptic impairment and progressive neurodegeneration once a pathological threshold is reached [41]. Therefore, the importance of AD-like pathology involved in DE should not be undervalued.
As reported, autophagy is a key regulator of intracellular Aβ clearance. The mechanism of autophagymediated clearance involves isolation of cytoplasmic contents by a double-membrane vesicle called an autophagosome or autophagic vacuole (AV). Subsequent lysosomal fusion facilitates degradation of the AV and its contents, which including Aβ and APP-CTFs (amyloid precursor protein-cleaved C-terminal fragment) [42][43][44]. In addition, autophagy is associated extracellular release of Aβ [45]. As to tau, autophagy is reckoned to be an effective degradation pathway for it [46]. Meanwhile, autophagy also affects the phosphorylation of tau. Inoue et al. [47] found a large amount of highly phosphorylated Tau protein deposits in the brain of mice with ATG7 gene knockout, and this p-Tau deposits would be greatly reduced after autophagy restored. It can be seen that autophagy is pivotal for Aβ and p-Tau metabolism. Once autophagy is impaired, Aβ and p-Tau will deposit in large amounts, which are toxic to brain cells leading to disease development. Unfortunately, Aβ and P-Tau can further provoke defective autophagy, leading to malignant pathological cycles and progression of diseases [48,49].
In recent years, the studies focus on AD-like pathology and autophagy have made a lot of feats in DE. Chen et al. [26] reported enhancing autophagy could reduce tauopathy and thus improve cognitive impairment in db/db mice, so as in high glucose-cultured HT22 cells. In addition, study of Santos et al. [50] observed an increase in tau protein phosphorylation at Ser396 residue in STZ diabetic rats while inducing autophagy partially reversed that effect. Moreover, as reported, the increased Aβ production and cognitive deficits in diabetic mice were reversed by rapamycin (a autophagy activator) treatment [32]. Many other studies have reached similar conclusions [10,51]. Above all, impaired autophagy is a wellestablished participating mechanism in the AD-like pathology of DE and should not be underestimated.
Neuroinflammation and autophagy in DE
In general, inflammatory response may serve as a protective mechanism in the brain, however, excessive inflammation can lead to neuronal damage. Many studies reported higher levels of pro-inflammatory factors, such as TNF-α, IL-1β, in different brain tissues of STZ diabetic rats and mice [52][53][54]. Continuous hyperglycemia under diabetes can trigger activation of the nuclear factor kappa-B (NF-κB) pathway and release of pro-inflammatory factors, resulting in an imbalance between the proinflammatory and anti-inflammatory networks, leading to unrestricted formation of inflammatory mediators, thereby causing neuronal damage [55]. In conclusion, diabetes can significantly induce neuroinflammation, which is an important mechanism of DE.
Recently, the role of autophagy involved in inflammation is gradually recognized, which is also one of the important interactions between autophagy and DE. NF-κB is a transcriptional factor that participates in the modulation of inflammation. Some studies have demonstrated the interplay between autophagy and NF-κB signaling pathway. Overexpressed ATG5, but not the autophagy-incompetent ATG5 mutant K130R in HK-2 cells, could suppressed inflammatory response via inhibition of NF-κB signaling [56]. Another study figured out pharmacological administration of mTOR inhibitors and autophagy stimulators markedly ameliorated inflammatory in vivo [57]. In addition, reduced autophagy may also enhances microglia activation, including secretion of pro-inflammatory cytokines such as Il-1β in vitro [58]. Except for the above cases, autophagy has also been reported to regulate inflammation through other pathways [59].
In a study of Cui et al. [28], they found melatonin (MLT) treatment significantly improved neuroinflammation and ameliorated cognitive impairment in T2DM mice. However, 3-MA treatment increased the neuroinflammation, indicating that the treatment effect of MLT was mediated by autophagy and targeting autophagy enhancement had a therapeutic effect on DE by alleviating neuroinflammation. Summarizing, these studies suggest that autophagy might play a protective role during the course of DE via interaction with neuroinflammation.
Synaptic plasticity and autophagy in DE
Synaptic plasticity is deemed as the neurobiological basis of learning and memory and has long been one of the hottest pots in molecular and cellular neurobiology. Many studies support that diabetes leads to a significant decrease in the number of hippocampal synapses, synaptic degeneration, blurred synaptic gaps, discontinuous synaptic connections, affecting synaptic function, and leading to spatial learning and memory disorders [60,61]. In addition to changes in synaptic structural plasticity, functional plasticity of hippocampal synapses is also impaired in diabetes. Long-term potentiation (LTP) and long-term depression (LTD), believed to be related to the cellular mechanisms of learning and memory, have been the object of intense investigation of synaptic functional plasticity. In the hippocampus of STZ diabetic rats, the magnitude of higher frequencies-induced LTP is strongly reduced [62,63] whereas that of low frequencies-induced LTD is either increased [64] or not changed [63]. In conclusion, DE is closely related to changes in brain synaptic plasticity.
Many studies indicated autophagy is crucial to synaptic plasticity in neurons, once dysregulated, might contribute to brain disorders. Recent studies have shown that autophagy can selectively target synaptic components, regulate the stability of specific proteins in synapses. One step further, this process is also regulated by neuronal activity, thus contributing to the maintenance of specific functions of neurons [65][66][67]. In addition, autophagy is also involved in synaptic plasticity in microglia [68].
Above findings suggest that there is a non-trivial connection between synaptic plasticity and autophagy. In a study of DE, LTP and depotentiation (DPT) were exacerbated by autophagic inhibition in diabetic mice, which indicating impairment of synaptic plasticity. However, no significant change of pair-pulse facilitation (PPF) was recorded in diabetic mice with autophagic suppression compared with the diabetic mice, which implied that presynaptic function was not affected by autophagic inhibition in diabetes [31]. Further investigation is required to fully understand the mechanisms involved in the association of synaptic plasticity and autophagy during DE process.
Oxidative stress and autophagy in DE
In DM, hyperglycemia reduces antioxidant levels and concomitantly increases the production of free radicals, which contributes to tissue damage and leads to alterations in the redox potential of the cell with subsequent activation of redox-sensitive genes [69]. In addition, the brain is particularly sensitive to oxidative damage as a result of its high oxygen consumption rate, abundant lipid content, and relative paucity of antioxidant enzymes as compared to other tissues [70]. A number of studies provided the evidence that the activities of superoxide dismutase (SOD), catalase and antioxidant enzymes were significantly decreased in the brain of DM models [71][72][73][74].
As reported, when reactive oxygen species (ROS) causes intracellular energy imbalance, ROS will activate AMPK [75], and then through AMPK/tuberous sclerosis complex (TSC) 1/TSC2/Rheb (a Ras-related GTP binding protein ) pathway to inhibit mTOR and finally promote autophagy activation [76]. Activated autophagy is a response to oxidative stress and protects the cells from apoptosis [77], whereas impairment of autophagy will cause accumulation of oxidative stress [78]. Kelch-like ECH associated protein 1 (Keap1)/nuclear factor erythroid-2-related factor 2 (Nrf2)/ antioxidant response element (ARE), one of the most important antioxidant pathways, is substantial for resisting ROS-induced damage. Interestingly, P62, as an autophagy substrate, can regulate the Keap1/Nrf2/ARE pathway. Phosphorylated P62 can increase the activity of binding to Keap1, while Keap1 loses its chance to bind to NRF2, then the NRF2 can enter into the nucleus and participate in the regulation of ARE antioxidant elements [79]. As previous study reported, upregulation of autophagy by rapamycin decreased oxidative stress-induced generation of ROS, whereas inhibition of autophagy by 3-MA or by knockdown of ATG7 or BECN1 increased ROS generation, exacerbated oxidative stress-induced reduction of mitochondrial activity, reduced cell viability [80].
Fakih et al. [81] discovered treatment with metformin or pioglitazone in non-obese rat model of prediabetic could reversed oxidative stress markers ameliorated cognitive function, which was owing to the autophagy activation. In addition, following the administration of 5-PAHSA (a novel palmitic acid hydroxy stearic acid) in PC12 cells under diabetic conditions, increased levels of autophagy were observed and the concentration of ROS declined, which implied a neuroprotective role [82]. Zucker Diabetic Fatty (ZDF) rat, a model of T2DM, is characterized by a mutated leptin receptor gene. Talaei et al. [83] observed ZDF brains showed a higher level of reactive oxygen species. Treatment of ZDF brain slices with NaHS, however, enhanced autophagy while counteracting oxidative stress. From the above studies, we can infer that abnormal autophagy in DM is closely related to oxidative stress at the organ level, which makes us full of imagination about the aggravation of oxidative stress caused by down-regulation of autophagy in DE.
Potential Therapeutic Implications of autophagy in DE
In recent years, powered by drug structure and more thorough research on the molecular mechanism and related studies on DE, the studies on DE related therapies have also made some progress. The potential therapeutic implications on DE by targeting autophagy are summarized as follows and presented in detail in Table 1. Ex-4, exendin-4; HGSD, Huang-Gui Solid Dispersion; ZBPYR, ZiBuPiYin recipe; NC, Nicotinate-curcumin; G-CSF, granulocyte colony-stimulating factor; L-NNA, Nv-nitro-L-arginine; MEG3, maternally expressed gene 3; i.p. injection, intraperitoneal injection; s.c. injection, subcutaneous injection
Antidiabetic drugs
Glucagon-like peptide-1 (GLP-1) receptor agonists are a novel type of antidiabetic drug used in clinical practice, which have been proved to possess numerous potential benefits in improving capacity in many diabetic complications by targeting autophagy [84,85]. It has also been reported in studies of DE. Liraglutide, a type of GLP-1 receptor agonist, was figured out could decrease diabetes-induced cell loss and pyknosis and improve cognitive function that acts by increasing mTOR expression via the AMPK and PI3K/Akt pathways [27]. In addition, Kong et al. [86] reported liraglutide promoted autophagy as indicated by enhanced expression of the autophagy markers LC3-II and Beclin 1, decreased expression of p62, and increased formation of autophagic vacuoles and LC3-II aggregates. Meanwhile, liraglutide exhibited neuroprotective effects against diabetesinduced hippocampal neuronal injuries and cognitive impairment via the AMPK/mTOR pathway. Besides, exendin-4 (Ex-4), a kind of GLP-1 mimetics, was also indicated constituting a promising therapy against the chronic complications of T2DM affecting the brain by inducing autophagy through increasing PI3K class III [87]. Metformin is one of the first-line treatments for glycemic control in T2DM patients. Interestingly, beyond its glucose-lowering effect, metformin possesses a variety of other beneficial effects according to emerging clinical and experimental studies, which is mostly due to its function in mediating autophagy activation [88,89]. In a study of Chen et al. [26],12-week-old male db/db mice received consecutive intraperitoneal injection of 200 mg/kg/d metformin or (and) 10 mg/kg/d chloroquine for eight weeks. Metformin attenuated cognitive impairment in db/db mice, reduced p-Tau proteins, restored the impaired autophagy in diabetic mice, all of which were reversed by chloroquine (an autophagic flux inhibitor) treatment via inhibiting of autophagy activity. In high glucose-cultured HT22 cells, metformin enhanced autophagy in a dose-dependent manner. Mechanically, it is proved that metformin enhanced autophagy activity in an AMPK dependent manner.
T1DM patients critically depend on lifelong insulin treatment to survive. On top of that, insulin therapy is expected to control some of the long-term complications associated with extremely high levels of blood glucose under T1DM condition [90]. Interestingly, Santos et al. [50] demonstrated daily subcutaneous injections of insulin could dwindle p-Tau burden of STZ-induced rat model of T1DM, which ascribed to enhanced autophagy function by inhibiting mTOR activity. Briefly, insulin treatment is capable to normalize the alterations induced by T1DM supporting the importance of autophagy signaling.
Altogether, in addition to controlling blood glucose, antidiabetic drugs administration may also be a promising therapy against the chronic complications of diabetes affecting the brain.
Herbal medicine
Herbal medicine has been used for the treatment of diabetes and dementia for thousands of years in China. Modern pharmacological research uncovers that some active components from herbal medicine exert curative effect on DE by targeting autophagy signaling. Huang-Gui Solid Dispersion (HGSD), developed to improve oral bioavailability of Berberine (BBR), was indicated exhibited a good hypoglycemic activity by promoting AMPK activation [91]. Additionally, Xue et al. [92] figured out HGSD significantly inhibited cell apoptosis, enhanced cell autophagy and activated the AMPK/mTOR pathway in the hippocampus of diabetic mice. Moreover, HGSD vastly attenuated apoptotic death, enhanced autophagy and activated the AMPK/mTOR pathway in high glucose-treated SH-SY5Y cells. Accordingly, HGSD could protect against neurotoxicity induced by high glucose through activating autophagy and eventually inhibiting neuronal apoptosis, which was activated by the AMPK/mTOR signaling pathway.
ZiBuPiYin recipe (ZBPYR), a traditional formula of Chinese medicine documented in the book of Bujuji written by Wu Cheng in the Qing dynasty, is derived from Zicheng Decoction and used for the treatment of cognitive impairment. Early reports have indicated that ZBPYR improved the learning and memory process in HFD/STZinduced rat model of T2DM, and regulated the deposition of Aβ in the brain [93]. Recently, Bi et al. [51] confirmed ZBPYR treatment considerably reduced the deposition of Aβ, and ameliorated learning and memory impairments of ZDF rats with chronic psychological stress, which might contribute to inducing autophagy by inhibiting mTOR/ p70S6K signaling.
Curcumin, a major bioactive component of turmeric, has various pharmacological activities including regulation of autophagy [94]. Nicotinate-Curcumin (NC), a novel curcumin derivative derived from nicotinate and curcumin, which has superior water solubility and bioavailability [95]. Study of Gu et al. [29] showed that NC treatment improved cognitive deficit, attenuated neuronal loss and cellular ultrastructure impairment in the CA1 region of T2DM rats. Notably, NC treatment reversed autophagic flux impairment as evidenced by the deceases in LC3-II and p62 protein levels, and autophagosome accumulation in the hippocampal CA1 region of T2DM rats. However, these protective effects of NC were diminished by cotreatment with 3-MA and chloroquine, respectively. These results indicate that NC ameliorates diabetes-induced cognitive function impairment via restoring autophagic flux.
In a nutshell, herbal medicine may be a promising agent for DE prevention and treatment through autophagy activation. Therefore, identifying natural products of autophagy regulators is of remark importance.
Other chemicals
Rapamycin, a well-known autophagy activator, through selectively inhibiting of mTORC1 and thus modulator of the autophagy activity. It has been proved playing a role in improving learning and memory and reducing Aβ and P-tau pathology in the brains of AD mouse model via enhancing autophagy activity [96,97]. Chae et al. [32] reported rapamycin lessened Aβ burden and prevented cognitive impairment in STZ-induced mice model of T1DM, which dues to autophagy enhancement by activating AMPK/mTOR signaling.
Melatonin (MLT) is the main secretory product of the pineal gland. It acts as a regulator of the circadian rhythm. A recent study indicated MLT administration significantly improved neuroinflammation and regulated microglial apoptosis. Furthermore, 3-MA increased the microglial inflammation and apoptosis, indicating that the treatment effect of MLT was mediated by autophagy [28].
G-CSF is a glycoprotein that promotes the production of granulocytes and stem cells in bone marrow as well as their release into the blood stream, which aids in the proliferation and differentiation of neurotrophic factors [98]. Guan et al. [25] figured out administration of G-CSF significantly improved cognitive function in elderly db/db diabetic mice, and this change was likely related to the regulation of autophagy.
Genetic targets
TP53-inducible glycolysis and apoptosis regulator (TIGAR) is an endogenous inhibitor of glycolysis and increases the flux of pentose phosphate pathway (PPP) by regulating glucose 6-phosphate dehydrogenase (G6PD). TIGAR is highly expressed in neurons, and its role in DE was revealed recently. As reported, TIGAR was decreased in the hippocampus of STZ-induced diabetic mice as well as high-glucose-treated hippocampal primary neurons. Importantly, overexpression of TIGAR ameliorated STZinduced cognitive impairment in mice and reduced cell apoptosis. Furthermore, enhancing the expression of TIGAR rescued high glucose-induced autophagy impairment. Nitric oxide synthase 1 (NOS1), a negative regulator of autophagy, was also inhibited by overexpression of TIGAR. However, inhibition of autophagy abolished the protective effect of TIGAR [30]. Therefore, TIGAR may have a therapeutical effect via upregulation of autophagy in DE.
In recent years, long noncoding RNAs (lncRNAs) have been identified to be associated with diabetes and its complications [99]. Maternally expressed gene 3 (MEG3), a lncRNA gene localized at chromosome 14q32, is widely expressed in several normal tissues [100]. Wang et al. [101] observed that MEG3 was significantly downregulated in STZ-induced diabetic rats. MEG3 overexpression noticeably improved diabetes-induced cognitive dysfunctions, accompanied by promoting Mitophagy. Conversely, knockdown of MEG3 showed opposite effects.
However, autophagy associated genetic targets in DE, especially microRNAs (miRNAs) and transcription factors, are so far not fully understood and needs further investigation.
Conclusion and prospect
A growing number of studies point to the dysregulation of autophagy in DE, which is associated with DE progressing. In addition, the autophagy plays a key role in AD-like pathology, neuroinflammation, synaptic plasticity and oxidative stress, all of which may mediate its effect on DE. According to previous studies, DE related therapies by targeting autophagy have also made some progress. However, such autophagy-targeted therapy applying for DE remained poorly investigated. Therefore, a deeper and more comprehensive understanding of the autophagy-targeted therapeutic approaches in DE is needed in the near future. | 5,707.8 | 2022-04-01T00:00:00.000 | [
"Medicine",
"Biology"
] |
Solid pseudopapillary neoplasms of the pancreas are dependent on the Wnt pathway
Solid pseudopapillary neoplasms (SPNs) are rare and relatively indolent tumors of the pancreas. While primary SPNs can be surgically resected, there are currently no therapies available for patients with advanced stage disease. Given that these tumors frequently carry CTNNB1 hotspot (recurrently mutated loci in a gene) mutations resulting in β‐catenin nuclear accumulation, it has been speculated that the Wnt pathway may be a driver in this disease. Here, we present a comprehensive “multi‐omics” study where the genome, transcriptome, and methylome of SPNs were analyzed. We found that SPNs are characterized by a low‐complexity genome where somatic mutations in CTNNB1, present in 100% of the cases, are the only actionable genomic lesions. Compared to more common subtypes of pancreatic tumors (adenocarcinomas and pancreatic neuroendocrine tumors), SPNs show high expression levels of genes belonging to the Wnt pathway. Their methylome was consistent with an epithelial cell origin and a general upregulation of Wnt pathway genes. Clinical studies to evaluate the exquisite sensitivity of SPNs to inhibitors of the Wnt pathway are warranted.
Introduction
Solid pseudopapillary neoplasms (SPNs) are rare pancreatic tumors of unknown etiology, accounting for 1% of all pancreatic exocrine neoplasms. SPNs typically present as large, solitary, well-circumscribed lesions with indolent clinical course and a low propensity to metastasize (Klimstra et al., 2000;Ren et al., 2014). Although they are commonly managed surgically, some SPNs can exhibit a more aggressive behavior and metastasize. Currently, there is no consensus on effective systemic treatments for malignant SPNs, and given the rarity of advanced disease, prospective clinical trials testing novel therapies have not been performed as yet.
Solid pseudopapillary neoplasms are characterized by the presence of somatic CTNNB1 exon 3 hotspot mutations (Abraham et al., 2002;Guo et al., 2017;Tanaka et al., 2001;Wu et al., 2011), leading to stabilization and nuclear localization of b-catenin, which can be detected by immunohistochemistry (Tanaka et al., 2001). Given these premises, the role of the Wnt pathway in SPN development has been suggested. The Wnt pathway is a signal transduction cascade that under normal physiological conditions regulates development and stemness but has also been tightly associated with multiple growth-related pathologies and cancer (Nusse and Clevers, 2017). A key component of the Wnt pathway is the protein b-catenin encoded by the gene CTNNB1, which regulates transcription of downstream target genes (e.g., LEF1, AXIN2). Hotspot mutations in CTNNB1 can cause abnormal accumulation of nuclear b-catenin through stabilization of the protein and eventually constitutive activation of the pathway.
Here, we assessed whether SPNs are dependent on the Wnt signaling pathway and performed a comprehensive "multi-omics" profiling of SPNs collected at our institution during the last two decades to define their repertoire of somatic mutations and copy number alterations, the transcriptional activation of the Wnt pathway and their methylation profiles.
Cases
Patients with written informed consent for research that had a diagnosis of SPN treated at Memorial Sloan Kettering Cancer Center (MSKCC) were identified from our institutional database. Clinicopathological characteristics of the SPN patients are shown in Table 1. Electronic medical records were retrospectively reviewed for data on patient demographics, pathology, presentation (benign versus malignant SPN), treatment (surgical and systemic therapies), and outcomes. In addition, pancreatic adenocarcinomas (ADCs) and pancreatic neuroendocrine tumors (PNETs) were identified as controls. All pathology was reviewed by gastrointestinal pathologists at MSKCC experienced in the diagnosis of SPN. Approval for data collection and analysis was obtained from the MSKCC Institutional Review Board. The study conforms to the guidelines set by the Declaration of Helsinki.
Immunohistochemistry
Immunohistochemical analysis for b-catenin (Clone 14, 1 : 200; BD Transduction, San Jose, CA) was performed on 4-lm-thick sections from representative formalin-fixed, paraffin-embedded SPN tissue blocks, as previously described (Basturk et al., 2016). Positive and negative controls were included in each slide run. The expression of b-catenin was assessed in the membrane and cytoplasmic and nuclear subcellular compartments, and considered abnormal if cytoplasmic and nuclear accumulation were present.
Whole-exome sequencing analysis
DNA samples extracted from 14 flash-frozen SPNs and matched normal tissues were subjected to wholeexome sequencing at the MSKCC Integrated Genomics Operation as previously described (Ng et al., 2017). Briefly, raw sequence reads were aligned to the reference human genome GRCh37 using the BURROWS-WHEELER ALIGNER (BWA 0.7.15) (Li and Durbin, 2009). Local realignment, duplicate read removal, and base quality score recalibration were performed using the GENOME ANALYSIS TOOLKIT (GATK 3.7) (McKenna et al., 2010). Somatic single nucleotide variants (SNVs) were called using MUTECT (1.1.7) (Cibulskis et al., 2013), and small insertions and deletions (indels) were identified using STRELKA (1.0.15) (Saunders et al., 2012), VARSCAN2 (2.3.7) (Koboldt et al., 2012), LANCET (1.0.0) (Narzisi et al., 2018), and SCALPEL (0.5.3) (Narzisi et al., 2014) and further curated by manual inspection. SNVs and indels outside of target regions were filtered out, as were SNVs and indels for which the variant allele fraction (VAF) in the tumor sample was < 5 times that of the paired normal VAF as previously described (Ng et al., 2017;Weigelt et al., 2018). Finally, SNVs and indels found at > 5% global minor allele frequency in dbSNP (build 137) and > 5% global allele frequency in EXAC (0.3.1) were discarded. Somatic copy number alterations and loss of heterozygosity were obtained using FACETS (Shen and Seshan, 2016). The cancer cell fractions (CCF) of all mutations were computed using ABSOLUTE (1.0.6) (Carter et al., 2012). A mutation was classified as clonal if its probability of being clonal was > 50% ( Landau et al., 2013) or if the lower bound of the 95% confidence interval of its CCF was > 90% (Ng et al., 2017;Weigelt et al., 2018). Mutations that did not meet the above criteria were considered subclonal. A combination of in silico functional predictors was used to define the potential functional impact of each missense SNV as previously described (Martelotto et al., 2014;Ng et al., 2017). Mutation hotspots were assigned according to Chang et al. (2016). CTNNB1 mutation frequencies were assessed in 10 100 common cancers from The Cancer Genome Atlas (TCGA) (Bailey et al., 2018;Gao et al., 2013), including 175 pancreatic ADCs. In addition, mutational data from 8 SPNs from Wu et al. (2011) and 344 non-SPN pancreatic tumors, including 23 acinar cell carcinomas from Jiao et al. (2014), 98 PNETs from Scarpa et al. (2017), and 24 cystic tumors of the pancreas Wu et al. (2011). The mutational data were retrieved from cBioPortal (Gao et al., 2013). CTNNB1 mutation and hotspot mutation frequencies were assessed following exclusion of hypermutated cases, defined as cancers harboring more than 1000 nonsynonymous mutations, microsatellite-unstable, or harboring POLE or POLD1 exonuclease domain mutations, as previously described . Mutation diagrams ('lollipop' plots) were generated using Muta-tionMapper on CBIOPORTAL (Gao et al., 2013) and manually curated.
Gene expression analysis
Total RNA extracted from nine SPNs, seven pancreatic ADCs, and 8 PNETs was subjected to expression analysis of 240 selected genes using the nCounter platform from Nanostring Technologies, Seattle, WA (Table S3). The raw counts were normalized using the nSolver analysis software. We performed background subtraction using the negative control and normalized the background corrected counts using the housekeeping genes ACTB, MRPL19, PSMC4, RPLP0, and SF3A1. Comparison between SPN samples and ADCs or PNETs was done using the R/BIOCONDUCTOR LIMMA package, and genes with P values < 0.05 were considered as significantly differentially expressed.
Genome-wide methylation analysis
DNA extracted from 13 SPNs was subjected to Illumina Infinium Methylation 850K array profiling as previously described (Chiang et al., 2016). The R/BIO-CONDUCTOR MINFI package was used to process the raw files and obtain the normalized beta values. The methylation data in the form of beta values of cells of epithelial (n = 22), fibroblast (n = 10), and muscle cell (n = 6) origin were downloaded from encyclopedia of DNA elements (ENCODE) project (ENCODE Project Consortium et al., 2007) and processed as described above. To avoid the confounding effects of gender, probes mapping to sex chromosomes were discarded while batch effect was removed using the COMBAT method (Johnson et al., 2007) implemented in the R/ BIOCONDUCTOR package SVA. Probes which were differentially methylated between ENCODE samples of epithelial, fibroblast, and muscle cell origin were identified using the Kruskal-Wallis test and an FDRadjusted P-value < 0.1 (Table S4). The SPN methylation data were projected onto the first two principal components estimated using the ENCODE samples. Probes of the Wnt pathway found to be differentially methylated between SPNs and ENCODE samples were subjected to hierarchical cluster analysis using Pearson correlation and Ward's distance.
Statistical analysis
Using the transcriptomic data, genes differentially expressed between SPNs and ADCs or PNETs were identified using a linear model fitted to the expression data. We considered genes with a P-value < 0.05 and an absolute fold change value > 2 as statistically significant. In the case of methylation data, the data were filtered by identifying probes with multimodal distributions of beta values in the ENCODE dataset. A mixture of Gaussian distributions was fitted to the pooled data using the R/BIOCONDUCTOR package MCLUST. Probes which were differentially methylated between ENCODE samples of epithelial, fibroblast, and muscle cell origin were identified using the Kruskal-Wallis test and an FDR-adjusted P-value < 0.1. The SPN methylation data were projected onto the first two principal components estimated using the ENCODE samples. All hypothesis tests were unpaired, and Pvalues were two-sided. Unless otherwise stated, all computations were performed in R/BIOCONDUCTOR.
Activation of the Wnt pathway in SPNs
From a genomics standpoint, SPNs appear to be driven solely by CTNNB1 activating somatic mutations, which result in nuclear accumulation of the protein (Polakis, 1999). Accordingly, we detected strong b-catenin protein expression in both cytosol and nuclei of all SPNs analyzed (Fig. 1D). This, in turn, initiates a transcriptional program primed to activate the Wnt pathway (Mosimann et al., 2009). To investigate the components of the Wnt signaling pathway activated in SPNs, we performed a differential gene expression analysis of nine SPNs, four of which were metastatic, seven pancreatic ADCs, and eight PNETs using the Nanostring platform (Table S3). Compared to ADCs and PNETs, SPNs displayed significantly higher expression levels of genes encoding components of the Wnt pathway, including DKK4, which has recently been detected by mass spectrometry in SPNs (Park et al., 2015), and direct TCF/b-catenin target genes such as LEF1 (Aoki et al., 1999) or AXIN2 (Jho et al., 2002) ( Fig. 2A-D, Fig. S2). Other genes whose expression has been described to be induced by Wnt/b-catenin signaling activation such as LGR5, ASCL2, or CCND1 were also expressed at significantly higher levels in SPNs (Fig. S2).
Methylome analysis of SPNs
Given the unknown histogenesis of SPNs, we analyzed the global methylation profiles of 12 of the 14 SPNs analyzed by whole-exome sequencing and compared their methylation patterns with those of normal cells of various anatomical sites from the ENCODE database (ENCODE Project Consortium et al., 2007). The majority of the SPNs profiled in this study clustered with epithelial cells (Fig. 3A). We further performed a differential analysis between ENCODE samples of epithelial origin and SPNs, which identified 2511 differentially methylated probes (Table S3). Probes that were significantly differentially methylated between samples of epithelial, fibroblast, and muscle cell origin in the ENCODE database were mapped to genes in the Wnt pathway and showed differential methylation in the gene bodies (intronic and exonic areas of a gene), which, based on ontology, would have resulted in upregulation of the respective transcript (e.g. WNT5A). Conversely, hypermethylated probe sets corresponded with genes whose transcripts were downregulated in SPNs (e.g., CD44; Fig. 3B). Two exceptions were probes mapping to ZIC2 and WNT5B, which were found to be hypermethylated in SPN compared to ENCODE samples. Unlike CD44, these genes had a significantly higher expression in SPNs compared to ADCs or PNETs. Also, the methylation pattern is not unexpected, given that the hypermethylated probes mapped to the 3 0 UTR of the corresponding gene, a phenomenon not uncommonly associated with overexpression of the target gene.
Discussion
Here, we report a multi-omics analysis of SPNs compared to the other two more common subtypes of pancreatic cancer, ADC and PNET. In agreement with the existing literature, we found that SPNs have low genomic complexity and are characterized by the invariable presence of CTNNB1 exon 3 mutations. Accordingly, we found consistent increased expression of genes encoding components of the Wnt pathway in these tumors. Nuclear b-catenin accumulation promotes the expression of a panel of Wnt target genes codifying for proteins involved in a myriad of cell processes. Among them, some codify components of the Wnt/b-catenin pathway itself such as LEF1, AXIN2, or RNF43, which induce a positive feedback loop that enhances signaling activation (Zhan et al., 2017). Here, we observed that SPNs with mutations in CTNBB1 that provoke constitutive accumulation of nuclear b-catenin express higher levels of some of these Wnt target genes that are also Wnt pathway components such as LEF1, AXIN2, and RNF43 (Fig. 3). We also observed that other genes codifying components of the Wnt pathway are highly expressed in SPN than ADC, such as ligands (WNT5A, WNT2B, or RSPO4), receptor components (LRG6 or FZD10), or other key proteins for signal transduction such as APC. Although these are not formally demonstrated to be Wnt/b-catenin pathway target genes, their higher expression could suggest and enhanced activation of the pathway additional to that promoted by CTNNB1/b-catenin activating mutations.
The lack of somatic genetic alterations other than CTNNB1 mutations and low levels of genomic complexity may provide an explanation for the indolent behavior of SPNs, akin to colorectal polyps associated with familial adenomatous polyposis in patients with germline APC mutations developing multiple KRAS wild-type, benign tumors where a dysfunctional APC can be the only driver (Leoz et al., 2015;Takane et al., 2016). In mice, activation of b-catenin is indeed sufficient to produce large pancreatic tumors that resemble human SPNs both morphologically and by immunohistochemical analysis (Heiser et al., 2008).
Of note, a recent report identified also inactivating mutations of the epigenetic regulators KDM6A, TET1, and BAP1 to be associated with metastatic spread (Amato et al., 2019). Whether these alterations are also playing a role in regulating the expression of Wntdependent genes remains to be elucidated.
While inhibition of the Wnt pathway may be an intuitive therapeutic option for this disease, its rarity and the lack of available preclinical models are clear limitations in the advancement toward an effective treatment for metastatic SPNs. Furthermore, the more clinically advanced Wnt pathway inhibitors target components that are upstream of b-catenin transcriptional activity and would therefore be futile for the treatment of SPN patients.
Conclusions
Taken together, our data suggest that SPNs have simple genomes and appear to be uniformly driven by CTNNB1 exon 3 mutations with consequent activation of the Wnt signaling. Future drugs designed to target directly b-catenin may have therapeutic potential in this disease. Heatmap of methylation data from SPN samples profiled in this study and ENCODE samples of epithelial origin. Probes found to be differentially methylated (FDR < 0.1) between SPN and ENCODE samples were mapped to the Wnt pathway. With few exceptions, the probes mapped to gene bodies where hypomethylation corresponded to upregulation of the corresponding transcript. The two exceptions were probes mapping to ZIC2 and WNT5B which were located in 3 0 UTR regions where hypermethylation also corresponded to upregulation of the upstream gene.
Supporting information
Additional supporting information may be found online in the Supporting Information section at the end of the article. Fig. S1. Copy number profiles of SPNs analyzed in this study. Fig. S2. Differential gene expression analysis of SPNs, ADCs and PNETs. Table S1. Whole-exome sequencing statistics. Table S2. Nonsynonymous somatic mutations identified in SPNs using whole-exome sequencing. Table S3. Genes in the Wnt pathway assessed by Nanostring nCounter. Table S4. Probes differentially methylation between SPN samples (this study) and ENCODE samples of epithelial origin. | 3,677.8 | 2019-07-03T00:00:00.000 | [
"Medicine",
"Biology"
] |
Leptoquark on $P\to \ell^{+} \nu$, FCNC and LFV
Motivated by the disagreement between the experimental data and lattice calculations on the decay constant of the $D_{s}$ meson, we investigate leptoquark (LQ) contributions to the purely leptonic decays of a pseudoscalar (P). We concentrate on the LQs which only couple to the second-generation quarks before the electroweak symmetry breaking and we discuss in detail how flavor symmetry breaking effects are brought into the extension of the standard model after the spontaneous symmetry breaking. We find that the hermiticity of fermion mass matrices can not only reproduce the correct Cabibbo-Kobayashi-Maskawa and Maki-Nakagawa-Sakata matrices, but also reduce the number of independent flavor mixing matrices and lead to $V^{R}_{f}=V^{L}_{f}$ with $L(R)$ denoting the chirality of the f-type fermion. Accordingly, it is found that the decays $D_{s,d}\to \ell^{+} \nu$, $B^{+}\to \tau^{+} \nu$ and $B_c\to \ell^{+} \nu$ have a strong correlation in parameters. We predict that the decay constant of the $B_c$ meson calculated by the lattice could be less than the experimental data by 23%. Intriguingly, the resultant upper limits of branching ratios for $D\to \mu^{+} \mu^{-}$ and $\tau\to \mu (\pi^0, \eta, \eta', \rho, \omega)$ are found to be around $ 5.1\times 10^{-7}$ and $(2.6, 1.5, 0.6, 7.4, 4.8)\times 10^{-8}$, which are below and close to the current experimental upper bounds, respectively.
As many puzzles such as matter-antimatter asymmetry, neutrino oscillations and dark matter etc are unsolved, it is clear that the standard model (SM) only describes parts of the universe and should be regarded as an effective theory at the electroweak scale. To explore the unknown parts, searching for new physics effects that do not belong to the SM becomes very important. However, since most measurements are eventually resulting from the SM, by naive speculation, the new effects should be small and difficult to be found out. Therefore, where we can uncover the new physics should be addressed in the first stage to look for new physics. Usually, the rare decays with the suppressed SM contributions are considered to be the good candidates. In addition, through precision measurements, finding a sizable deviation from the theoretical expectation provides another direction to search for the new effects.
Recently, via the observations of D s → ℓ + ν decays, CLEO [1, 2] and BELLE [3] collaborations have measured the decay constant of D s to be f Ds = 274 ± 10 ± 5 MeV (CLEO) , where the result by CLEO is the average of µ + ν and τ + ν modes, while the BELLE's one is only from µ + ν. By combining the radiative corrections from D s → γℓν, the average of the two data in Eq.
More information on the measurement from other experiments can be found in Ref. [4].
Furthermore, if we compare the measured value with the recent lattice calculation [5], given by f Ds = 241 ± 3 MeV (HPQCD+UKQCD) , we see clearly that 3.2 standard deviations from data have been revealed in the purely leptonic D s decays [4,6]. That is, a correction of 10% to f Ds is needed. Does the discrepancy indicate new physics or the defeat of the theory? Although the answer to the question is not conclusive yet, by following the new CLEO's result on the decay constant of D + [7]: which is in a good agreement with the lattice calculation [5]: it seems to tell us that the lattice improvement may not be large enough to singly compensate the quantity that is more than 3 standard deviations in f Ds .
Inspired by the above interesting measurements, the authors in Ref. [8] propose that new interactions associated with leptoquarks (LQs) might resolve the anomaly of f Ds . However, the assumption adopted by Ref. [8] that the LQs only couple to the second-generation quarks seems to be oversimplified. It has been known that up-type and down-type quark mass matrices can not be diagonalized simultaneously. Therefore, if the LQ couples to upand down-type quarks at the same time, after the spontaneous symmetry breaking (SSB), the flavor mixing matrices to diagonalize the quark mass matrices will be introduced so that intergenerational couplings in quarks become inevitably [9]. To generalize the approach of Ref. [8], in this paper, besides we discuss how flavor mixing effects influence the decays P → ℓ + ν and how the number of free parameters can be diminished, we also investigate the implications of LQ interactions on the processes with flavor changing neutral current (FCNC) and lepton flavor violation (LFV). We note that the effects of the charged Higgs with a large tan β in the ordinary two-Higgs-doublet models are destructive contributions to the SM [4,10], more complicated multi-Higgs doublets are needed to get the enhancement [8]. In addition, other models such as R-parity violation in supersymmetric models might also provide the solution [11]. However, due to the parameters in different quark flavors having no correlation, the models have a less predictive power.
In order to examine the effects of a light LQ in a systematic way, the LQ model is built based on the gauge symmetries SU(3) C × SU(2) L × U(1) Y . To simply display the role of the LQ on the low energy leptonic decays, FCNC and LFV, the LQ in this paper is limited to the SU(2) L singlet S 1 with the charge of -1/3. To avoid the proton decays, the LQ does not couple to diquarks. Indicated by the inconsistent results in the D s leptonic decays, we consider that before the SSB, the LQ only couples to the second-generation quarks and the interactions in the weak eigenstates are given as [8,12] L LQ = Ē g L iτ 2 P R Q c 2 +lg R P L c c S 1 + H.c. , = l g L P R c c −ν ℓ g L P R s c S 1 +lg R P L c c S 1 + H.c. , where g L(R) denotes a 3-component effective coupling and is represented by g T α = (g αe , g αµ , g ατ ) with α = L and R, Q T 2 = (c, s), f c = Cγ 0 f * = Cf T (C = iγ 2 γ 0 ) describes the anti-fermionic state, τ 2 is the 2nd Pauli matrix, E T = (ν ℓ , ℓ) with ℓ = e, µ, τ , and P L(R) = (1 ∓ γ 5 )/2. Since the flavor mixing effects are governed by the Yukawa sector, we write the sector as where H is the SM Higgs doublet andH = iτ 2 H * . Implicitly, the flavor indices are suppressed. In addition, it is known that the flavor changing effects in the SM only appear in processes related to the charged weak currents, while the weak interactions in weak eigenstates are expressed by with g being the gauge coupling of SU(2) L . After introducing the relevant pieces, in the following we discuss after the SSB how the flavor mixing effects are brought into the effective interactions and how they can be controlled through the notable patterns of mass matrices.
It has been known that Eq. for neutrinos, due to the observations of the neutrino oscillation, we consider that neutrinos are massive particles. We will show that the induced effects such as the Maki-Nakagawa-Sakata (MNS) matrix [13] do not explicitly emerge after summing up the three neutrino species. To diagonalize the mass matrices of fermions, we introduce the unitary matrices where p(w) represents the physical (weak) state and α denotes the left or right-handness.
Straightforwardly, Eq. (8) becomes Here, [14] and MNS matrices, respectively. Clearly, besides the CKM matrix, if we regard the neutrinos as massive particles, we bring in a new mixing matrix for leptons. However, does V M N S have any effects on the low energy leptonic decays? The answer to the question in the SM is obvious. Since the neutrinos in hadronic decays are regarded as missing particles and are not detected, when one calculates the decay rate for the process, it is needed to sum up all neutrino species and the squared amplitude is associated with respectively. Clearly, we see that V M N S appears in Eq. (11). Nevertheless, like the SM, the explicit form of V M N S can be rotated away by transforming the physical neutrino states to flavor states. Meanwhile, unlike the case in the SM where ν ℓ in a process is always associated with the corresponding charged lepton ℓ, in the LQ model, for each charged lepton inevitably we have to consider all possible neutrino flavors.
Using Eqs. (10) and (11) with removing V M N S , the effective Hamiltonian for P → ℓ + ν related decays are found to be where we have used V as V CKM , the indices i, j, k and ℓ denote the possible flavors, are 3 × 3 matrices, and σ µν = i[γ µ , γ ν ]/2. Although tensor-type interactions could be generated in Eq. (12), since they cannot contribute to two-body leptonic decays, hereafter we will not discuss them further. Therefore, there are two main types of four-fermion operators , which is the same as the SM, and the other is (S ± P ) × (S ± P ). For P → ℓ + ν decays, we will see that the former will lead to the helicity suppression, whereas the latter does not. On the contrary, for D →Kℓ + ν decays where the lattice calculations have been consistent with the experimental data, the latter has the helicity suppression whereas the former does not. Consequently, D →Kℓ + ν will directly give strict constraints on the parametersg Lℓ . Since the new physics effects are considered perturbatively, if we only keep the leading effects and neglect the higher order ing α , the partial decay rate for P → ℓ + ν is found to be with m 0 P = m 2 P /(m U + m D ) and where the decay constant f P is defined by Since CP problem is not concerned in this paper, for a further simplification of our numerical analysis, the weak phases will be tuned to zero. Then, X U D ℓ and Y U D ℓ can be shortened as Clearly, X U D ℓ and Y U D ℓ are associated with |g Lℓ | 2 andg * Lℓg Rℓ , respectively. We note that the capital symbol of U(D) denotes the up (down)-type quark in a specific decay. For instance, X cs ℓ and X ud ℓ are for D s and π decays, respectively. Before doing the numerical analysis, we need to know how many free parameters are involved in the model and how to reduce the number of parameters. From Eq. (6), it is obvious that six free parameters from g L and g R are introduced in the original LQ model. [17,18,19]. In other words, the structure of V α U should be similar to V α D . Furthermore, it has been shown that a simple pattern of the mass matrix, proposed by Ref. [20] with could lead to reasonable structures for the mixing angles and CP violating phase in the CKM matrix just in terms of the quark masses. Using the current accuracy of data, the mass patterns of Eq. (18) have been reanalyzed and applied to lepton masses by the authors in Ref. [15]. It is found that the elements of V CKM can satisfy with current accuracy of data and the component of (V M N S ) 13 can be consistent with present experimental constraint as well. Although the phenomenological patterns may not be the general form, due to the support of experiments, the resultant flavor mixing matrices could be taken as a clue to the true mass matrices.
Inspired by the fascinating mass matrices and their results, we speculate that to avoid the restricted patterns shown in Eq. (18), the mass matrices could be extended to those which not only own the main character of Eq. (18) but also provide the relationship between V R f and V L f . Accordingly, we find that the criterion to get a more general property of Eq. (18) could be established if the mass matrices are hermitian. It is worth mentioning that the hermitian mass matrices could be naturally realized in gauge models such as left-right symmetric models [21]. Furthermore, the hermiticity is helpful to solve the CP problem in models with supersymmetry (SUSY) [22], which has an important implication on CP violation in Hyperon decays [23]. With the hermiticity, we obtain the results from the definition of the CKM matrix, intriguingly the number of independent flavor mixing matrices in the quark sector could be reduced to one and the unknown flavor mixing matrix is chosen to be V D for our following analysis.
After setting up the model and the associated parameters, subsequently we study the constraints on the free parameters and their relative implications. Firstly, we discuss the limits of D →Kℓ + ν. As mentioned early, the effects ofg R for D →Kℓ + ν are helicity suppressed. Here we only display the constraints ong L . By the effective Hamiltonian of Eq. (12), the transition matrix element for D →Kℓ + ν can be written as where the sum is to include all neutrino species and the D →K form factors can be parametrized by If the effects of the 2nd order ing L are neglected, a simple expression for D →Kℓ + ν is given by With V U = V V D , the effective coupling (C L † ul ) ℓc (C L dv ) sℓ could be expressed as Since the off-diagonal elements of V D represent the flavor symmetry breaking effects, according to Eq. (18), the diagonal elements of V D are roughly order of unity while the off-diagonal elements are order of m i /m j with j > i [19,20,24]. As a result, X cs ℓ could be written as where G F / √ 2 = g 2 /8m 2 W has been used. From the data [25] and the recent unquenched lattice calculation [27], given by obviously the theoretical calculation is consistent with the experimental value, i.e. we can setg Lℓ as small as possible. In order to sense the order of magnitude of the parameters, we require that new physics effects are only less than 1σ Exp , i.e.
Now, we study the LQ effects on D s → ℓ + ν decays where the disagreement between theory and experiment shows up. In terms of the previous analysis, although the LQ only couples to the second-generation quarks, through the flavor mixing matrices, the LQ could also couple to the quarks of the first and third generations. Therefore, besides D s → ℓ + ν decays, we can also study the processes D d → ℓ + ν and B u → τ + ν, in which the involving parameters are correlated each other. Taking V cs ≈ 1, V cd = −λ ≃ 0.22, V D22 ≈ 1 and neglecting the subleading terms, from Eq. (17) the effects of LQ to D s → ℓ + ν, D d → ℓ ′+ ν and B u → τ + ν can be simplified to be respectively. Clearly, the parameters contributing to D s → ℓ + ν will also affect the decays D d → ℓ ′+ ν and B u → τ + ν. Moreover, since the decay rate for P → ℓ + ν is directly related to the decay constant of the P-meson, to display the new physics effects, we express the connection of the observed decay constant with the lattice calculation to be To explain the anomalous results occurred in D s → (µ + , τ + )ν shown in Eqs. (2) and (3), the new physics at least should enhance f Ds by 10%, that is, X cs µ(τ ) + Y cs µ(τ ) should be around 20%. Due to X cs ℓ < 8%, we see that the dominant contributions are from Y cs ℓ . For simplicity, we will ignore the effects of X cs ℓ and adopt Y cs Adopting V U 22 ≈ 1, V D32 ≈ 0.043, V cb ≈ 0.042 and Y cs ℓ ≈ 0.2, we immediately find Y cb ℓ ≈ 0.49. In other words, we predict that the calculation of the lattice on f Bc could have ∼ 23% below the observation of the experiment. According to above analysis, we see clearly that even in the restricted case, where the fermion mass matrices are hermitian, the explanation of the D s puzzle in terms of the LQ remains viable despite constraints from other flavor processes.
With the constraints on the parameters of the LQ model, in the following we study the implications of the LQ effects on the decays associated with FCNC and LFV. Firstly, we discuss the D → µ + µ − decay. It is known that due to the stronger Glashow-Iliopoulos-Maiani (GIM) mechanism [29], the short-distance contributions to D → µ + µ − are highly suppressed in the SM [30] and long-distance effects are small [31]. The decay of D → µ + µ − is definitely a good candidate to probe the new physics effects [32]. According to Eq. (11), we know that the dominant effective Hamiltonian for c → uµ + µ − is from the left-right interference terms and can be written as By combining Eqs. (13), (16), (27) and V U = V V D , the BR for D → µ + µ − can be simplified to be Using Y cs µ ≈ 0.2 and V D12 ≈ −0.57λ, the values of BR with various values of f Latt D are presented in Table I. Interestingly, the LQ predictions satisfy and are close to the current experimental upper bound, given by B(D → µ + µ − )| Exp < 5.3 × 10 −7 [26]. The LQ interactions in Eq. (11) could also contribute to the lepton flavor violating processes. Since the constraints on theg Re are more uncertain, we only pay attention to the decays τ → µ(P, V ), in which the relevant effective Hamiltonian is For the light mesons, u represents the up-quark. By Eq. (13), the BRs for τ → µ(P, V ) are given by respectively. To calculate the modes associated with η and η ′ mesons, we employ the quarkflavor scheme in which η and η ′ physical states could be described by [33,34] with φ being the mixing angle, η q = (uū + dd)/ √ 2 and η s = ss. Accordingly, the decay constant of η (′) associated withūγ µ γ 5 u current is given by f η (′) = cos φ(sin φ)f ηq . For numerical calculations, we have to know the direct bound on the free parameterg Rτ /m LQ .
From Y cs ℓ of Eq. (27) and the result of Eq. (26), the information can be obtained immediately as With Y cs ℓ ≈ 0.2, the direct bound ong Rℓ /m LQ is found to bẽ g Rℓ m LQ ≤ 1.6 × 10 −3 m ℓ .
By taking φ ≈ 39 • , f ηq ≈ 140 MeV [34], f π = 130 MeV, f ρ(ω) = 216(187) MeV, V D12 ≈ −0.57λ and the above resultant upper limits, the values of BRs for τ → µ(π 0 , η, η ′ , ρ 0 , ω) decays are displayed in Table II. We see that interestingly the contributions of the LQ to lepton flavor violating processes are below the current experimental upper bounds. In addition, the predictions on the decays τ → µ(η, ρ, ω) are very close to the current upper bounds. In summary, to understand the inconsistency between the experimental data and lattice calculations in f Ds , we have extended the SM to include the LQ interactions which involve only the second-generation quarks above the electroweak scale. After the SSB, the flavor mixing matrices introduced to diagonalize the mass matrices of quarks can make the LQ couple to the first and third generations. We have derived that if the mass matrices of fermions are hermitian in which the obtained CKM and MNS matrices can be consistent with data, besides having V R f = V L f ≡ V f , the independent flavor mixing matrices are further reduced to one, say V D . Accordingly, it is found that the effects of the LQ on the decays D s,d → ℓ + ν, B + → τ + ν and B c → ℓ + ν are correlated together. With the obtained constraints, we predict f Exp Bc ≈ 1.23f Latt Bc . Moreover, the upper limits of BRs for D → µ + µ − and τ → µ(π 0 , η, η ′ , ρ, ω) are found to be around 5.1 × 10 −7 and (2.6, 1.5, 0.6, 7.4, 4.8) × 10 −8 , respectively. Interestingly, all predicted values are below and close to the current experimental upper bounds. | 4,992.4 | 2008-07-15T00:00:00.000 | [
"Physics"
] |
On the Potential of Preprints in Geochemistry: The Good, the Bad, and the Ugly
: In recent years, the pace of the dissemination of scientific information has increased. In this context, the possibility and value of sharing open access (OA) online manuscripts in their preprint form seem to be growing in many scientific fields. More and more platforms are especially dedicated to free preprint publishing. They are published, non-peer-reviewed scholarly papers that typically precede publication in a peer-reviewed journal. They have been a part of science since at least the 1960s. In 1990, Tim Berners-Lee created the World Wide Web to help researchers share knowledge easily. centralized web-based arXiv arXiv is the most influential preprint of physics, mathematics and computer in many bioRxiv for biological sciences) towards OA publishing, and be publisher- or community-driven, profit or not for profit, and based on proprietary or free and open source software. A range of discipline-specific or cross-domain platforms now exist, with exponential growth these last five years. While preprints as a whole still represent only a small proportion of scholarly publishing, a strong community of early adopters is already beginning to experiment with such value-enhancing tools in many more disciplines than before. The two main options for geochemists are EarthArXiv and ESSOAr. A “one size fits all” model for preprints would never work across the entire scientific community. The geochemistry community needs to develop and sustain their own model.
In recent years, the pace of the dissemination of scientific information has greatly increased [1]. In this context, the possibility and value of sharing open access (OA) online manuscripts in their preprint form are growing in many scientific fields [2]. More and more platforms are becoming dedicated to free preprint sharing. Preprints? What? Also sometimes referred to as e-prints, they are digitally shared, non-peer-reviewed scholarly articles that typically precede publication in a peer-reviewed journal [3]. They have been a part of science since at least the 1960s [4]. In 1990, Tim Berners-Lee created the World Wide Web to help researchers share knowledge easily. A few months later, in August 1991, a centralized web-based network, arXiv (https://arxiv.org/, pronounced 'är kīv' like the word "archive", from the Greek letter "chi"), was created. arXiv is arguably the most influential preprint platform and has supported the fields of physics, mathematics, and computer science for over 30 years. After a hiatus of about 15 years, preprint platforms have become popular in many disciplines (e.g., bioRxiv for biological sciences) due to the increasing drive towards OA publishing, and can be publisher-or community-driven, profit or not for profit, and based on proprietary and open source software. A range of discipline-specific or interdisciplinary platforms now exist (e.g., [5]), and these have had exponential growth these last five years, as highlighted in Figure 1. While preprints as a whole still represent only a small proportion of scholarly publishing (e.g., 2% of the biomedical literature published every month [6]), a strong and diverse community of early adopters is already beginning to experiment with integrated value-enhancing tools in many more disciplines than before (e.g., peer review overlay platforms). In general, the Earth science community and its subcommunities have perhaps been a little slow in adopting the use of preprints. Several dedicated servers now exist, including EarthArXiv, ESSOAr, and paleorXiv, as well as InarXiv, which researchers use to share some research in the Indonesian language.
The reasons for this general growth in the importance, popularity, and acceptance of preprints are numerous. One of the reasons is the delay in the peer-review process and the subsequent publication ( Figure 2), which can also impact the career progress of researchers. This is a generic problem in scholarly publishing and affects the geochemistry community as much as other disciplines. Some research has shown that preprints tend to be of similar quality to their final published versions in journals [7]. This raises major issues around the "added-value" of both the publishing and peer-review processes, which continue to cost 10s of billions of dollars in public and private money each year [8]. In geochemistry, we know that around US$7,000,000 each year is spent on open access to journals [9], with virtually none of this being reinvested into the community itself or the community being reimbursed. Given the immense value of preprints, reinvesting this value into more sustainable community-led non-profit ventures, such as EarthArXiv, is of great potential. The reasons for this general growth in the importance, popularity, and acceptance of preprints are numerous. One of the reasons is the delay in the peer-review process and the subsequent publication ( Figure 2), which can also impact the career progress of researchers. This is a generic problem in scholarly publishing and affects the geochemistry community as much as other disciplines. Some research has shown that preprints tend to be of similar quality to their final published versions in journals [7]. This raises major issues around the "added-value" of both the publishing and peer-review processes, which continue to cost 10s of billions of dollars in public and private money each year [8]. In geochemistry, we know that around US$7,000,000 each year is spent on open access to journals [9], with virtually none of this being reinvested into the community itself or the community being reimbursed. Given the immense value of preprints, reinvesting this value into more sustainable community-led non-profit ventures, such as EarthArXiv, is of great potential. There are a number of general benefits but also potential drawbacks to preprint sharing. The possible benefits of preprint sharing for geochemists include: However, the preprint model still has some possible drawbacks. For example, the increased dissemination effect has the potential to be used to promote non-reproducible scholarship or fake news and adds an extra potential burden on journalists reporting on new research [11], as well as preprint platform moderators. According to Altmetric, the most-shared research article ever at the time of writing is a bioRxiv preprint about the COVID-19 virus [12]. This article has since been withdrawn due to flaws in the research. However, retractions are common even in peer-reviewed scholarly journals, so this is not necessarily a trait exclusive to preprints; in fact, preprints actually tend to make the process of correcting the scholarly record far simpler. The preprint model also increases the scientific community's responsibility by not legitimizing preprint publications that lack scientific rigour. Thus, the burden is on researchers, and indeed everyone, to think critically about the research they read, share, and re-use, whether it has been peer-reviewed or not.
Despite this development, there is still some apparent resistance to preprints among geochemists and the wider geoscience community. One major hurdle is the question of their citation. Some researchers have argued that preprints are no different from other grey literature due to their preliminary existence. It is a direct consequence of our academic culture, where typically only work that has been explicitly peer-reviewed and published in a scholarly journal is usually cited. Another There are a number of general benefits but also potential drawbacks to preprint sharing. The possible benefits of preprint sharing for geochemists include: rapid sharing of research results, particularly during outbreaks (e.g., , where there remains a clear role for the wider geoscience community [10]; -visibility and accessibility (i.e., not placed behind a paywall); -sharing diverse types of outputs such as data, research code, or methods; -extra feedback and peer-review; -small or even non-existent costs for authors; -assignment of a digital object identifier (DOI) so that the paper is known and stored in the digital world; -the possibility of setting research precedents (preventing scooping); -work can be reported on internationally and then be improved (i.e., overall quality, integrity, and reproducibility of research outputs) and released later; -incentivizes collaboration; -authors retain full copyright to their article.
However, the preprint model still has some possible drawbacks. For example, the increased dissemination effect has the potential to be used to promote non-reproducible scholarship or fake news and adds an extra potential burden on journalists reporting on new research [11], as well as preprint platform moderators. According to Altmetric, the most-shared research article ever at the time of writing is a bioRxiv preprint about the COVID-19 virus [12]. This article has since been withdrawn due to flaws in the research. However, retractions are common even in peer-reviewed scholarly journals, so this is not necessarily a trait exclusive to preprints; in fact, preprints actually tend to make the process of correcting the scholarly record far simpler. The preprint model also increases the scientific community's responsibility by not legitimizing preprint publications that lack scientific rigour. Thus, the burden is on researchers, and indeed everyone, to think critically about the research they read, share, and re-use, whether it has been peer-reviewed or not.
Despite this development, there is still some apparent resistance to preprints among geochemists and the wider geoscience community. One major hurdle is the question of their citation. Some researchers have argued that preprints are no different from other grey literature due to their preliminary existence. It is a direct consequence of our academic culture, where typically only work that has been explicitly peer-reviewed and published in a scholarly journal is usually cited. Another argument is that a preprint might bring confusion in citation when it has been published formally in a journal. Moreover, some authors report that manuscripts are rejected because similarity-check software shows high similarity between submitted and preprint versions. The extent of these issues remains poorly understood but should be clarified in journal policies and on preprint platforms. However, we believe that it is our duty as scholars, and readers in general, to think critically of anything that we are reading, irrespective of whether it has been peer-reviewed or not.
"It should be noted that reference 15 is a non-peer reviewed version. I suggest referring to a peer-reviewed publication from another source."
Reviewer #2
The sustainability of geoscience preprint systems is always questionable, as we can see through popular, not-for-profit, community-driven preprint servers (e.g., INA-Rxiv) that currently face closure because of financial troubles [13] or are moving towards other economic options (e.g., EarthArXiv). This highlights the issue with the sustainability of these services, which should perhaps not be an issue considering how much money is currently being spent on less-efficient and less-sustainable for-profit systems (i.e., in commercial publishing activities, around US$7,000,000 has been spent per year these last years) [9]. Governments and funders desperately need to reconsider their focus on where they allocate funds in decisions related to scholarly communication [14]. Learned societies might also have a role to play in supporting preprints more in the future. For example, the Geological Society of America and the Geological Society of London both indirectly support preprints but have not yet financially or formally supported any of the community-led initiatives around them. Part of the issue here is that there exists a general fear that preprints might threaten the sustainability of traditional journals, which geoscientific learned societies still derive a substantial portion of their revenue from.
In the Earth sciences, only a few articles are submitted as preprints every month [15,16], so we cannot really provide much insight into their specific use at the present. However, what about preprints in Geochemistry? As stated by Pourret et al. [17] and Pourret [18], the preprint model is unfortunately still perhaps little-known and is not routinely used by geochemists. A small overview of preprints available in geochemistry using the keywords "Earth science category and Geochemistry", "Geochemistry and Petrology", "Biogeochemistry and Cosmochemistry sub-categories", and "Geochemistry category" (depending on servers) shows that less than 250 articles in total have used this model in the last three years (Table 1). This number is very low compared to the 9326 and 9196 articles published in the field of geochemistry in 2018 and 2019, respectively [9]. However, as stated by Pourret [18], a majority of the journals in geochemistry also have a green colour according to the SHERPA/RoMEO grading system, indicating that preprint (and the peer-reviewed postprint version) articles submitted to these journals can be freely shared on a preprint server, without compromising authors' abilities to publish in parallel in those journals. Moreover, Pourret et al. [17] highlighted that the majority of journals in geochemistry allow authors to share preprints of their articles (47/56; 84%). Therefore, the relatively low uptake of preprint use in geochemistry is not because the opportunity is not there. It is more likely that a complex network of sociocultural factors is responsible for their low use, as is the case in other small research communities (e.g., a similar pattern is observed in palaeontology), even if open data sharing has been acknowledged by the community for more than 15 years [19]. The two main options for geochemists are EarthArXiv, a free preprint service for the Earth sciences initially powered by OSF Preprints, and ESSOAr, developed in a joint initiative by the American Geophysical Union with financial support from Wiley. Moreover, geochemists who have published in the many journals of the European Geosciences Union have already become accustomed to such openness and are posting their work prior to peer-review as a discussion on the Copernicus platform [20].
Attempts to close this gap between the inherent benefits of preprints and their relatively low uptake by research communities have concentrated primarily on making preprints more citable, for instance by having improved metadata, permanent identifiers (DOIs), and even the look and feel of a conventional and historical journal article (e.g., Preprints.org). There are good preprints and bad preprints, just like there are with journal articles. Overall, do not be afraid to be scooped or plagiarized! Preprints also actually protect against scooping [21,22]. Preprints establish the priority of discovery as a formally published item. Therefore, a preprint acts as proof of provenance for research ideas, data, code, models, and results-all outputs and discoveries. The fact that most preprints come with a permanent identifier (e.g., DOI) also makes them easier to cite, index, and track, and articles that are published as preprints appear to gain more citations at a faster rate [23]. Although arXiv was established almost thirty years ago, we are only just at the start, and there is a long way to go still for preprints. The Earth sciences are extremely complex, with many subdisciplines like geochemistry, each with its own norms. It is reasonable that a "one size fits all" model for preprints would never work for the entire scientific community and that geochemists need to develop and sustain their own model. The community should really be developing this, along with new standards for linking their datasets in the spirit of the FAIR (Findable, Accessible, Interoperable, Reusable) model [24], and the usage of open standards, licensing, and free and open source Software.
In the near future, given the increase in the use and profile of preprint servers and alternative publishing platforms, such as F1000 Research, it will be necessary to identify how many relevant platforms exist, to describe their scientific scope (i.e., covered disciplines), and, similar to the way that researchers evaluate the aims and scope of journals, to compare their characteristics and policies. In the vast usage of public software sharing platforms (e.g., Github, http://github.com and Gitlab, http://gitlab.com), there is also strong encouragement to make code re-usable, shareable, and citable, via DOI or other persistent link systems. For example, GitHub projects can be connected with Zenodo for indexing, archiving, and making them easier to cite alongside the principles of software citation [25]. This all comes as part of a wider global shift towards more open research practices, and the geochemistry community needs to make sure it is engaging widely with these, as well as connected issues like research integrity and reproducibility, if it is to maintain its relevance in the modern research age.
In Memory of Jonathan P. Tennant: You opened so much for so many. It is your time to have your way opened. Take some rest Jon. You were too young to die; we will miss you and this article will miss your "special social media blast" as you liked to say. | 3,728.2 | 2020-03-15T00:00:00.000 | [
"Computer Science"
] |
FRICTION AND WEAR BEHAVIORS OF A HIGH NITROGEN AUSTENITIC STAINLESS STEEL Fe-19Cr-15Mn-0.66N
The friction and wear behaviors of a Fe-19Cr-15Mn-0.66N high nitrogen austenitic stainless steel (HNSS) were investigated. Tribological investigations were carried out under different applied loads of 5 N, 10 N, 15 N, and 20 N. Scanning electron microscope (SEM) and laser scanning confocal microscope (LSCM) were used to understand the wear mechanisms under different loads and the reasons for the improved wear resistance. The lower friction coefficient and improved wear resistance were observed with the increase in applied loads. Under a higher load, the friction enhanced the work hardening ability of HNSS, which in turn improved its surface hardness and thus the increased wear resistance of HNSS.
Introduction 1.
High nitrogen nickel-free stainless steels (HNSSs) have gained immense attention for various industrial applications owing to their high strength, good plasticity, excellent cavitation erosion resistance, and superior corrosion resistance [1][2][3][4][5]. For instance, HNSS can be used as bearing steel because it can overcome harsh service condition of high temperature, heavy load and high velocity due to improved wear resistance [6]. Better biocompatibility and wear resistance make the HNSS have the great potential as a biomedical material [7]. These desirable properties are mainly attributed to the addition of nitrogen (N) element. N has a strong ability to improve the strength of austenitic steels via solution strengthening, grain boundary hardening and strain hardening [8][9][10][11], and it can also enhance their pitting corrosion and wear resistance [12][13][14][15]. Some researchers have found that N, working with other alloying elements (i.e., Cr, Mo, V) together, can also improve the mechanical properties of steels [16,17].
As a stabilizing element, N plays a vital role in stabilizing austenite phase. It has been reported that the ability of N element to stabilize austenite phase in the stainless steel is higher than that of Ni, and the stainless steels with solid solution N usually have high strength and good plasticity [18][19][20][21]. Therefore, all of these outstanding performances make the HNSS a promising engineering material.
Since friction is one of the main issues leading to material failure in service [22,23], it is important to investigate the friction and wear behaviors of the HNSSs. Lin et al. researched the fretting wear performance of high-nitrogen stainless bearing steel (40Cr15Mo2VN) under lubrication conditions and found that the volume loss grew sharply because the wear mechanisms changed from abrasive wear to adhesion wear and finally to abrasive wear corresponding to the contact stress from 1.788 to 2.579 GPa [6]. Zhao possessed excellent work-hardening capacity, and the dry wear rate decreased initially but subsequently increased due to increasing cold deformation [24,25]. Vats et al. studied the tribo-corrosion behaviors of nickel-free high nitrogen austenitic stainless steel in simulated body fluids, and found that E corr and i corr values increased with the increase in load from 5 N to 10 N in Ringer's and artificial saliva solutions [26]. Mills et al. investigated the tribological behavior of a high-nitrogen Cr-Mn austenitic stainless steel and found that high nitrogen Cr-Mn steel performs better than AISI 304 in dry abrasion condition, high nitrogen Cr-Mn steel performed better than Hadfield manganese steel and AISI 304 stainless steel when tested in a corrosive environment [27]. In conclusion, the research on friction and wear behavior of HNSS is mainly focused on the deformation produced during production, lubrication and friction environment (e.g. human body, ocean). However, the effect of load on its tribological behavior at room temperature has hardly been investigated, while friction and wear will eventually occur in the practical use and will be significant [28][29][30].
In this work, the effect of applied load on the friction and wear properties of the HNSS was investigated and the wear mechanisms at different applied loads were revealed. The friction behaviors of a new-developed Fe-19Cr-15Mn-0.66N stainless steel were investigated using scanning electron microscopy, electron backscatter diffraction, and Xray diffraction under different loads of 5 N, 10 N, 15 N and 20 N and the damage mechanisms were also discussed. This work provides a fundamental insight on the development of stainless steels with a higher wear resistance.
Experimental details 2.
The HNSS used in present study is Fe-19Cr-15Mn-0.66N stainless steel which has been recently developed by Northeastern University, and its chemical composition (wt. %) is listed in Table 1. The raw materials were smelted in a JNL-172KL high vacuum furnace and casted into ingots, and then processed by forging, hot rolling, and cold rolling. After that, the processed material was cut into coupons with the dimension of 30 mm × 30 mm × 5 mm. Each sample was gradually ground using SiC paper up to 2000 grit, then polished using a diamond paste with diameter of 2.5 μm, cleaned in ethanol, and finally dried using cool air.
To characterize the elastic properties of the HNSS, nanoindentation curves were acquired using a CSM NHT2 nanoindenter (Anton Paar) with a Berkovich tip at a maximum load of 20 mN and a loading/unloading rate of 40 mN·min -1 . The elastic behavior of material can be analyzed by its depth recovery ratio (η h ) obtained from the loaddisplacement curve [31], and the material with a better elastic property usually has a higher η h value.
The η h value can be calculated as follows: (1) where h max is the maximum penetration depth (nm), and h r is the residual depth after unloading (nm) [32]. The nanoindentation experiments were repeated at least five times. The average value of five experiments was used as the test result, and the plus/minus ranges were calculated by calculating the standard deviation of five experimental data.
The friction test was conducted using an UMT-2 friction tester without lubrication, the schematic diagram of which is shown in Fig. 1. During the test, the pretreated samples were used as the working disk and the ceramic ball (Si 3 N 4 ) as the friction couple. Under the action of the vertical load, the load was applied to the working disk, while the transverse load enabled the friction couple to reciprocate in a straight line through the motor. In the process of friction, the corresponding friction coefficient was calculated by transmitting data to the computer through the sensor on the loading rod. The tests were performed under dry conditions at the load of 5 N, 10 N, 15 N and 20 N and at a sliding speed of 0.025 m/s for 30 min corresponding to a sliding distance of 45 m.
The microstructure of the HNSS sample was characterized by scanning electron microscopy (SEM, JEOL, JSM-6480) and electron backscatter diffraction (EBSD, Oxford Instruments, NordlysNano Detector). The SEM was used the secondary electron (SE) imaging modes at an accelerating voltage of 20 kV and probe current of 50 pA. The step size of EBSD was 0.3 μm and the obtained EBSD data were processed and analyzed using the software HKL Channel 5. X-ray diffraction (XRD, Rigaku Corporation, Tokyo, Japan) with Cu Kα radiation was used at 10 kV and 35 mA to determine the phase present in the HNSS. The scan step size was 0.02 ° and the duration of each step was 2 s. After the friction test, the morphologies of wear scars and cross-section were observed using a laser scanning confocal microscope (LEXT, OLS400 LSCM) and SEM. Subsequently, the wear rates (W s , mm 3 ×N −1 ×m −1 ) can be calculated using Eq. 2: where C is the length of the wear scar (mm), A is the average area of wear loss (mm 2 ), F is the loading (N), and L is the distance of the wear (m) [33]. To investigate the effect of load on the hardness of the HNSS sample, the Vickers micro-hardness measurement was performed using an HXS-1000TAC tester with a load of 200 g and a load time of 20 s.
3.
Material characterization 3.1. Fig. 2 shows the EBSD images of the HNSS before friction test. It can be seen that the HNSS was mainly composed of austenite grain and some annealing twins were distributing inside of some austenite grains. The grain size ranged from 11 μm to 55 μm, making the average grain size to be 37 μm. Generally, it is easy for austenitic stainless steel to form strain-induced martensite after cold deformation [34]. To determine the phase present in the HNSS, XRD was performed and the result is shown in Fig. 3, showing the presence of a single-phase austenite in the HNSS and the absence of strain-induced martensite. The presence of the annealing twins observed in Fig. 2 is mainly attributed to the addition of high N content, since N can significantly reduce the stacking fault energy (SFE) of the HNSS [35] which made the annealing twins to form easily during the annealing process. Although some grains recrystallized after rolling, some of them were still present as subgrains with small sizes, which should be produced by grain refinement during the rolling process. The twins and the grain refinement can increase the hardness and strength of the HNSS based relevant investigation [36].
Nanoindentation test 3.2.
The load-displacement curve of the HNSS acquired in the nanoindentation test is showed in Fig. 4 depth recovery ratio, η h , of the HNSS is calculated to be 0.23. Besides this, the nanoindentation hardness can be determined according to the Oliver-Pharr method [37] and the calculated parameters are presented in Table 2.
Wear performance 3.3.
Fig . 5 shows the plots of friction coefficient of the HNSS as a function of time under different loads. When the load was 5 N, the friction coefficient increased gradually upon the test periods of 600 s, and then fluctuated with the increasing time. The increase in the friction coefficient represented the transition from material intact to material fracture [38], whilst the variations of the friction coefficient were probably caused by the contact instability when the indenter plowed against the samples [39]. This phenomenon is in good agreement with the results of the published work [40,41]. The maximum value of the friction coefficient could reach to 0.7. When the load increased to 10 N, the changes in the friction coefficient followed the same trend, but the variation amplitude became smaller compared with that under the load of 5 N. Under this circumstance, the maximum value of the friction coefficient was about 0.6. When the applied load was ≥15 N, the changes of the friction coefficients were similar. The friction coefficient increased rapidly at the initial stage (< 100 s), and then slightly fluctuated as the time increased, which yielded the maximum friction coefficient values of 0.56 and 0.54 under the load of 15 N and 20 N, respectively.
It is obvious that the friction coefficient decreased with the increase of applied load, suggesting that the variation of the friction coefficient may have been related to the wear mechanism caused by the change in the applied load [42]. Also, it can be noted that the friction coefficient of the HNSS remained relatively stable under a higher load (i.e., 15 N and 20 N). The wear mechanisms of the HNSS would be interpreted based on the morphology observation in the wear scars, and would be explained in detail below.
The average friction coefficients of the tested samples under different applied loads are shown in Fig. 6. It is clear that the average friction coefficient steadily decreased with the increasing applied load, suggesting that the wear resistance of the HNSS sample increased as the applied load increased.
According to Eq. 2, the changes in the wear rate of the HNSS samples with the increase of applied load are shown in Fig. 7. It is clear that the wear rate decreased from 1.7 × 10 7 mm 3 ×N −1 ×m −1 to 3.4 × 10 6 mm 3 ×N −1 ×m −1 as the load increased from 5 N to 20 N.
Wear morphologies of HNSS 3.4.
The results of friction coefficient and wear rate obtained are shown in Figs. 5-7, it showed that the wear resistance of the HNSS gradually enhanced with the increase of applied load. After the friction test, the wear surfaces and the cross-section of the HNSS samples under different loads were observed using Fig. 8 clearly shows that the width of the wear scars increased progressively from 554 μm to 899 μm under a higher load, and the edges of the wear scars appear to be more uneven as the load increases. The friction between the friction couple and the HNSS caused the maximum radial stress on both sides of the wear track [43], leading to the initiation of cracks in the wear surface. Under higher loads (i.e., 15 N and 20 N), the higher frictional forces made these cracks grow at each side of the wear tracks in Fig. 8 c and d, leading to cohesive spallation [44]. Cross-sectional 2D topography of HNSS samples under different loads are shown in Fig. 9. As the load increases from 5 N to 20 N, the depth increases from 7 μm to 14 μm. It also shows obvious increase of the width of the wear scar, and the accumulation of the edge of the wear scar due to extrusion becomes more obvious as the load increases, which is consistent with the results of Fig. 8. When the applied loads are 15 N and 20 N, the widths and depths of the wear scars are similar and the profiles are only slightly different, and the sides of the profiles of 15 N and 20 N show much smoother compared with the profiles of wear scars of 5 N and 10 N, this exactly corresponds to the results of friction coefficient. Fig. 10 presents the SEM morphologies of the HNSS under different applied loads. It can be seen that there were many defects observed such as grooves, wear debris, tearing, and delamination (as the arrows marked in Fig. 10). Based on the formation of these defects above, there were two wear mechanisms involved: abrasive wear and adhesive wear mechanism. When the loads were applied to the sample, the friction couple extruded the sample surface, leading to the plastic deformation of internal grains and eventually the nucleation and growth of cracks by cumulative plastic shear. Plentiful defects (i.e., grooves and wear debris) would form in the process of grain plastic deformation. The formation and propagation of the crack would lead to the detachment of materials. This micro-fracture process of materials is the typical process of abrasive wear [45]. During friction test, the local bonding between the HNSS sample and the friction couple occurred resulting in the formation of momentary microwelding and tearing and eventually the material loss. This type of wear is known as adhesive wear. Thus, the wear resistance of a material is dependent on the resistance to deformation and fracture [24].
When the applied load was 5 N, there were many large scratches with grooves, tearing and delamination in the sliding direction, as shown in Fig. 10 a. The formation of the grooves in the sliding direction was due to the hard asperities of the counter-face [46], while tearing and delamination could be produced by the adhesion of the wear particles during their removal from the sample surface or/and their back transferring from the surface of friction couple [46]. A number of wear debris with various sizes were also observed, which were detached by plastic deformation [47]. As 5 N, b 10 N, c 15 N, d 20 N Figure 9. Two-dimensional (2D) profiles s of cross section of the wear scars the load increased to 10 N, the number of wear debris distributed in the grooves slightly decreased, as shown in Fig. 10 b. Under a higher applied load (i.e., 15 N or 20 N), this tendency of the decrease in wear debris number became more obvious, as shown in Figs. 10 c and d. The smooth appearance of the worn surface correlated well with the low friction coefficient, which was consistent with the previous work [42]. Fig. 11 shows the cross-sectional micro-hardness profiles of the HNSS under different applied loads. It can be seen that the micro-hardness decreased from the subsurface layer underneath the worn surface (>450 HV 200 ) to the un-deformed base metal (~ 400 HV 200 ), suggesting that all samples experienced work hardening. According to the empirical electron theory of solids and molecules [48], the interstitial C, N and alloy element atoms can form many strong N(C)-Me covalent bond nets in the HNSS, which markedly hinder the dislocation movement and lattice reconfiguration process, thus improving the strength and work-hardening ability of the HNSS. High Mn and N content of the HNSS can reduce the SFE and facilitate the formation of the annealing twins. During the friction test, plastic deformation was accompanied by the increase of dislocation density, and the formation of twins during plastic deformation resulted in an increase in the resistance of dislocation slip, thus increasing the hardness [22,49,50]. The increase in the microhardness of the sub-surface layer underneath the worn surface indicates that the workhardening rate increased with the increase of applied load. It is consistent with the previous work that the hardness of the HNSS increased after cold deformation as a consequence of the work-hardening effect [24,32]. The work hardening behavior of the samples was more pronounced under a higher applied load, which could be one of the reasons for higher wear resistance of HNSS as the load increased [51,52].
4.
According to Hsu et al. [53], plastic deformation and its accumulation on the contacting asperities control the wear process when the temperature is ambient, and the tribological properties of the materials are closely related to their hardness.
At initial stages of the application of low load (i.e., 5 N and 10 N), the HNSS sample firstly had to experience elastic deformation (Fig. 4). The friction couple extruded the surface of HNSS, and the surface could be easily damaged, producing debris due to the low hardness [48], as demonstrated in Fig. 10 a and Fig. 12 a. Since it was difficult to embed these debris into the HNSS matrix in the process of reciprocating friction, these debris in turn would work together with the friction couple ( Fig. 1) to wear the HNSS sample, leading to the formation of many grooves, as shown in Fig. 10 b. This is typical of 5 N, b 10 N, c 15 N, d 20 N Figure 11. Cross-sectional hardness profiles of the HNSS under different applied loads abrasive wear, Fig. 12 b. As the tribology process progressed, more and more debris/grooves were produced, making this ploughing process more severe but more unstable. Thus, the friction coefficient was high and fluctuated with the increasing time (Fig. 5). However, the further development of the ploughing process would lead to the increase of the friction strain of wear scars. As friction strain reached a critical value, the contacting asperities on worn surfaces started to yield to plastic deformation and finally fracture, leading to the formation of the stripping zone [54]. The stripping zones were transferred between the surface of wear scars and friction couples leading to adhesive wear. As a result, the wear mechanisms of the HNSS were abrasive wear and adhesive wear (Figs. 10 a and b) when the applied load is low (5 N or 10 N). Under a higher applied load (i.e., 15 N and 20 N), it would be much easier for the HNSS sample to exceed the elastic deformation and experience plastic deformation. At initial stage of wear, the friction couple was pressed into the sample surface under the normal load, the contact area was abnormally small and the macroscopic contact stress was very large. When the friction couple moved relatively, it ploughed the wear surface with large friction resistance, resulting in high friction coefficient. With the progress of wear, the contact area between friction couple and the wear surface gradually increased, and the macroscopic contact stress decreased, thus the friction coefficient stabilized after the initial sharp increase [55] (Fig. 5). The changes in the fiction coefficient (Figs. 5 and 6) indicate that the wear mechanism of the HNSS sample changed with the applied load. Under these circumstances, both the grooves and debris particles decreased (Figs. 10 c and d), but the area of plastic deformation increased due to higher hardness (Fig. 8). As the plastic deformation continued to develop, the micro-bulge on the surface of the HNSS sample was produced when the sample was in contact with the friction couple, and the friction force would push the shedding particles adhered to the surface of the sample, showing signs of delamination. Under these circumstances, the wear mechanism of the HNSS sample was characteristic of adhesive wear mechanism [52].
During the fiction and wear processes, work hardening can increase the hardness, strength, and deformation resistance of a material [56]. According to the changes in the friction behaviors of the HNSS samples and in the wear surface morphologies (Figs. 5-10), it is clearly stated that the hardness of the HNSS caused by work hardening during the friction test played a predominant role in the wear process [57]. After tribology test, both the micro-hardness of the HNSS sample underneath the wear scars and its work hardening rate increased with the increase in the applied load (Fig. 11), which was similar to the results obtained by Dib et al [58]. They found that the friction coefficient of AISI 304 stainless steel decreased with the load rise, which was attributed to the increased hardness, but the difference is that during the load increase, the hardness was increased mainly due to martensitic transformation, while the decrease of HHNSS's friction coefficient was mainly due to the increase of hardness caused by work hardening. The increased micro-hardness raised the threshold for micro-cutting and decreased the fraction of material remove during the cutting regime [59]. Both the wear damage and the rate of the HNSS sample decreased with the increasing applied load, as displayed in Fig. 7 and Fig. 8. Fig. 7 shows a decreased wear rate of the HNSS as the load was increased from 5 N to 20 N, which could be attributed to the better work hardening performance of the HNSS during sliding under the higher normal loads enhancing the hardness and the strength of the substrate [54,60]. The reason for the high work-hardening capacity of the HNSS was due to the effect of N and Mn (more than 15% in weight, Table 1) on the microstructures resulting in the reduction of the SFE [61,62], which can not only promote the formation of twins [9,63] (Fig. 2), but also make the dislocation configuration to change from wavy to planer dislocation. Also, the change of Figure 12. Schematic diagram of the wear mechanism a, b abrasive wear; and c, d adhesive wear dislocation configuration reduced the chance of dislocations to cross-slip [64], thus improving the validity of planer dislocation. The fixed Lomer-Cottrell dislocations were formed at the intersection of planer dislocations, and further plastic flow was hindered as the higher loads were applied, which became the obstacle of subsequent dislocations, thus significantly increasing the work hardening tendency and wear resistance of the HNSS [10,48].
5.
In this work, the friction and wear behaviors of Fe-19Cr-15Mn-0.66N high nitrogen austenitic stainless steel at different loads were investigated with Si 3 N 4 ball as friction couple. The influences of load on wear morphologies were analyzed. The main conclusions of this work can be summarized as follows: With the applied load increased from 5 N to 20 N, the friction coefficient of the Fe-19Cr-15Mn-0.66N austenitic stainless steel decreased from 0.51 to 0.43, indicating the increase in wear resistance.
The wear resistance of the HNSS was higher under a higher applied load due to the increased micro-hardness of the deformed HNSS caused by the formed work hardening layer and the increased work hardening rate.
When the applied load increased from 10 N to 15 N, the wear mechanism of the HNSS changed from mixed abrasive wear and adhesive wear to adhesive wear due to the increased hardness caused by work hardening, which was verified by the decrease of grooves and debris on the wear surfaces. | 5,640.6 | 2021-01-01T00:00:00.000 | [
"Materials Science"
] |
Optically reconfigurable unit cell for Ka-band reflectarray antennas
A new method for achieving amplitude recon fi guration in a re fl ectarray antenna is presented in this Letter. An individual unit cell is a compact multilayer structure, including a silver inkjet-printed layer for rapid prototyping of the re fl ectarray. A small infrared light emitting diode (IR-LED) illuminating a silicon wafer provides the recon fi guration in the system. Various illumination intensities of the IR-LED allow for differing magnitudes of re fl ection from the unit cell. This provides the potential for radiation pattern tapering or amplitude modi fi cations of the gain of the re fl ectarray. Simulation and measurement results for a single unit cell are presented here, with the matching between measurement and simulation also allowing for the change in the values of conductivity of the silicon to be extracted.
Introduction: The incorporation of reconfigurability in such an antenna typically focuses on the use of active elements to adjust the reflection phase [1]. PIN diodes, microelectromechanical switches and liquid crystals have been demonstrated in reflectarray antennas to provide variation in the reflection phase of the unit cells [2,3]. Similarly, the adjustment of the reflection amplitude of each unit cell is another area in which reconfiguration can be incorporated. This has potential advantages in a full reflectarray configuration, in which the sidelobe levels of the radiation pattern can be adjusted using an amplitude-only reconfiguration mechanism for each cell. The traditional methods of reconfiguration as mentioned above will not continuously adjust the reflection magnitude, and as a result of this, a novel unit cell is designed here, making use of silicon as an optically reconfigurable substrate.
The use of optically activated semiconductors such as silicon to provide reconfigurability has been implemented previously. In [4], a silicon switch was used for a beam and frequency reconfigurable antenna. When illuminated with sufficient optical power (above the bandgap energy of the material), electron-hole pairs are generated through photon absorption. This creates a plasma in the material, the conductivity of which is dependent on the optical power used [5]. Despite the potential advantage of continuous reconfiguration without the need for unpredictable bias lines, optical reconfiguration has an inherent disadvantage in that it requires high power illumination sources [6]. Nevertheless, it has been shown that a high power infrared light emitting diode (IR-LED), as opposed to a bulky laser source can provide sufficient optical illumination power [7,8]. The use of an IR-LED light source removes the need for a large and expensive optical source, giving this method of reconfiguration the potential for large-scale applications, as developed in this Letter. Description of unit cell: The proposed unit cell for reflection amplitude variation makes use of a high power surface mount IR-LED in close proximity to the silicon surface to act as the reconfiguration mechanism. A plasma layer is generated in the silicon, thus controlling the reflectivity of the unit cell. A multilayer structure shown in Fig. 1 is used for the biasing and control lines of the LED, ensuring that these have minimal impact on the performance of the structure. A thin layer of Rogers RT Duroid 5880 with no metallisation is placed above the silicon, to act as a protective layer. In this case, medium resistivity silicon is used. An inkjet-printed metallic grating is placed above the layer of silicon, providing both a reflective surface, whilst allowing the incident radiation of the feed horn to reach the silicon layer. To satisfy the requirement of phase distribution across the reflectarray surface, the size of the slots and the overall area of each grating element can be varied. This grating is printed by a Diamatix Materials Printer (DMP-2831) on a polyethylene terephthalate (PET) substrate using silver ink, as shown in Fig. 2. This allows for rapid prototyping of the grating. Fig. 2 Top metallic grating layer, printed using silver ink on PET Waveguide characterisation procedure: Waveguide characterisation of the unit cells for reflectarrays is a common technique, both in simulation and in measurement scenarios [9]. The use of the waveguide characterisation setup allows for rapid prototyping of the array, without the need for costly fabrication of the full structure of the reflectarray. The experimental waveguide setup used in this Letter is shown in Fig. 3. The characterisation process used here has a two-fold purpose: first, to characterise the response of the silicon substrate under illumination, and secondly to ascertain the reflection properties of the reflectarray unit cell itself. When characterising the response of the silicon, the property of interest is that of the conductivity of the plasma layer. For this, the top PET grating layer is not used, removing any potential uncertainty from this layer in terms of its material properties. All other layers of the unit cell are used, and the reflection response of the structure under different IR-LED illumination powers is measured and recorded. Variation of the illumination power is realised by changing the DC bias voltage and current. To ascertain the conductivity levels, the measured results are compared and matched to an accurate simulation model generated in CST Microwave Studio, with the only variable parameter being the conductivity level of the silicon. The conductivity level that can be achieved is important for the continuing design of the full reflectarray antenna.
For the characterisation of the reflectarray unit cell itself, the grating is put in place and the illumination power of the IR-LED is varied, in a similar fashion to that used in the silicon characterisation. It is important in this case that the reflection phase remains predictable throughout the variation of illumination power.
Experimental results: The first results presented show the measured and simulated results for the characterisation of the silicon substrate. The results presented in Fig. 4 show the differences between the active and offstate of the silicon. By fixing all other parameters of the CST simulation model, it is possible to match the simulation and measurement results, using only the conductivity values. The conductivity value extracted for the off-state was 5 S/m, while for the active state it was 80 S/m. These values are the first reported Ka-band conductivity levels achieved using LED illumination rather than laser sources. The profile of the results presented in Fig. 4 shows that there are a number of resonances in the structure, the causes of which can be determined through parametric analysis of the structure, which is done once the conductivity level is ascertained. The depth of the first resonance at 30.7 GHz is predominately controlled by the size of any air gaps between the FR-4 LED circuit layer and FR-4 layer directly above it. The frequency at which this resonance occurs is also controlled by the same parameter. The second resonance which occurs at 33.1 GHz in the measured results is fixed in magnitude and is caused by the IR-LED itself, which could not be modelled accurately in the simulations. Fig. 4 Simulated and measured results for silicon in its on and off states, using parametric sweeps to match conductivity values Following the characterisation of the silicon itself, the reflectarray unit cell could be modelled and tested. As mentioned in the previous sections, the unit cell used in this Letter only differs in that the PET printed grating is present. The results presented in Fig. 5a highlight a high level of deviation for the reflection magnitude, across a relatively large bandwidth. More precisely, between on and off states, the maximum deviation is 7 dB. Furthermore, with each increase in voltage, the reflection magnitude increases by at least 1 dB, with the largest increase occurring between the off state and 1.4 V. The amount of variation decreases as the power of LED reaches its maximum at 1.8 V and 512 mA. The phase deviation of this unit cell is an important aspect which needs to be considered. The reflection phase of this unit cell should be independent of the illumination intensity of the LED, allowing the phase to be controlled only by the dimensions of the grating on the top layer. Fig. 5b shows that very little phase deviation is present with respect to illumination intensity, particularly at around 31 GHz. Furthermore, away from this frequency, the deviation at a particular frequency is no more than ±20°. Although this variation is not significant, it will be necessary to adjust the phase distribution accordingly, as these phase alterations will cause phase error which may affect the reflectarray performance negatively.
Conclusion: A novel reconfigurable unit cell is proposed for sidelobe reduction in reflectarrays, in which the reflection magnitude is controlled by an optically activated semiconductor substrate. Inkjet printing of silver is used for rapid prototyping of the grating layer, allowing quick turnaround in the design process. The chosen silicon substrate is integrated as part of a multilayer structure, along with the inkjetprinted layer. Furthermore, we have used a variation of this unit cell structure to characterise the conductive properties of silicon under IR-LED illumination. A variation of 14 dB is observed at 30.8 GHz, corresponding to an increase in the conductivity to 80 S/m. Additionally, the full reflectarray unit cell has been measured, and shows good reflection magnitude reconfigurability, meaning this unit cell design is a good candidate for a reflectarray with variable amplitude unit cells for sidelobe and pattern modification. | 2,161.6 | 2017-11-09T00:00:00.000 | [
"Physics"
] |
Dynamic Water Balance Modelling for Risk Assessment and Decision Support on MAR Potential in Botswana
: Botswana experiences a water stressed situation due to the climate and a continuously increasing water demand. Managed Aquifer Recharge (MAR) is considered, among other measures, to improve the situation. To evaluate the possibility for increased water supply security, a probabilistic and dynamic water supply security model was developed. Statistically generated time series of source water availability are used in combination with the dynamic storages in dams and aquifers, and the possible supply is compared with the demand to simulate the magnitude and probability of water supply shortages. The model simulates the system and possible mitigation measures from 2013 to 2035 (23 years), using one ‐ month time steps. The original system is not able to meet the demand, and the estimated volumetric supply reliability in the year 2035 is 0.51. An additional surface water dam (now implemented) will increase the reliability to 0.88 but there will still be a significant water shortage problem. Implementing large ‐ scale MAR can further improve the reliability to at least 0.95. System properties limiting the effect of MAR are identified using the model and show how to further improve the effect of MAR. The case study results illustrate the importance and benefit of using an integrated approach, including time ‐ dependence and future scenarios, when evaluating the need and potential of MAR.
Introduction
Access to potable water is essential to human health and economic development. Water scarcity and drought are, however, major challenges on all continents [1] and must thus be managed to enable safe and secure access to clean water. Climate change, increased water demand and other factors will increase the problem of water scarcity, making this a key issue to reach the UN Sustainable Development Goals [2]. This calls for integrated water resources management, including measures to avoid water losses, the efficient use of water, the introduction of water saving technologies, as well as of water re-use and recycling.
Botswana is an example where the hydrological conditions and a continuously increasing water demand result in a water stressed situation. The arid to semi-arid climate provides a situation with low rainfall and high rates of potential evapotranspiration, resulting in low rates of surface runoff exceed 50 mm anywhere except in small steep rocky catchments. The annual recharge to aquifers from rainfall reaches a maximum of about 40 mm in small areas in the Chobe District in the north. For most of the Kalahari region, the natural groundwater recharge is less than 1 mm/year [8]. The largest groundwater resources are in the Kalahari sediments (including the Okavango Delta), the Ntane Sandstone, the Ecca Sandstones, and the Damaran and Ghanzi rock formations.
In eastern and southern Botswana, with its relatively high density of population and substantial water demand, several surface water dams have been constructed to collect and store ephemeral river flow. The largest dams are the Shashe, Dikgatlhong, Letsibogo, and Gaborone dams. The storages of the dams are very variable due to the highly seasonal, occasional, and variable river flows. In addition, the need to store water for drought periods and the flat topography in most areas result in large losses of water to evaporation from these dams. The surface water dams in eastern Botswana have been connected through a nearly 400-km long pipeline transfer system denoted the North-South Carrier (NSC), providing possibilities to transfer water to urban centres.
The NSC water supply system is the focus of this study and the included demand centres, surface water dams, aquifers and additional components are shown in Figure 1. The study was performed in the year 2013 and the descriptions of the system, planned measures, etc., are thus based on the situation at that time. The Dikgatlhong Dam was being constructed when the study was performed and thus included in one of the modelled scenarios to represent the coming system structure. In addition to the surface water dams, a few groundwater wellfields are connected or are planned to be connected to demand centres supplied with water from the NSC, e.g., Palla Road, Chepete, Masama, Makhujwane, Malotwane, and Palapye Wellfields.
Due to the highly variable storage in surface water dams, the groundwater aquifers have a potential to support the NSC demand centres during drought periods. Because of the very limited natural recharge to these aquifers, their long-term sustainable capacity could be improved by managed recharge with surface water. Managed recharge (injection) with collected and treated surface water from dams may also reduce the total loss of water to evaporation. The focus of the case study is thus to evaluate the possibility and effects on the water supply security of MAR scenarios including the Palla Road/Chepete and Masama/Makhujwane Wellfields.
Water Supply Security Model (WSSM)
The WSSM is a dynamic water balance model where statistically generated time series of the availability of source water are used, together with dynamic storages in dams and aquifers, as well as water demands, to simulate the magnitude and probability of water supply shortages. Models have been previously developed for the water supply in Botswana but they have not considered MAR scenarios [8]. The WSSM is developed as a spreadsheet model in Excel since one of the goals of this study was to provide an easily accessible model that can be run without expert knowledge. To enable statistical analysis considering uncertainties in input data and results, an add-in software (Oracle ® Crystal Ball) is used to run Monte Carlo simulations.
The WSSM simulates the NSC system and connected components from 2013 to 2035 (23 years). The period is selected to match water demand forecast in the National Water Master Plan Review [8]. The simulations are performed with a time step of one month and for each month the demand, the available storage in dams and aquifers, as well as treatment capacities, water losses, etc., are considered.
The schematic illustration in Figure 2 shows the parameters considered in the model and the link to the model components. Based on historical data on inflow to the dams (see Section 3.2), a set of possible time series are generated and used to sample from when running the model. The generated time series consider the correlation between the dams and each generated data set includes all five dams. The annual inflow data is transformed into monthly data based on the closest historical annual inflow and the monthly distribution that year. Since the dams are spatially correlated, the historical data for the Gaborone Dam is used when transforming the simulated annual data for the Bokaa and Gaborone Dams. In the same way, the historical data for the Dikgatlhong Dam is used for the Letsibogo, Shashe, and Dikgatlhong dams. For each dam, water balance calculations are performed for each month, considering initial storage, inflow, abstraction, evaporation, seepage, spill over, and additional parameters presented in Figure 2. The input data is based on [8] and information from personnel at the Water Utility Corporation (WUC) and the Department of Water Affairs (DWA). The evaporation is calculated based on the area-storage relationship and data from previous studies in the area [8,25]. Key inputs for modelling the dams in the WSSM are presented in Table 1. The water balance calculations for MAR wellfields are performed considering initial storage, natural recharge, inflow, injection, outflow, and abstraction. Necessary input data for the aquifers are based on [26][27][28][29], and the key figures used in the scenarios modelled here (see Section 3.3) are presented in Table 2. The wellfields are recharged by injecting water if the maximum storage is not reached and provided that water is available in the dams and is at a capacity to abstract, treat, transfer, and inject the water. A critical dam storage level (20%) was defined by the WUC and DWA and is used as an operational rule in the model stating that water for injection may only be abstracted when the dam storage is above this level. The abstraction of water from the MAR wellfields starts when the water demand cannot be met by the supply of treated surface water and the non-MAR wellfields. The abstraction is only limited by the abstraction rate and capacity to treat and distribute the water.
For the wellfields not considered relevant for MAR, an estimated sustainable yield is used as a maximum abstraction rate to not cause groundwater mining. The sustainable yield is estimated on an annual basis and defined in the model as a monthly maximum abstraction that may not be exceeded. The total sustainable yield for the non-MAR wellfields is 7.2 Mm 3 , and 11.7 Mm 3 when also including the Masama/Makhujuwane and Palla Road/Chepete Wellfields as non-MAR wellfields. The water demand forecast from [8] is used to determine how much water must be abstracted from the dams and wellfields. The estimated change in water demand is based on a population forecast and an increase in specific water demand, including assumptions of changes from standpipe to yard and yard to house connections. The assumed industrial, commercial, and institutional annual growth rate is 3%. Unaccounted-for water, including technical losses and non-technical losses (unmetered consumption and illegal connections), is also considered in the forecast. Since the reported water consumption in 2012 was 4 Mm 3 /year lower than the forecast for the same year, the original demand forecast was reduced by this volume. The total annual demand for the demand centres included in the WSSM is 81 Mm 3 in 2013 and 148 Mm 3 in 2035.
In addition to the capacities and other parameters presented above, a set of operational rules are used to determine, for example, when different sources are used and to what demand centres and the extent to which water is supplied. In all calculation steps, available abstraction rates, treatment capacities, water losses during treatment etc., are considered. The model is thus not used to optimize the supply from different sources but to estimate the performance based on the actual operational rules used to manage the system. The schematic illustration in Figure 1 shows how the different components of the system are connected and how water can be transferred. The actual supplied amount of water is compared with the demand for each demand centre and possible shortage etc., is calculated in each time step.
Dam Inflow Time Series
The time series of monthly inflows to the five dams (Gaborone, Bokaa, Letsibogo, Dikgatlhong and Shashe) are available based on measurements and hydrological modelling for the 80-year period of 1925 to 2004 [8] (vol. 11). The dams are grouped based on their spatial correlation and the annual inflows are presented in Figure 3. An analysis of the annual inflows is made to generate 96,000 future annual inflow time series (23 years) that are used to sample from when running the WSSM. This fivedimensional time series is modelled as a first-order stationary Gaussian Auto-Regressive, AR(1) sequence: where the column vector t y is the annual inflow and t = −79, −78, …, 0 (t = 0 corresponds to year 2004). The column vectors μ and t denote the long-time yearly mean and white noise, respectively, the latter with covariance matrix Σ. To carry out a standard least squares (LS) estimation, the model is rewritten as follows:
Scenarios
The system included in the analysis and implemented in the WSSM includes: 6 surface water dams, 8 wellfields, 7 water works, and 18 demand centres. In addition to five dams previously presented, the Molatedi Dam in South Africa is also included in the model. A constant supply (80% of the maximum agreed transfer) from the dam is assumed since no historical time series are available. The same assumption has previously been used when evaluating the supply system [8]. The selection of wellfields for MAR scenarios was based on [9,[26][27][28][29][30][31][32][33] and workshops including representatives from the DWA, WUC, and the authors. Several scenarios including MAR and non-MAR wellfields are possible, but we here focus on the three scenarios listed below as a basis for evaluating the potential of using large scale MAR in Botswana. The system structure in 2013 (Scenario A), i.e., when the study was performed, is used as a reference to illustrate the need and potential effects of mitigation measures (Scenarios B and C) on the water supply security. As mentioned above, the Dikgatlhong Dam was under construction when the study was performed and is now in operation. Hence, the dam is included in Scenario B and combined with MAR in Scenario C. The purpose is not to evaluate MAR as an alternative measure to the Dikgatlhong Dam but to see how MAR can further improve the system. To facilitate a relative comparison of the mitigation measures, i.e., the Dikgatlhong Dam and the MAR wellfields, they are included from the start of the simulated period (i.e., year 1).
Results
The results from the WSSM show that the supply system in Scenario A is clearly insufficient to meet the water demand within the simulated period of 23 years. Water shortage is likely to be a problem early in the simulated period and is expected in around 70% (mean value) of the months for most demand centres. Given a month with water shortage, the deficit varies between c. 20%-60% of the demand. The water supply security can be assessed based on the volumetric reliability, i.e., the volume of water supplied divided by the demand in a given year. The results are presented in Figure 4 and show that the reliability is dramatically reduced for Scenario A over the simulated period. There is no reliability target level defined in Botswana but at the end of the simulated period the level is only 0.51 (mean value). As a comparison, case studies in Australia [21,22] have applied a 0.995 volumetric reliability target for potable supplies and a 0.95 target level for non-potable use.
In Figure 5, the expected (mean) probability of annual water shortage of different magnitudes is presented for Gaborone and the demand centres connected to the capital city, here referred to as Great Gaborone. The results are similar for most of the demand centres, and, for evaluating the potential effect of MAR, we focus on Great Gaborone. The total demand for Great Gaborone will increase over the analysed period from 44.8 (year 2013) to 82.4 Mm 3 /year (year 2035). The water demand for Great Gaborone constitutes 62% of the total demand in the NSC system. The connection of the Dikgatlhong Dam to the NSC and the related system upgrades (Scenario B) will have a large positive effect on the supply security, see Figure 6, and reduce the expected total water shortage (summed over the 23 years) by approximately 90%. The supply reliability will increase ( Figure 4) and be >0.99 for approximately 10 years. However, in 2035, the reliability is estimated to be 0.88 and the results thus show that there still will be a significant risk for water shortage for Great Gaborone during the late part of the simulation period.
In Figure 7, the results are presented for Scenario C, i.e., including the MAR wellfields. The probability of shortage is further reduced compared to Scenario B. For example, the probability of having a 10% (8 Mm 3 ) water shortage in Great Gaborone in 2035 is reduced from 40% (Scenario B) to 10%. For Scenario C, the supply reliability is >0.99 in approximately 15 years and is estimated to be 0.95 in 2035. The effects of implementing MAR are, however, limited due to the capacity of different system components. As an example, Figure 8 shows what limiting the injection of water from the Scenario C dams at the Palla Road Wellfield. Injection is expected to be needed in 41% of the months. In 34% of these months, injection up to the full storage or maximum injection rate is obtained. However, the dam storage (abstraction of water for injection only allowed if dam storage is >20%), the abstraction rate from dams, and the capacity of the treatment plants (only treated water is injected) are limiting the injection in 45%, 17%, and 4% of the cases, respectively. If the most critical technical system properties causing the limitations are eliminated, the positive effects of MAR in Scenario C further increase. For example, the supply reliability in 2035 will increase to 0.97 and the probability of an annual water deficit of 2 Mm 3 (2.5% of the demand) will reduce from 32% to 10%. This effect can be obtained without any substantial risk of mining the wellfields. The maximum active storage for the Masama/Makhujwane and Palla Road/Chepete Wellfields are 40 and 42.8 Mm 3 , respectively ( Table 2). The probability of having full storage at the end of the simulated period is 0.8 for both wellfields in Scenario C when the key limiting factors have been eliminated. If the limitations are included, the probability of full storage is 0.2 and 0.5, respectively.
Provided that no water is abstracted and the maximum injection can be applied, it would take 5-6 years to recharge the MAR wellfield from 0 Mm 3 to full storage. If dependent on natural groundwater recharge only, the wellfields will only be recharged up to approximate half of the maximum storage after the simulated 23 years.
Discussion and Conclusions.
The performed case study addresses the possible effects of implementing MAR in the NSC system in Botswana. It is concluded that the NSC system including the Dikgatlhong Dam (Scenario B) but without MAR is not likely to be able to provide a safe water supply over the entire time period. When the water demand increases, the reliability of the system is reduced. Implementing MAR at the Palla Road/Chepete and Masama/Makhujwane Wellfields (Scenario C) will further improve the system, although not eliminate the risk of future water shortage. However, implementation of MAR may be of great importance in managing the water supply situation in eastern Botswana.
By including the Dikgatlhong Dam in the system (Scenario B), an additional water source is added and the potential volume of water that may be accessible is increased. Due to the spatial correlation between the dams, periods of no or limited inflow may affect several dams at the same time and thus cause a severe water shortage. By including the MAR wellfields, we add components that are dependent on the surface water dams to be recharged but the water stored in the aquifers can be used independently of the dams. The latter part is one of the key reasons for the increased reliability in Scenario C. The results show that over time there is enough water in the dams to be able to recharge the MAR wellfields. However, the possibility to inject water is partly limited in Scenario C due to both the capacity of the system components and access to the surface water. If these limitations are reduced or eliminated, the positive effect of implementing MAR will further increase.
The non-MAR wellfields are operated using the estimated sustainable yields as a maximum monthly abstraction rate. If this criterion would have been defined on an annual basis and allowed a varying abstraction over the year, it is possible that some smaller shortage events could have been avoided. Another criterion for sustainable yield could be implemented into the WSSM but would, however, not have a significant effect on the more severe shortage events. By allowing the same abstraction rates for the Palla Road/Chepete and Masama/Makhujwane Wellfields, as in Scenario C, but without MAR, the system would improve but only for a limited time. Due to the limited natural groundwater recharge, the aquifers would gradually be emptied. MAR is thus needed in order to provide for a long-term sustainable solution.
The results from the modelled scenarios do not show any cases where the implementation of MAR reduces the supply system security in Botswana. This could be the case if, for example, there are large losses of water or the abstraction rate is too low compared to the surface water dams.
The developed WSSM enables a thorough analysis and evaluation of the original system as well as the effect of both MAR implementation and other system changes. A key advantage of the model is the ability to not only model the possible enhanced groundwater recharge over time but to compare the possible supply and demand for all system components. The predicted water shortage over time in combination with dam and groundwater levels provides a comprehensive picture of the system performance. This makes it possible to evaluate system reliability with consideration to the entire system and compare MAR scenarios with other possible measures to avoid the sub-optimisation of risk mitigation measures.
Furthermore, system properties limiting the effects of MAR can be identified as shown in the case study. This result can guide further analysis and improvements to enhance the effect of implementing MAR. Hence, the WSSM can provide results to support decisions on both larger system changes and minor upgrading to improve water supply security.
The main conclusions of this study are: The developed WSSM is a comprehensive and dynamic water balance model that enables a thorough analysis of recharge and abstraction from MAR wellfields as well as the overall system reliability. The case study application demonstrates the practical applicability of the model and shows that useful decision support is provided. Future development of the WSSM approach will include consideration to climate change in dam inflow data and other relevant system parameters. The WSSM provides added value by enabling an integrated approach, including timedependence and future scenarios, when evaluating the need and potential of implementing MAR.
Author Contributions: The study was initiated by all authors. L.R. was the project leader and P.-O.J. analysed and estimated input data related to aquifers and water demand. A.L. created the water supply security model with support from the other authors. T.N. analysed and modelled time series of inflows to surface water dams. A.L. performed the calculations and was the main author of the paper. All authors have read and agreed to the published version of the manuscript. | 5,132.4 | 2020-03-06T00:00:00.000 | [
"Environmental Science",
"Engineering"
] |
DIGITAL IMPLANT PLANNING: A BRIEF NARRATIVE REVIEW
Recently, the development of radiology, and software engineering, has led to the development of a new protocol called computer-assisted implantology (CAI) or guided implantology. CT / CBCT scanners allow the dentist to visualize a patient's anatomy in 3 dimensions. Define the precise measurement of bone for implant placement, soft tissue thickness, proximity and adjacent root anatomy. The exact location of the maxillary sinuses, and other relevant vital structures such as mandibular canal, mental and incisal foramen canal. Once the images are imported, to the software the clinician can then virtually begin treatment planning. The type and size of the planned implant, its position in the bone, its relationship to the restoration and adjacent teeth and/or implants, and its proximity to vital structures can be determined prior to surgery. Computer-generated surgical drill guides can then be manufactured from the virtual treatment plan.
ISSN: 2320-5407
Int. J. Adv. Res. 9(02), 869-873 870 projects it into a digital sensor with each pulse. The conical beam makes it possible to directly obtain the volume of the object by computer calculation from the multiple 2D projections acquired during the rotation of the device. [3] Both CT and CBCT are stored inthe universal format for "Digital Imaging and Communicationin Medicine" (DICOM-format). Amongst imagingdata, geometric and mathematical information, practicalinformation such as acquisition details and settings areincluded in the DICOM file.
Volumetric imaging data is displayed in 2D crosssectionalimages aligned to the prospective implant position.3D surface models of CT or CBCT data are displayedusing segmentation.CT or CBCT does not sufficiently display the tooth surfacefor the prosthetic set-up and for drill guide production.Especially in the presence of restorations, Therefore, CTor CBCT scans and a virtual dental model obtained eitherfrom an intraoral optical scan or an extraoral scan of impressionsor stone casts are aligned to each in implant planning software. [4] [5] Implant planning software : Recent Pre-implant simulation software are programs that provide clinicians excellent tools for pre-operative implant planning. to make digitally the placement of implants and different prosthetic components. These programs, for the most advanced ones, can also offer the possibility to design a surgical guide from the computer project, and even to foresee thedesign of the future prosthesis.
This software does not necessarily revolutionize the surgical procedure, but above all improves the conditions of reliability and security. They allow the practitioner to anticipate thepositioning of the implant and the resulting surgical procedure. [6] Most implant planning systems use CT or CBCT DICOM data for bone diagnostics. Three-dimensional reconstructions and multiplanar cross-sections oriented along the alveolar process in the implant region are available in all systems to review important parameters for the implant position. [7] imaging artefacts can occur distorting the tooth surface and bone volume. Implant planning software systems provide automatic segmentation of bone, teeth or soft tissues; however due to artifacts these default settings could not be used to display specific anatomical structures. Manual segmentation by limiting the window of grey values for the display of three-dimensional models is necessary and possible in all systems. [8] The importation, segmentation and pre-processing of radiographic data is crucial for the accurate transfer of the planned implant position to the surgical site. Radiographic data and virtual dental models are aligned with each other using either the tooth surface displayed both in CT or CBCT and in virtual dental models or with the help of reference markers in a radiographic splint. Incorrect matching between CT or CBCT and virtual models is known to happen after registration in relation to the number of existing metallic restorations. [9] It is possible to use either an intra-oral optical scan or an impression or model scan, respectively, to produce a virtual dental model if the data is imported in STL format.
Intra-oral optical scanning reduces the steps and thus the time required to produce virtual models. In addition to the promising efficiency of intra-oral scanners, the accuracy of intra-oral optical scanning is still not fully validated in vivo. On the other hand, extraoral optical scanning of stone casts has shown high accuracy (10 μm). [10] This means that depending on the implant system used, the drilling sequence and insertion of the implant is either performed in one step or through the drill guide. The software used in the examination has enabled guided implant placement for a number of integrated systems. The choice of implant planning software therefore depends on the specific implant systems used in daily routine.
The positioning of the drill guide on the teeth and mucosa, respectively, allows a more precise transfer of the implant position than the bone support. The operator is able to choose between the three support surfaces. The time required for the personal design and/or manufacture of the drill guide and the cost of the software must be taken into account by the user when using or selecting virtual implant planning software. [11] 871 It has to be considered that the user's experience plays an important role in any CAD software. According to the user's experience and affinity for digital products, the learning curve may vary. In conclusion, the authors find that one planning software is more intuitive than the other, which is very subjective. Before choosing a system, it is recommended to test as much as possible to find a satisfactory product.
Drilling guide:
Three types of computer-generated surgical guides are currently available: supported by teeth, mucosa and bone. Tooth-supported guides are used in cases of partial edentulism [12].
The surgical guide is conceived to rest on other teeth in the arch to ensure a precise fit of the guide. Mucosasupported guides are primarily used in fully edentulous cases and are designed to rest on the mucosa. Accurate registration of the occlusion between the arches is of critical importance when these guides are used to ensure accurate positioningof the surgical guide [13] and placement of screws or pins priorto implant placement. In addition, pins or provisional implants can be placed with all systems to facilitate fixation of the drill guide during the procedure.
The individual design of the drill guides allowed the user to choose the supporting surfaces according to the individual patient case. While most systems (NC, SIM, CDX, IST) suggest a closed design of the guide, an "open" design may be beneficial for more visibility, accessibility and less risk of interference with hard or soft tissue. Consequently, the insertion of windows in the closed design becomes important. Because of the centralized design and production of drill guides, the user must provide individual information for any design specialty before manufacturing. Bone supported guides can be used in partially toothless or fully edentulous cases, but are mostly used in fully edentulous cases where there is significant crestal atrophy and where the proper seating of a mucosasupported guide is doubtful. Such guides require the elevation of a thick flap to expose the bone in the intended implant sites and adjacent areas for a complete and stable seating of the guide on the bony ridge. [14] The placement of dental implants using CT-guided drill guides is known to improve safety over the freehand technique as well. Based on the NobelGuide protocol, when the guided abutment is used to secure the immediate restoration, the accuracy should be sufficient to insert a final prefabricated restoration at the time of implant surgery. However, no CT-guided drill guide technology exists today with absolute accuracy. The literature on stereolithographic guides shows errors in all dimensions between virtual planning and the resulting implant positions [16].
According to the literature, implants placed by bone-supported guides have the highest mean deviations, while implants placed by mucosa-supported guides have smaller deviations. Dental-supported guides have the smallest measured deviation. A single guide, using metal guide sleeves and rigid screw or pin fixation with specific drilling instrumentation, further minimizes the error. [15] Clinical case reporting the digital steps for implant planning using implaStation software:
Conclusion:-
The implant guided surgery can offer many advantages to this discipline, like precision, predictability of the results and more simple steps in the prosthetic steps, alearning curve must be conducted before facing complex cases,the clinician must understand the limitations and advantages associated with guided surgery so as to apply the benefits of this rapidly evolving technology when appropriately indicated. | 1,920.8 | 2021-02-28T00:00:00.000 | [
"Engineering",
"Medicine"
] |
Short-Block-Length Low-Density Parity-Check Codes-Based Underwater Acoustic Spread-Spectrum Communication System
: Low-density parity-check (LDPC) codes are commonly used in communication systems to improve the system performance, but LDPC codes takes too long for decoding, making communication inefficient and unsuitable for short-frame data transmission methods. In underwater acoustic channels, spread-spectrum communication becomes an effective way to realize long-distance communication. This paper combines short-block LDPC codes with a direct sequence spread spectrum and soft spread spectrum in underwater acoustic communication, addressing the problem of the inapplicability of conventional LDPC codes. The applicability of the proposed method in this paper is verified through simulation tests and pool experiments. The results indicate that the proposed communication system achieves lower bit error rates compared to the classical coding methods used in underwater acoustic spread-spectrum communication systems under the same channel conditions.
Introduction
Underwater acoustic channels are complex and variable [1][2][3], and spread-spectrum communication techniques [4][5][6] are often used for robust acoustic communication.Considering the low-latency requirements of the communication system and the frame data volume of underwater acoustic spread-spectrum systems, short-block-length code is generally preferable in terms of its decoding latency and short-frame-data transmission.
MN Danish et al. constructed a quasi-cyclic LDPC (QC-LDPC) code based on Euclidean geometry and cyclic decomposition, which has a shorter girth, and, by comparing the BER performance of LDPC codes based on the randomized construction method with those constructed based on this method under different modulation modes, the (256,128) code based on the design of the method has a good performance [7].Medova L R et al. proposed a new method for constructing LDPC codes based on the Orange Book of the Consultative Committee on Space Data Systems (CCSDS), "Short Block Length LDPC Codes for TC Synchronization and Channel Coding", and the simulation experiments show that, compared with the LDPC codes in the experimental specification, the LDPC code constructed using this method can obtain about a 0.4 dB gain when the SER is 1 ×10 −7 [8].Ranganathan S V S et al. proposed a protograph-based Raptor-like (PBRL) low-density parity-check code design method that can obtain a better error frame rate at short-code-block lengths [9].Abdu-Aguye U F et al. constructed short-block LDPC codes using an improved progressive edge-growth (PEG) algorithm; the LDPC codes constructed by this method have a shorter girth with a better approximate cycle extrinsic message degree than the existing PEG algorithm [10].
For spread-spectrum coding systems, in 2020, Rahman et al. [11] applied coding techniques to an ultrawideband spread-spectrum system and compared the performance of the spread-spectrum system using Turbo [12][13][14], low-density parity check (LDPC) [15,16] and Polar codes [17][18][19].The direct sequence spread spectrum (DSSS) with a bit error rate (BER) of 10 −4 and a bandwidth of 1.2 GHz provided a spread-spectrum gain of about 21 dB.The spread-spectrum system using LDPC codes achieved a combined gain of over 30 dB, allowing for the successful retrieval of message signals with 1000× higher power interference.Peng et al. applied spread-spectrum coding techniques to UV scattering communication systems.Using the direct spread-spectrum method and LDPC codes with a code rate of 1/2 and a code length of 1024, the results showed that the coded system could achieve a BER of 10 −2 at −2 dB, while the non-coded system achieved a BER of 10 −1 [20].Wei X F et al. combined QC-LDPC code with spread-spectrum technology and high-order modulation technology, and the performance of an underwater acoustic spread-spectrum communication system is investigated: through simulation experiments, the underwater acoustic spread-spectrum system combining LDPC code has a better performance compared with the spread-spectrum system combining Turbo code, and can obtain a better BER performance under a low signal-to-noise ratio [21].
For spread-spectrum systems in underwater acoustics communications, in 2021, Yang G et al. addressed the signal distortion problem caused by the Doppler effect in mobile underwater acoustic communication scenarios by using different spread-spectrum codes with different frequency offsets as local reference signals, correlating the received signals one by one and searching for the maximum correlation value in the frequency domain and the code domain in order to complete the signal descaling and Doppler estimation.Simulations and experiments show that, compared to the average Doppler-compensated sliding correlation spread-spectrum method, this method has a better BER performance [5].Sun D. et al. propose a Doppler tracking and compensation algorithm for direct spreading based on the fuzzy function method, which achieves high Doppler estimation accuracy at a 20 dB signal-to-noise ratio through high-precision delay estimation.Although the underwater acoustic spread-spectrum technique has strong multipath resistance by virtue of the good autocorrelation property of pseudorandom sequences, the multipath delay exceeding the spread-spectrum symbol length and the non-minimum phase underwater acoustic channel still bring serious inter-symbol interference (ISI) to the spread-spectrum signals, which affects the system reception signal-to-noise ratio (SNR) [22].Sozer E. M. et al. used the RAKE receiver processing structure in the DSSS system to improve the SNR gain by utilizing the multipath energy [23].Stojanovic M. et al. proposed a hypothesis-feedback equalization (HFE) algorithm in order to solve the effects of channel time-variation and ISI on the underwater acoustic spread spectrum, and the idea of judgment-feedback equalization can be applied in underwater acoustic spread-spectrum communication systems [24].
For the application of coding techniques in underwater acoustics communication, Xiaomei X et al. studied the performance of LDPC code in positive sound velocity gradient (PSVG), constant sound velocity gradient (CSVG) and negative sound velocity gradient (NVG) underwater acoustic channels, and the simulation shows that LDPC code has the best performance in the NSVG underwater channel, the second best performance in the ISVG underwater channel and the worst performance in the PSVG channel, and that there is a difference of about 4 dB compared to the former two [25].As researchers recognize the changes in the harshness of the underwater channel environment, channel coding techniques based on adaptive code rate adjustment have been applied in underwater acoustic communication technology.Among them, the fountain code, which can generate arbitrary length characters, is a typical representative.It has the feature of coding without a code rate, which makes it have good application prospects in time-varying underwater acoustic channels.Therefore, in recent years, the main fountain codes LT code (Luby Transform Code), Raptor code, Strider code, etc., in underwater acoustic communication research have been put on the agenda, and there are preliminary experimental results that show that they have good error correction capabilities.Padala S K et al. applied spatially coupled low-density parity-check (SC-LDPC) code in an underwater acoustic OFDM communication system that has a high communication rate with low equalization complexity.Simulation experiments demonstrate that the performance of protograph-based SC-LDPC code is improved by about 1 dB at 1 ×10 −4 BER compared to the general LDPC code with the same delay under the condition of a shallow water acoustic channel with 1000 m and a 10 KHz bandwidth [26].
In this paper, we study an underwater spread-spectrum system combining the Consultative Committee for Space Data Systems (CCSDS) 231.1-O-1 standard LDPC codes, and verify the system performance through simulations and water pool experimental analysis.The results show that the method proposed in this paper is suitable for underwater acoustic complex channels and the BER performance is improved compared to other existing coding methods.The LDPC coding and spread-spectrum methods used are listed in Table 1.The remainder of this paper is organized as follows.Section 2 introduces the CCSDS codes and their encode/decode algorithms.Section 3 describes the DSSS, M-ary spreadspectrum, and cyclic-shift-keyed (CSK) spread-spectrum.Section 4 presents the simulated BER performance of the spread-spectrum coding system, and Section 5 analyzes the experimental results given by this spread-spectrum coding system.Section 6 discusses the results presented in this paper, before Section 7 concludes with a summary of this study.
LDPC Codes
The channel coding technique involves extending the original bit information by introducing parity bits and recovering the original information at the receiving end based on the correlation between the bit information.LDPC codes are linear block codes, the continuous binary sequence of symbols output from the source is called a message bit and the redundant binary sequence output after encoding according to certain rules is called a code word.In (n, k) linear packet codes, the message bits are often divided into multiple groups of message packets of length k and sequentially encoded as code words of length n.A message code of length k can represent a total of 2 k types of messages.The message is mapped one-to-one with the codeword.Its code rate R = k n denotes the average number of message bits carried by a single code bit.Benefiting from the low-density feature of their check matrix, LDPC codes with iterative decoding based on belief propagation can obtain good error correction.
CCSDS Code
The check matrix of CCSDS codes consists of a submatrix of M = k/4 = n/8, where n, k denote the code word length and the original bit length, respectively.Let I M denote the identity matrix, 0 M denote the zero matrix, Φ k denote the identity matrix cyclically shifted right by k bits and ⊕ denote the modulo-two addition of matrix elements at the corresponding positions.The check matrix can then be written as From the check matrix of the CCSDS code, its generator matrix can be calculated by setting where Q, P denote the submatrix of the first 4M and last 4M columns of the check matrix, respectively.Then, we have where W can be calculated from
LDPC Decoding Algorithm
Based on the low-density characteristics of the LDPC check matrix, despite the belief that propagation-based iterative decoding algorithms is suboptimal, the result can still be obtained close to the optimal decoding criterion.The sum product algorithm (SPA) is a classical iterative decoding algorithm that accomplishes iterative decoding by passing messages between nodes.The log-likelihood ratio sum product algorithm (LLR-SPA) replaces probability domain calculations with likelihood domain calculations, reducing the algorithm complexity without changing the decoding performance.
In addition to matrix representation, LDPC codes can also be represented by Tanner graphs, which can be used to better illustrate the decoding algorithm.Tanner graphs are bipartite graphs, where nodes on the graph are classified into two categories: variable nodes (VNs) and check nodes (CNs), and lines connecting the two categories of nodes are called edges.Their equivalent Tanner graph can be obtained based on the check matrix H.According to this rule, the VN can correspond to the coded bits in the check equation, while the CN corresponds to the set of check equations.Tanner graphs are often used to describe sum-product decoding algorithms.An example of a Tanner graph is given in Figure 1.Let the jth variable node (VN) be V N j and the ith check node (CN) be CN i .In the check matrix, element h ij = 1 indicates the existence of an edge between CN i and V N j on the Tanner graph.The specific LLR-SPA algorithm is as follows.
Step 1. Initialize the variable nodes according to Equation (7), where L j denotes the result of the channel message after initialization, y j denotes the actual value received by the channel and v j denotes the estimated value of the code word.According to the Tanner diagram, for h ij = 1, let L j→i = L j : Step 2. The CN is updated to calculate the extrinsic information passed according to Equation (8), where L i→j denotes the extrinsic information passed from CN i to V N j , N(i) denotes the set of nodes connected to CN i and j denotes any variable node connected to CN i except V N j : Step 3. The VN is updated and the extrinsic information passed is calculated according to Equation (9), where L j→i denotes the extrinsic information passed from V N j to CN i , N(j) denotes the set of nodes connected to V N j and i denotes any check node connected to V N j except CN i .
Step 4. Sum the LLR according to L i→j (10) Step 5. Termination criterion: for j ∈ [0, n − 1], judge the code bits according to Equation (11).If the check condition v H T = O is satisfied, terminate the decoding.Other- wise, the decoding has failed; return to step 2 and repeat the process until the decoding succeeds or the maximum number of iterations is reached.
Spread-Spectrum Technology
Spread-spectrum technology refers to the extension of narrowband data to a wider band and its transmission.The receiver obtains the spread-spectrum gain and recovers the data through correlated de-spreading.During this process, as the noise in the channel only experiences one spread spectrum, the energy is extended to a wider band.Thus, the in-band noise energy is reduced and the signal-to-noise ratio of the received signal is enhanced.With a better autocorrelation performance of the spread-spectrum sequence, any multipath energy beyond the duration of a code slice can be treated as noise.As the spread-spectrum symbol duration generally exceeds the multipath delay of the shallow water channel, ISI does not affect too many subsequent symbols, so the spread-spectrum technology itself has a strong anti-multipath performance.
Direct-Sequence Spread-Spectrum
The communication principles of the direct spread-spectrum system are shown in Figure 2. The transmitter spreads the signal to a wider frequency band, which is transmitted by carrier modulation and the channel, and the receiver performs the de-spreading of the received signal, restoring the broadband signal to a narrowband.The de-spread signal is then demodulated by the local carrier to restore the original information.
M-ary Spread-Spectrum
The M-ary spread-spectrum communication system improves band utilization compared with a direct spread communication system.The theoretical communication rate is log 2 M times that of direct spreading using a random sequence of the same order, and each spreading symbol can carry log 2 (M) bits of information, where denotes rounding down.The M-ary spread-spectrum exploits both the good autocorrelation properties and the quasi-positive cross-correlation properties of pseudorandom codes, using different spread-spectrum sequences for different spread-spectrum symbols to characterize this information.M-ary spread-spectrum communication is illustrated in Figure 3.At the transmitter side, the data are divided into multiple groups of k bits through a serial-to-parallel conversion, which, for M-ary spreading, has 2 k = M.Each k bits of data constitute a spreading symbol, which is mapped to a spreading code according to certain rules.The k bits of data contain a total of 2 k binary sequences, which also correspond to 2 k spreading codes.The binary sequence is first converted to the corresponding decimal number p[m], 0 ≤ p[m] ≤ M − 1, and then c p[m] (t) is selected as the spreading code from the mutually quasi-orthogonal M-ary spreading codes according to certain rules.We express c p[m] (t) as g(t) denotes a pulse-forming function.The orthogonal M-ary spread-spectrum receiver consists of M correlators, which makes the hardware complexity of the receiver relatively high.To overcome this problem, the CSK spread-spectrum method is used to exploit the cyclic correlation property of pseudo-random codes, which are used to achieve spread-spectrum communication by splitting the source information into a few bits of spread-spectrum symbols that are then mapped into spread-spectrum codes.M-ary spread-spectrum communication achieves the mapping of symbols to spreading codes using pseudo-random codes with different sequences of the same length, such as Gold codes, where each symbol corresponds to a spreading code of that length.In contrast, CSK maps symbols to spreading codes using different cyclic shifts of the same spreading code.CSK spreading reduces the hardware complexity while maintaining transmission efficiency, but introduces new problems.
Figure 4a shows the results of cross-correlation between M-ary sequences of different principal polynomials of order seven, with a poor cross-correlation performance between spreading codes.Figure 4b plots the cross-correlation characteristics of a cyclic shift sequence of an M-sequence of order seven, spaced by 15 code pieces and carrying three bits of eight ary per symbol.In addition to the autocorrelation peak, there are several correlation peaks with similar energies.This indicates that if the signal is subject to severe multipath effects in the transmission process of the channel, such as the cross-correlation peak of spreading code 1 and cyclic code 2, which is close to the energy of the autocorrelation peak, the energy of the correlation peak is likely to exceed the energy of the autocorrelation peak under the influence of the superimposed multipath.This will result in a decoding error.The multipath component in this case cannot be regarded as noise and requires channel equalization, which leads to an increase in hardware complexity.
Overview of Spread-Spectrum Coding Systems
The communication schematic of a spread-spectrum coding system is shown in Figure 5, where bits of information are first coded by the channel and redundant check bits are added to obtain a code word for transmission.The length of the information bit before coding is given as k, the length of the code word after coding is given as n and the code rate is given as R = k/n, indicating the amount of information carried by each channel bit.To reduce the effects of ISI, the baseband signal is waveformed.The baseband signal is then spread and carrier-modulated to be transmitted via the transducer to the underwater acoustic channel.After the receiver has received the acoustic signal, the signal is demodulated by the local carrier, filtered by low-pass filtering to remove out-of-band noise and then recovered by matched filtering and de-spreading.The input to the decoder varies according to the spreading method used.For the direct spread system, the information is fed into the decoder without judgment, which allows the decoding performance of the soft judgment decoder to be fully utilized.For the M-ary spread-spectrum system, the judgment rule of detecting the maximum energy of the correlated peaks means that the information obtained after decoding is in the form of symbols, and is sent to the decoder as a 0.1 bit stream.This loses some of the channel information.Overall, the spread-spectrum coding system using the soft spread-spectrum combined with LDPC codes obtains a limited coding gain, and is inferior to the direct spread coding system.
Simulation Analysis 4.2.1. Channel Description
In this paper, we use Bellhop to simulate a channel that is as close as possible to the experimental conditions of the pool and bring it into the simulation experiments with the condition parameters of this channel (Figure 6): Here, the depth of the simulated water body is set to 10 m, and the sound velocity profile is a negative gradient sound velocity environment, in which the depth of 0 m results in the speed of sound at the surface of the water being 1510 m/s, and the depth of 10 m results in the speed of sound at the bottom of the water being 1500 m/s.It is assumed that the surface of the water is a flat water surface with no undulation, the upper part of it is a vacuum environment, the bottom of it is assumed to be the liquid seabed and the sound velocity is 1650 m/s.
Simulation of Direct Spread-Spectrum Coding Systems
The simulation results for the direct spreading coding system based on a Gaussian channel and multipath channels are shown in Figures 7 and 8.The sampling frequency f s = 16 kHz, the carrier frequency f c = 2 kHz, the bandwidth is 2 kHz, the spreading code is a 5th-order m-sequence and the spreading gain is 31.The modulation method is binary phase-shift keying (BPSK), the encoding code is CCSDS code, the decoding algorithm is LLR-SPA and the maximum number of iterations is 100.The simulations compare the performance of the direct spreading non-coding system with that of the direct spreading coding system.The direct spreading sequence system has the best performance under Gaussian channels and the performance decreases under multipath channels.With a BER of 10 −3 , a coding gain of about 7.2 dB can be obtained using CCSDS(512,256) codes.The simulation results also compare the performance of the spread-spectrum coding system using CCSDS codes with that of (2,1,7) convolutional codes, Bose-Chaudhuri-Hocquenghem (BCH) codes and Turbo codes.Under 1 × 10 −4 BER conditions, the code length is the same as 256 and the code rate is 1/2 for both Turbo and LDPC codes.Compared to Turbo codes, the direct spreading sequence system with CCSDS codes has a gain of about 0.4 dB.
M-ary Spread-Spectrum Coding System Simulation
The simulation results for the M-ary spread-spectrum coding system under a Gaussian channel and multipath channels are shown in Figures 9 and 10, where M = 16.Using a 5th-order Gold sequence as the spread-spectrum code, with a bandwidth of B = 2 kHz, carrier frequency f c = 2 kHz, and sampling frequency f s = 16 kHz, the M-ary spreadspectrum system with CCSDS(512, 256) codes achieves a BER of 10 −3 with a minimum SNR of −14.94 dB; the minimum SNR required for the uncoded system to achieve 10 −3 BER is −8 dB.Thus, the coding gain is approximately 6.94 dB.Under 1 ×10 −4 BER conditions, the code length is the same as 256 and the code rate is 1/2 for both Turbo and LDPC codes.Compared to Turbo codes, the M-ary spread-spectrum system with CCSDS codes has a gain of about 0.3 dB.
CSK Spread-Spectrum Coding System Simulation
The simulation results for the CSK spread-spectrum coding system under a Gaussian channel and multipath channels are shown in Figures 11 and 12.In these simulations, M = 16, so 16 different spreading codes with a 5th-order M-sequence and 2-bit cyclic shift are used.The bandwidth B = 2 kHz, carrier frequency f c = 2 kHz and sampling frequency f s = 16 kHz.The simulation results are consistent with the theoretical analysis in that the direct spread coding system has the best coding gain while the soft spread coding system has limited coding gain.Spreading coding systems using short LDPC codes (CCSDS codes) achieve higher coding gains than spreading coding systems using other channel coding algorithms such as Turbo codes and convolutional codes.Under 1 × 10 −4 BER conditions, the code length is the same as 256 and the code rate is 1/2 for both Turbo and LDPC codes.Compared to Turbo codes, the CSK spread-spectrum system with CCSDS codes has a gain of about 0.3 dB.
Experimental Conditions and Parameter Settings
Pool experiments were conducted to verify the feasibility of the spread-spectrum coding system.The pool measures 45 m × 6 m × 5 m, the pool bottom is deep sand and the pool wall has an anechoic tip split.Figure 13 shows a schematic diagram of the pool experiments, where the low-frequency transducer and the receiving hydrophone are nondirectional; the receiving hydrophone is a BK8105 hydrophone with a receiving sensitivity of −205 dB.Figures 14 and 15 show the placement of the transducer during the pool experiment and the overall experimental scene, respectively.Table 2 lists the parameters of the coded spread-spectrum system.The channel response was first tested.Figure 16 shows the signal response curve with normalized amplitude.
Direct Spread-Spectrum Coding System
The BER performance of the DSSS communication system under different coding methods is shown in Figure 17.Analysis of Figure 17 indicates that the LDPC coding/decoding method using CCSDS codes can achieve a better coding gain than other channel coding algorithms, such as Turbo code, convolutional code and BCH code.The performance of (2, 1, 7) convolutional codes is related to the quantization accuracy, which is 4-bit quantization.The performance of Turbo codes is similar to that of LDPC codes at a lower SNR, and as the SNR increases, the method proposed in this paper has the best performance when the BER is 1 × 10 −4 , where it has a BER performance improvement of 0.3 dB compared to Turbo codes.
M-ary Spread-Spectrum Coding System
The experimental results of the M-ary spread-spectrum system are shown in Figure 18.The M-ary spread-spectrum error comes from the maximum correlation peak detection error.This causes the M-ary spread-spectrum to lose part of the channel information, and can make all bits in a symbol erroneous.Together, these issues affect the performance of the M-ary spread-spectrum coding system.
CSK Spread-Spectrum Coding System
The experimental results for the CSK spread-spectrum communication system under different coding methods are shown in Figure 19.Analyzing the results of pool experiments, for channel coding methods with similar code lengths and consistent communication rates, spread-spectrum communication systems incorporating CCSDS codes have certain performance advantages over spread-spectrum communication systems incorporating other coding methods.
Significance of the Proposed Method
The spread-spectrum coding system proposed in this paper has a better BER performance than the underwater acoustic spread-spectrum communication system using classical coding methods, and the technique enables robust transmission of short-frame data.The performance of the spread-spectrum coding system combined with CCSDS short-block LDPC codes has been verified through simulations and pool experiments to outperform the spread-spectrum system combined with the classical coding method.
The DSSS + LDPC spread-spectrum coding system has the best BER performance and is suitable for applications with limited transmission energies and high BER requirements, such as satellite communications.The soft spread-spectrum + LDPC spread-spectrum coding system offers improved band utilization, but is limited by the spread-spectrum method, which reduces its BER performance.This approach is more suitable for communication scenarios with limited bandwidth resources.
Limitations of the Proposed Method
The soft spreading coding system combined with LDPC codes proposed in this paper loses channel information during the process of mapping the spreading sequence to symbols.This degrades its BER performance.To achieve an improved BER performance, the main correlation peak and the secondary correlation peak symbols of the M-ary correlator decoding could be combined and the input to the decoder could be adjusted to compensate for the partial loss of channel information.In addition, the performance of the method can be further verified in extreme environments through sea trial experiments.
Conclusions
This paper has proposed a short-block LDPC coding system for underwater acoustic spread-spectrum communication that is highly adaptable to the short-frame data transmission process.Simulation experiments and pool experiments have verified the effectiveness and practicality of the proposed method in this paper.Simulation analysis shows that the proposed direct spread coding system can achieve a coding gain of up to 7.2 dB in BER compared with the direct spread non-coding system.The proposed M-ary spread coding system and CSK spread coding system can achieve coding gains of up to 6.94 dB and 5.64 dB, respectively, compared with their corresponding spread non-coding systems.Pool experiment results also show that the proposed method has a better BER performance compared to conventional coding methods in underwater acoustic communication systems.This method has good application prospects in the field of underwater acoustic communication.
Figure 4 .
Figure 4. Spread-spectrum sequence correlation characteristics.(a) Seventh-order M-series correlation properties; (b) Cyclic shift sequence correlation properties for seventh-order M-sequences.
Figure 5 .
Figure 5. Communication schematic for spread-spectrum coding systems.
Figure 6 .
Figure 6.Channel impulse response of the simulation.
Figure 7 .
Figure 7. BER performance of DSSS coding systems in Gaussian channel.
Figure 8 .
Figure 8. BER performance of DSSS coding systems in multipath channel.
Figure 9 .
Figure 9. BER performance of M-ary spread-spectrum coding systems in Gaussian channel.
Figure 10 .
Figure 10.BER performance of M-ary spread-spectrum coding systems in multipath channel.
Figure 11 .
Figure 11.BER performance of CSK spread-spectrum coding systems in Gaussian channel.
Figure 12 .
Figure 12.BER performance of CSK spread-spectrum coding systems in multipath channel.
Figure 17 .
Figure 17.BER of DSSS communication system under different coding methods.
Figure 18 .
Figure 18.BER of M-ary spread-spectrum communication system under different coding methods.
Figure 19 .
Figure 19.BER of CSK spread-spectrum communication system under different coding methods.
Table 1 .
Spread-spectrum coding system research content. | 6,354.6 | 2023-09-14T00:00:00.000 | [
"Computer Science"
] |
Application of DFT Simulation to the Investigation of Hydrogen Embrittlement Mechanism and Design of High Strength Low Alloy Steel
In this work, first-principles methods were performed to simulate interactions between hydrogen and common alloying elements of high strength low alloy (HSLA) steel. The world has been convinced that hydrogen could be one of the future clean energy sources. HSLA steel with a balance of strength, toughness, and hydrogen embrittlement susceptibility is expected for application in large-scale hydrogen storage and transportation. To evaluate the property deterioration under a hydrogen atmosphere, hydrogen embrittlement (HE) of HSLA steel attracts attention. However, due to the small size of hydrogen atoms, the mechanism of HE is challenging to observe directly by current experimental methods. To understand the HE mechanism at an atomic level, DFT methods were applied to simulate the effects of alloying elements doping in bcc-Fe bulk structure and grain boundary structure. Furthermore, the potential application of DFT to provide theoretical advice for HSLA steel design is discussed.
Introduction
The conflict between resource protection and increasing energy consumption worldwide requires further development and application of renewable energy. Meanwhile, most renewable energies such as solar and wind power are restricted by environmental factors [1]. As a clean, renewable energy and energy storage media, hydrogen attracts attention recently for its high chemical energy density (142 MJ/kg), which is three times larger than petrol. However, as the lightest molecule, the storage and the transport of hydrogen limits the large-scale application. Improving the storage pressure of hydrogen gas can evocatively increase the storage density and efficiency of hydrogen gas.
Currently, austenitic stainless steels are widely accepted as the candidate materials for hydrogen energy-related equipment. However, the low strength grade of austenitic stainless steels could not fulfill the increasing hydrogen storage pressure. High strength low alloy (HSLA) steels have been widely applied for transporting oil and gas [2]. With a superior combination of strength, toughness, and weldability, HSLA steel is also considered as the candidate material for gaseous hydrogen storage and transportation. However, the ductility of conventional metal materials, especially in high strength steels, degrades under hydrogen environment [3]. This phenomenon is commonly known as hydrogen embrittlement (HE) [4]. The hydrogen embrittlement phenomenon seriously deteriorates the mechanical properties of most structural steels, which might directly threaten the safety of large-scale hydrogen applications [5].
Multiple factors were suspected to be responsible for the HE of materials, such as the strength of materials, residual stress in materials, concentration of hydrogen traps, heat treatment et al. [6][7][8]. Almost all the influential factors are affected by the chemical composition and microstructure of the material. Experimental methods have been tried to investigate the hydrogen embrittlement mechanism. However, due to the small size of hydrogen atoms, the mechanism of HE is challenging to observe directly by current experimental methods [9][10][11][12]. Therefore, a comprehensive investigation of the interaction between hydrogen and low alloy steels via computational simulation at an atomic scale is expected to improve the understanding of the HE of materials.
First-principles computational method based on density functional theory (DFT) is an effective method for theoretically studying the physical and chemical properties of materials at the atomic scale, that has been applied broadly to describe the electronic and atomic structures of materials at the atomic level in recent decades [13][14][15][16][17]. DFT calculation could simulate the interaction between hydrogen and alloy atoms and further be applied to investigate the mechanism of HE at the atomic level [18][19][20]. However, current first-principles research of HE mainly concentrated on describing and explaining the interactions of hydrogen with particular alloy elements in specific structures [21,22]. Lacking comprehensive interatomic investigation of common alloy elements underestimates the value of DFT simulation in HE investigation and design of HSLA steels.
In this research, two model plates of steel were characterized under high-pressure hydrogen gas to estimate the hydrogen embrittlement susceptibility. To understand the hydrogen embrittlement mechanism of the two model materials at an atomic level, the interactions of hydrogen and alloying elements in bcc-Fe were systemically studied utilizing first-principles simulation. The hydrogen dissolution energies and hydrogen diffusion coefficients in doped bulk structure and grain boundary were calculated. Additionally, the charge transfer and density of states (DOS) analysis were explored in detail. Furthermore, theoretical advice for designing HSLA steel with low hydrogen embrittlement susceptibility is discussed based on the DFT calculation.
Materials and Experiments
Two plates of model steel with a tensile strength higher than 790 MPa were designed and produced. Commercially pure metals melted utilizing a vacuum induction furnace. 50 kg cast ingots were hot processed to 16 mm plates via hot forging and hot rolling, followed by proper thermal treatment. Specimens were cut from the plate materials, wet ground, polished, and etched with HNO 3 -ethanol solution. A FEI Quanta 650 FEG field emission scanning electron microscopy (FE-SEM) was applied for microstructural observation.
Hydrogen embrittlement susceptibility of designed materials was evaluated utilizing low strain rate tensile tests and fatigue crack propagation tests. Both tensile properties and fatigue crack propagation properties were tested under high-pressure hydrogen gas in comparison with that under nitrogen gas. Uniaxial tensile tests at 2 × 10 −5 /s were performed, and reduction in area and elongation of a smooth tensile specimen under specific hydrogen/nitrogen pressure were measured, respectively. To generate plots of fatigue crack growth rate as a function of stress intensity factor range, pre-cracked specimens were tested using fracture mechanics methods.
DFT Calculations
The hydrogen dissolution energies and hydrogen diffusion coefficients in bcc-Fe bulk structure and grain boundary were studied by first-principles calculations based on DFT in the Vienna Ab-initio Simulation Package (VASP). The core electrons and the electron exchange were described utilizing the projector augmented wave (PAW) method, and the correlation was modeled with the Perdew-Burke-Ernzerhof (PBE) method. Plane-wave expansions are considered with a cutoff energy of 500 eV (c.f. Figure S1). All the structures were fully relaxed with the residual force on each atom less than 0.02 eV/Å, and the total energy was converged to 10 −6 eV/atom for the calculations. All calculations were carried out as spin polarized. The Brillouin zone (BZ) was sampled employing Monkhorst-Pack grids with a 5 × 5 × 5 k-point mesh for the bcc-Fe bulk structure (c.f. Figure S1), and a 5 × 5 × 1 k-point mesh for the bcc-Fe Σ5 GB. The optimized lattice constants are a = b = c = 2.834 Å for the bcc-Fe unit cell (c.f. Table S1), which is consistent with the experimental values a = b = c = 2.86 Å [22].
According to the typical transition state theory, based on the Arrhenius equation, the diffusion coefficient of a hydrogen atom can be calculated as [23][24][25][26]: where l is the hop distance; υ is the attempt frequency; E di f f is the activation energy for the diffusion of a hydrogen atom; k is the Boltzmann constant, and T is the temperature.
Hop distance (l) and attempt frequency (υ) could be calculated by employing the DFT simulation.
Results and Discussion
Chemical compositions of the two model materials (1# and 2#) are displayed in Table 1. The microstructures of both materials were characterized by an optical microscope and scanning electron microscope, typical bainite structures were observed in both materials, as displayed in Figure 1. Tensile and impact properties were first characterized to confirm the mechanical properties of the two types of steel after thermal processing. Both tensile and impact test results confirmed the yield strength of the two plates of steel above 790 MPa with sufficient impact absorbing energy (c.f. Table 2). From the mechanical property and microstructure characterization investigation, the two model types of steel were considered qualified. The mechanical properties of both model materials under the H 2 /N 2 pressure at 10 MPa were tested, respectively. Key properties of the low strain rate tensile tests are displayed in Figure 2a. It could be found that the tensile elongation under 10 MPa H 2 atmosphere for steel 2# decreased by 11.23% compared with that under 10 MPa N 2 atmosphere. While the tensile elongation determined under H 2 atmosphere reached over 95% for steel 1#, compared with that under N 2 atmosphere. Another important tensile property to evaluate hydrogen embrittlement susceptibility is the ratio of reduction in area. In both model materials, the reduction in area under H 2 gas decreased to 98.07% and 97.15% in comparison to the ones tested in N 2 gas, respectively. In view of low strain rate tensile tests, steel 1# behaves with less hydrogen embrittlement susceptibility. It has been found that cracks due to HE might grow rapidly [27]. Thus, the crack propagation properties of model steels were investigated to further compare the HE susceptibility of the two materials. Figure 2b plots the crack growth rate (crack extension per load cycle, da/dN) as a function of the stress intensity factor range(∆K). The crack growth rate increased with higher stress intensity, and both types of steel behaved at higher crack growth rates in the hydrogen atmosphere. At ∆K = 30, the crack growth rate of steel 1# in hydrogen gas is 10.44 times higher than that in nitrogen gas, while the crack growth rate ratio of steel 2# is 16.31 ( Figure 2b). Both fatigue crack propagation tests and low strain tensile tests indicate that steel 1# behaves a less susceptibility of hydrogen embrittlement in high-pressure hydrogen gas.
To understand the different HE behavior between the model materials from the atomic level, first principles method calculations were performed. We first studied the effects of alloying elements (Cr, Mn, Ni, and Mo atoms), which differ the two materials in chemical composition, on H dissolution energies of bcc-Fe bulk structure and bcc-Fe grain boundary (GB). For the periodic boundary condition, 4 × 4 × 4 bcc-Fe supercell was used to keep the distance between two repeated defects far enough, and thus the interaction between the defects could be ignored. The 4 × 4 × 4 bcc-Fe supercell includes 128 Fe atoms with the optimized lattice constants a = b = c = 11.33 Å, as shown in Figure 3a. The atomic structure diagram of bcc-Fe Σ5 GB was modeled to represent symmetric tilt grain boundaries based on an example of a real boundary with a vacuum layer of 15 Å is shown in Figure 3b [28,29]. In the calculation of doped atoms at the bcc-Fe Σ5 GB, the upper and lower four layers of Fe atoms were fixed. After structural optimization, the lattice constants became a = 5.73 Å, and b = 9.06 Å. The H dissolution energies of pure bcc-Fe bulk structure and pure bcc-Fe Σ5 GB were calculated to investigate the effects of alloying elements. The H dissolution energy E s is defined as: where E (structure with H) is the total energy of the pure or doped bcc-Fe bulk structure or GB with an interstitial H atom, and E (structure) is the total energy of the pure or doped bcc-Fe bulk structure or GB without H atoms.
2 refers to the energy of an H atom in a single H 2 molecule. Hence, a lower H dissolution energy indicates that the structure is more favorable to combine with H atoms.
The H dissolution energies of different locations were first calculated, and the most stable one was chosen for further calculation and discussion. In the bcc-Fe bulk structure, an H atom can occupy an octahedral interstitial site (o-site), or a tetrahedral interstitial site (t-site). The calculated E s in the o-site is 0.35 eV and E s in the t-site is 0.22 eV, which is consistent with the results calculated by W. Counts et al. [22]. Thus, we uniformly optimized the structure of the H atom in the t-site for subsequent calculations. For the pure bcc-Fe Σ5 GB model, the calculated E s is −0.26 eV. A negative value for the H dissolution energy represents an energy release when the H atom diffused into the GB interstitial site. That indicates the H atoms are easily dissolved at grain boundaries, where the HE is more likely to occur [30,31].
The H dissolution energies of bulk and Σ5 GB structures of bcc Fe with different alloying elements (Cr, Mn, Ni, and Mo atoms) were calculated by Equation (2). One Fe atom in the bcc-Fe bulk/Σ5 GB structure was substituted by Cr, Mn, Ni or Mo atom, respectively, corresponding to the doping concentration of 0.73, 0.77, 0.83 or 1.35% (mass fraction) in bulk structure, and 1.04, 1.10, 1.19 or 1.93% (mass fraction) in Σ5 GB structure. In Figure 4a,c, the blue atoms represent the alloying elements and the green ones represent the interstitial H atoms. Figure 4b The positive H dissolution energies, in bcc-Fe bulk structure with alloying elements, indicate that H atoms are either unstable or energetically unfavorable to occupy the lattice interstitial sites. The negative H dissolution energies, in bcc-Fe Σ5 GB structure with alloying elements, confirm that H atoms could stably occupy the interstitial sites at grain boundaries. In comparison to pure Fe structures, the H dissolution energies decreased while doping a Mn atom in bulk and GB structures. Additionally, the H dissolution energies increased in Cr-doped, Ni-doped, and Mo-doped structures. This indicates that Mn addition might lead to easier dissolution of H atoms in both bulk and GB structures.
To further understand the role of alloying elements in hydrogen damage, we studied the impact of alloying elements on hydrogen diffusion. Diffusion paths between different sites considering alloying elements were determined and studied employing the nudgedelastic band (NEB) methods [32,33]. This method is advantageous if the exact position of the transition point is unknown and/or if detailed information about the energy profile along the transition path is needed. Several images between two fully relaxed endpoints were calculated to simulate the diffusion pathway, and each image was relaxed until the perpendicular forces with respect to the minimum energy path were less than a given tolerance, which was set to 0.05 eV/Å in this case.
The diffusion of H atoms within the bcc-Fe bulk structure was investigated by employing CI-NEB calculations. H atoms at the interstitial site diffused to its equivalent site along the relax diffusion path, as illustrated in Figure 5a. For the hydrogen diffusion in pure bcc-Fe bulk structure, we obtained a diffusion barrier of 0.17 eV, as shown in Figure 5b, which is consistent with ab initio molecular dynamics simulation reported by Sanchez et al. [34] This indicates that the predicted hydrogen diffusion path is reasonable. The diffusion coefficient of a hydrogen atom in a pure bcc-Fe bulk structure can be estimated according to Equation The calculated hydrogen diffusion coefficient at room temperature (T = 298 K) is 6.03 × 10 -6 cm 2 /s, which is consistent with the literature value [35].
Meanwhile, the diffusion of H atoms within the bcc-Fe Σ5 GB structure was investigated. Figure 5d displays the schematic diagram of a hydrogen diffusion path in a bcc-Fe Σ5 GB structure with alloying elements.
Thus, the hydrogen diffusion coefficient of Σ5 GB at room temperature (T = 298 K) was calculated to 1.79 × 10 -13 cm 2 /s. This indicates that H atoms diffuse much slower in grain boundaries than in inner grains.
In comparison to bulk structures, GB structures show a higher diffusion barrier of H atoms (c.f. Figures 2 and 3). Xiao Zhou et al. presumed that H diffusion at GBs might be influenced by the different lattice patterns of the tilt axis because of the two-dimensional nature of GBs [36,37]. Meanwhile, the H diffusion depends on the alloying element in the bulk structure is relevantly equivalent. The structural differences between GB and bulk structures lead to the lower dissolution energy and higher diffusion barrier and behave as the slower H diffusion at grain boundaries. The slower diffusion and lower dissolution energy of hydrogen atoms at the grain boundaries might lead to the segregation of hydrogen atoms at the grain boundaries, which could lead to hydrogen embrittlement.
The hydrogen diffusion barriers and diffusion coefficients in bulk and GB structures with alloying elements were calculated. As shown in Figure 5b,c, the diffusion of H atoms inside the Cr-doped bcc-Fe bulk structure needs to cross a higher energy barrier than in pure Fe of 0.22 eV. On the other hand, the hydrogen diffusion barriers decreased for Mn-doped, Ni-doped, and Mo-doped bulk structures. The diffusion coefficient of H varied from 1.09 × 10 -6 cm 2 /s (for Cr-doped) to 6.16 × 10 -4 cm 2 /s (for Ni-doped) with doping alloy elements. The diffusion coefficients of the GB structure with alloying elements at room temperature kept slower than in bulk structures. However, the hydrogen diffusion coefficients in bcc-Fe Σ5 GB can be increased by orders of magnitude while doping alloying elements, especially by nickel (9.46 × 10 -8 cm 2 /s). Thus, the addition of alloying elements might contribute to the reduction of hydrogen accumulation, and benefit the properties of materials under hydrogen atmosphere.
To further understand the interaction of hydrogen and alloying elements and the influence of such interaction on the hydrogen embrittlement susceptibility, charge transfer, and density of states (DOS) analysis were explored. The alloying elements Cr and Mn doping in bcc-Fe Σ5 GB are exampled for illustration in detail.
The valence electron distribution of H in doped structures was analyzed utilizing the Bader Charge Analysis program code. The valence electron numbers of H in Cr and Mn doped structure are 1.29 e and 1.35 e, respectively. Which indicates that in Mn doped structure H gains more electrons and has strong interaction with the structure.
The differential charge density of H in Cr and Mn doped structure is defined as: where ρ (structure with H) is the total charge density of the doped structure with an H atom; ρ (structure without H) and ρ (H) are the charge density of the doped structure and H atom, respectively. Figure 6a Furthermore, for Cr doped structure with an H atom, the H-1s states mainly contribute above the Fermi level from 0.5 eV to 0.8 eV, and for Mn doped structure with an H atom, the H-1s states mainly contribute around the Fermi level. It is worth noting that the electronic density of states has enhanced due to the introduction of the hydrogen atom. In the ground state, the valence bands below the Fermi level (represented as 0 eV in Figure 6) are filled with electrons, and the conduction bands above are empty. The TDOS of Cr doping structure with H atom presents enhanced peaks at an energy of around 0.8 eV (c.f. Figure 6e, red arrow), which is located at empty bands. While in Mn doping structure with H atom, enhanced peaks appear at the energy from about −0.2 eV to 0.2 eV (c.f. Figure 6f, red arrows) and the DOS peaks below 0 eV would exhibit strong hybridization. The hybridization of H-1s states with Fe-3d states and Mn-3d states in Mn doping structure might enhance the interaction of H and Mn atoms in bcc-Fe Σ5 GB. Alloying elements Cr, Ni, and Mo doping in bcc-Fe bulk and Σ5 GB structures could increase H dissolution energies while alloying element Mn doping would decrease H dissolution energies. Moreover, doping alloy elements in the bulk structures could lead to the variation of H diffusion coefficients, but less pronounced than that in the Σ5 GB structures. According to the DFT analysis, in materials with a bcc-Fe matrix, the addition of Ni, Cr, and Mo might benefit the properties under hydrogen atmosphere, while Mn addition might deteriorate the properties of α-Fe based steel. That explains that model steel 1# with higher Ni, Cr, and Mo contents and lower Mn content might behave with lower hydrogen embrittlement susceptibility than model steel 2#. Furthermore, since Ni, Cr, Mo, and Mn are the most commonly used alloy elements in HSLA steel, outcomes of this work could provide theoretical advice for the designing HSLA steel with low HE hydrogen embrittlement susceptibility.
Conclusions
In summary, the hydrogen embrittlement susceptibility of two model materials was characterized under high-pressure hydrogen gas. The interaction of hydrogen and alloying elements (Cr, Mn, Ni, and Mo atoms) in bcc-Fe bulk and at grain boundary were investigated utilizing first-principles calculations. The main outcomes are summarized as follows: (a) Model steel 1# with higher content of Ni, Cr, and Mo behaves with lower susceptibility of hydrogen embrittlement in high-pressure hydrogen gas; (b) Alloying elements Cr, Ni, and Mo doping in bulk and Σ5 GB structures could increase H dissolution energies, while Mn doping could decrease H dissolution energies; (c) In comparison to bulk structures, GB structures show a higher diffusion barrier of H atoms and a lower H diffusion coefficient at grain boundaries; (d) Alloying elements significantly affect the hydrogen diffusion behavior, especially at Σ5 GB. The hydrogen diffusion coefficient for Ni dopingΣ5 GB structures increases by approximately six orders of magnitude.
Based on the DFT simulation, alloying elements Cr, Ni, and Mo might benefit the properties under hydrogen atmosphere. Additionally, Mn addition might deteriorate the properties of α-Fe based steel. DFT simulation can improve the understanding of the HE mechanism of HLSA steel and provide theoretical advice for alloy design.
Supplementary Materials: The following supporting information can be downloaded at: https: //www.mdpi.com/article/10.3390/ma16010152/s1, Figure S1: (a) The convergence tests for the plane-wave energy cut-off. (b) The convergence tests for the Monkhorst-Pack k-point grids; Table S1 | 4,968.6 | 2022-12-23T00:00:00.000 | [
"Materials Science"
] |
Applied Linguistic-Tú and Usted Spanish Personal Subject Pronouns
While the simple phonetics of Spanish language makes it easier to learn and speak irrespective of its grammar complexity, acquiring a good command of this language requires a serious and disciplined study of its grammar. The use of null and overt pronouns and their different grammar related forms in Spanish elevates the level of complexity when it comes to second language acquisition (SLA). In this regard, the teaching and learning of Spanish grammar still remains a subject of interest among linguists. Thereby, the article aimed to provide a guideline through which English language native speakers would gain an insight about language traits, associated with two pronouns and how they should be used in the speaking and writing context of Spanish language communication.
Introduction
Communication is instigated to express human experiences and traits.It is the channel through which an individual can communicate his thoughts.The most common approach used by an individual for communicating is through speaking or writing.These skills require a good understanding of language to be used, particularly its grammar (Ortega, 1990) 1 .Unlike English, Spanish is an inflected language.The verbs are potentially marked for tense, aspect, mood, person, and number (resulting in some fifty conjugated forms per verb).The nouns form a two-gender system and are marked for number.Pronouns can be inflected for J. L. Rivera DOI: 10.4236/ojml.2019.9100213 Open Journal of Modern Linguistics person, number, and gender, including a residual neuter (San José, 2010) 2 .The grammar of Spanish language possesses a rich, wide, and a variety of words, if compared to other languages.There are the words that are classified according to the use of orthographical accent or tilde "monosyllables words-pronoun tú".
There are words that require others to get a concrete meaning "Pronouns tú and usted plus pronouns adjacent"; "pronouns tú and usted plus verb conjugation".
There are words that can be omitted from the content of a sentence, already bequeathing its meaning to the following words "tú and usted".There are words that denote the use of what is known as Hispanic concept of proper etiquette "tú-informal/usted-formal", and from the point of view of translations from Spanish to English "tú and usted" are the English equivalent of "you" in most of the Spanish-speaking countries, excluding those where "vos" is the equivalent of "you".There are no additional efforts required for learning and speaking a language without studying its grammar; nevertheless, a serious and disciplined study of it would give an individual the advantage to organize the language (Bertuccelli, 1993) 3 .When it comes to acquiring the way, an individual should address the receiver "you-tú and usted" in Spanish language.Knowing about language traits related to these two pronouns will provide that person a better comprehension of this Spanish language grammar theme.
Socio-Cultural Input
Two of the peculiarities that distinguish the use of these two Spanish personal subject pronouns are the informal and the formal way, in which the two pronouns are treated in Spanish language communication.This has been the major consideration of English language native speakers when it comes to applying the use of tú and usted in Spanish language.A study of address patterns of Spanish personal subject pronouns Tú and Usted shows that L2 learners face difficulties in the interpretation of Spanish address forms (Gosselin, 2014) 4 .For many years, this Spanish language subject has been also the major concern of Spanish teachers in terms of teaching these pronouns to these kinds of learners.Nevertheless, knowing the ways with which these two pronouns should be used in Spanish language communication is not the most difficult task as many suggest.Generally, usted is used in reference to strangers, elders and social superiors while tú is used with friends, children and lower classes, although there is variation among individual speakers (Smith, 2013) 5 .From this cited statement, insight reveals the influence of socio-culture elements in the usage of these personal subject pronouns in Spanish language communication, which is nothing else than Spanish language socio-culture phenomenon.It is deemed that the subject personal pronoun tú is applicable for those treated as close relatives or friends.In other 2 San José, Miguel Ángel (2010), A Reference Grammar of Spanish.
4 Gosselin, Karen Marie, 2014.A study of address patterns: Spanish informal and formal forms Tú and Usted.Open Journal of Modern Linguistics words, it is a genuine expression of familiarity and trusts.On the other hand, the subject personal pronoun usted is simply the way to treat others with respect.It is believed that the highlighted discussion would be beneficial in supporting the perception about the real scenario and situation.
Nowadays, the use of pronoun tú has come to be more practical among Spanish native speakers than the pronoun usted.This phenomenon is being imitated not just for English learner's speakers, but for many others non-native Spanish speakers.Therefore, it might be one of the causes for which number of English language native speakers frequently make an error when applying the address forms for usted which involve the use of different grammar shapes in Spanish.
Syntax Input
Although Spanish is a much more heavily inflected language than English; when it comes to semantic the word order of the Spanish into sentences is similar to its English equivalent: Subject-Verb-Object (SVO).However, in the context of Spanish personal subject pronouns tú and usted, studying Spanish grammar can be a complex task, taking into account that these two pronouns are not required when the grammar associated forms has an impact on the way they are applied in the writing and speaking context of Spanish language communication.For instances, salutations; address forms; advertises, signpost: ¿Cómo estás?(tú)/¿Cómo está, señor?(usted) Translated as How are you, Sr.? ¿How is it going?= ¿Qué tal estás?(tú)/¿Qué tal está?(usted).¿Cómo te llamas?(tú) ¿Cómo se llama?(usted), Translated as What is your name?¿Do you have email?= ¿Tienes email?(tú)/¿Tiene email?(usted).Buy the boss perfume.= Compre el perfume boss.(tú)/Compra el perfume boss.(usted).Go straight= Siga recto (usted).
As can be seen from the above-examples; the grammar associated forms of the two pronouns are the elements that define the semantic structure and the indented meaning of the speaker.When many academics focus the use of tú and usted from the perspective of socio-culture (formal/informal) treatment the most, they somehow forget the significant of knowing and studying the grammar shapes of the Spanish personal subject pronouns tú and usted, which in fact should be the main focus to get mastering this Spanish language syntax topic.
Orthography Input
Monosyllables Words: Generally, the monosyllables words in Spanish are not written with accent (tilde or acento ortográfico) as it is known.However, this particular aspect of accentuation is used in many Spanish words to distinguish one from the others with similar spelling.Such are the cases of many words: el article and él personal pronoun, té noun and te pronoun, including the pronoun tú and tu possessive adjective etc.The use of accent/tilde also plays an important role in terms of syllable pronunciation in Spanish.For instance, interrogative sentences: ¿Cómo te llamas?In this example, the voice goes up in the beginning and decent in te llamas.
Grammar Patterns Input
Adjectives, Pronouns Adjacent, and Prepositions: The presence of tú and usted is a subject of interest, specifically when considering its actualization in Spanish grammar as personal pronouns.These two words take different persons, when ascertaining the subject personal pronouns in Spanish language.The pronoun tú takes the second person, and the pronoun usted takes the third person (together with the pronouns él and ella or he/she in English (Table 1).Both pronouns tú and usted are singular in Spanish language.English equivalent of these Spanish pronouns is the personal pronoun "you" (Table 2).But, it requires specific knowledge, when applying these two pronouns with adjectives, prepositions, and pronouns adjacent due to their connotation in Spanish language.
In Spanish, the prepositions "a", "de", "por", "para", "con", "sin", "en" never precede the pronoun tú.In the first four cases, the pronoun tú is replaced by the pronoun ti while the special construction of "contigo" is used in the last one.In contrast, all those prepositions can precede the pronoun usted.
Verbs in Present Indicative Tense: The present indicative or simple present in Spanish language has some similarities with its English counterpart when it has to agree with the verb.It goes the same way with "you".However, unlike English, in Spanish language; its equivalent tú and usted are far from one another.It means that these two Spanish pronouns have their own verbal pattern conjugation.It is no often a comprehensive point for English language native speakers, particularly when applying their correct verbal conjugations forms.
The main reason is not just due to the conjugation itself, but also because of duality that some verbs have in Spanish language as well.In particular, English language native speakers find it difficult to comprehend the verbs ser and estar, which are pronounced as to be in the English language.The verbal conjugation as well as the duality emerged in Spanish has always been one of the complex grammar tasks to overcome the difficulty of English language native speakers.In this regard, the appropriate examination of the spelling that distinguishes the verbal conjugations of tú and usted in relation to the verb cited can resolve particularly the verbal conjugation of the subject personal pronouns in Spanish.
Even though, all four conjugations mean "You are" in English.It is quite important to observe the spelling of these verbs in present indicative tense within Spanish language.The intention of explaining this point is because of the verb "estar" identified in present indicative that require specific attention to focus on the letter "s", making the difference between the verbal conjugation of tú and usted in Spanish.However, this observation might not deem to be complex particularly in practice.Following verb conjugated forms of many regular and irregular verbs in Spanish language are shown below: (You have.)Tú tienes./Ustedtiene.(You know.)Tú conoces./Ustedconoce.
When it comes to apply verbal conjugations of many regular and irregular verbs for tú and usted; one of the major aspects is to actualize precisely the letter "s".Such peculiar details can be seen in a number of regular and irregular verbs in present indicative tense in Spanish.It is important to know that tú and usted can be omitted in the content of sentence Do you want…?¿Quieres…?/¿Quiere…?, particularly in spoken Spanish.Unlike English language, the writing of interrogative sentences in Spanish requires the use of two question marks if they are direct interrogative sentences (¿…?); one in the beginning of the sentence and the other in the end.The interrogation marks are not required when the sentences are not direct sentences.The grammar structure for making questions in Spanish does not require auxiliary verbs like "do" as it does in English.
Verbs in Present Perfect Compound Tense: Quite similar to its English counterpart, present perfect compound tense in Spanish requires an auxiliary verb.Its grammar construction in Spanish is made up by using verb "haber" as auxiliary verb, in which the English equivalent is "to have".
In addition, the past participle of Spanish verbs must be used to complete its grammar structure.It is made up of three different classes of verbs that exist in Spanish language.The first group of Spanish verbs ends in "ar", the second ends in "er" and the third ends in "ir".The past participle for the Spanish verbs end-Open Journal of Modern Linguistics ing in "ar" is "ado", for "er" is "ido", and for "ir" is also "ido".
It is important to inquire and apply present perfect compound tense in Spanish language communication even though it is not used in many Latin America Spanish-speaking countries than in Spain.The past participle of Spanish verbs will remain unchangeable.In other words, once it is known, the only thing to change is the Spanish auxiliary verb "haber" according to the tense, in which it is used.
Verbs in Simple Present Progressive Tense: The present progressive tense in Spanish is made up by using auxiliary verb, which is similar to English counterpart.The verb in Spanish has two forms "ser" and "estar", and the only one that must be used as auxiliary verb to make up this tense in Spanish is "estar".
In addition, the ing of Spanish verbs must be used to complete its grammar structure.It is made up of three different classes of verbs that exist in Spanish language.By substituting the verbs ending "ar", "er", "ir" of the Spanish verbs in infinite forms and replacing them with the ending "ando", "iendo", "iendo".
However, the Spanish ing requires specific intention except for the infinite Spanish verbs ending in vowels, in which Spanish ing is "yendo".In the context of past participle of Spanish verbs, the Spanish ing will remain unchangeable.In other words, once it is known, the only thing to change is the Spanish auxiliary verb "estar" based on the tense in which it is used.
Pragmatic and Linguistic Input
"Pragmatics is a subfield of linguistics and semiotics that emphasize the ways, in which context contributes to meaning.Pragmatics encompasses speech act theory, conversational implicature, talk in interaction and other approaches to language behavior in philosophy, sociology, linguistics, and anthropology.Unlike semantics, pragmatics studies how the transmission of meaning depends on both structural and linguistic knowledge (e.g., grammar, lexicon, etc.) of the speaker and listener.In the context of utterance, any pre-existing knowledge, inferred intent of speaker, and other factors are involved.In this respect, pragmatics explains how language users are able to overcome ambiguity, since meaning relies on the manner, place, time etc. of an utterance.The ability to understand Open Journal of Modern Linguistics another speaker's intended meaning is called pragmatic" (García & Otheguy, 1977) 6 .Pragmatic will give a clear insight about those linguistic terminologies that require visible sings, sounds, environment etc. to apply the particular language, for instance, the questions, Are you tired?Are you mad?, are not particularly asked if the signs are already suggestive.By considering the significance and conjunction of the two in "applied syntax"; an example could be the translation of those English questions to Spanish.
As it can be observed from those examples, by right it will require more knowledge of Spanish syntax to comprehend those addressed forms and many others for tú and usted than the impact that pragmatic could has on them.Thus, it is necessary to study carefully the grammar associated form for tú and usted.
Objective of the Study
The core intention of this study has been to provide a guideline through which English language native speakers can get an insight about language traits associated with two pronouns and their significant usage in the speaking and writing context of Spanish language communication.Based on the fact that non-native speakers faced a significant difficulty regarding the usage of these Spanish personal subject pronouns; the study has reviewed inductive teaching and learning methods as a suitable medium to disseminate this knowledge to the Spanish learners.The inductive approach has been used to analyze the level of Spanish language proficiency in these learners regarding the use of these pronouns; therefore, it is recommendable as teaching approach in the development of language skills among non-native speakers according to the results of its application.
Methodology
Rationale for selected methodology The mindset of English native language speakers is difficult to understand about Spanish grammar as the nature of grammatical functions is complex.The reason for such is mainly pointing to the influence of native language in the subconscious of these learners, which is so powerful not to be influenced, especially when it comes to adult students.various contexts.There are many teaching and learning methodologies that address this arena; such as deductive learning.However, it has been found to be most effective to use inductive teaching and learning methods to aid students in the development of their language skills.Such methods are inclusive of inquiry learning, project-based learning, discovery learning, case based teaching, just-in-time teaching and problem-based learning, and levy a greater responsibility on the students to acquire knowledge.Rather than initiating the learning process by discussing general language principles and then moving on to their practical applications, such inductive teaching begins with specifics in the form of experimental data for interpretation, case studies for analysis or a real-world problem that needs a solution.Through the examination of this specific data, students understand the significance of theoretical knowledge that they need to analyze this data accordingly.This is in stark contrast to the traditional teaching methodology that utilized lecture-based deductive learning.Therefore, this study has conducted an exploration of inductive teaching and learning approaches to enable students and to accomplish their Spanish language development in relation to the effective usage of tú and usted.A set of exercises will be provided to these students to help ascertain the level of their language proficiency regarding the applications of these pronouns.
Teaching and Learning Guidance
Firstly, it is important to make it clear for the English native language speakers that learning a new language will require a profound interest on their part, which is the key to accomplishing the language tasks given successfully.Letting them know that in terms of studying the grammar of Spanish language, it is necessary to remember that the Spanish language has its own grammar patterns.
The students will therefore need to structure their learning approach in accordance with the program requirements.We thus initiate a set by step analysis of this discussion.
Socio-Cultural Input
A clear view about the positions is provided that tú and usted take in relation to verb conjugations before continuing to the next task.A note pertaining to the usage (formal and informal) of these pronouns in Spanish language is to be provided, which can be taken from this research paper.The students are asked to Open Journal of Modern Linguistics focus on it for future roleplay dialogues (informal and a formal).It is necessary to remind the significant aspect in learning the grammar patterns for usted and that can be used as well to make statements about él/ella (he/she) in Spanish language (Figure 1).
The study has used the examples of Spanish verbs in present indicative tense to create three kinds of sentences.Besides the conjugation of the verb to be "ser" in present indicative in Spanish, the letter "s" makes the difference between the conjugated forms of tú and usted in this tense in a gran number of regular and irregular verbs in Spanish.
Step 3: Tú and Usted-Verbs in Present Perfect Compound Tense.Additionally, the study has used the examples of Spanish verbs in present perfect compound tense to create three kinds of sentences.The letter "s" makes the difference between the conjugated forms of tú and usted in relation to the verb to have "haber", as well as about the use of the past participle of Spanish verbs "ado", "ido", "ido" to make this verb tense in Spanish.
Step 4: Verbs in Simple Present Progressive Tense.The study has used the examples of Spanish verbs in present progressive tense to create three kinds of sentences.The verb "estar" can be used as auxiliary verb to make the progressive tense in Spanish, and the use of Spanish ing "ando", "iendo", "iendo", "yendo".
Exercise: Do the verb conjugations in the tenses shown in this paper research
Results and Discussion
This study made use of cognitive, meta-cognitive and affective components of learning to review the significance of teaching and learning approaches for Spanish language.It was discussed in studies that learning is comprised of these three components.These studies discussed that cognitive learning activities help students to process and critically analyze the provided information and contribute in the strengthening of their knowledge pertaining to that arena.Affective learning approaches are used by students to deal with the emotional responses that follow the learning process lastly, the meta-cognitive component of learning is involved in the exertion of control and responsibility over one's cognitive and affective processes in order to understand the information provided (Prince & Felder, 2006) 8 .It may be seen that inductive learning and teaching approaches are an effective amalgamation of these three components of learning.Moreover, their utilization in disseminating information regarding Spanish pronoun usage would aid in the development of linguistic capabilities in Spanish language learners.This study conducted close observations of personal pronouns tú and usted in 8 Prince, M. J., & Felder, R. M. Inductive teaching and learning methods: Definitions, comparisons, and research bases.Journal of engineering education, ( 2006) 95(2), 123-138.Open Journal of Modern Linguistics Spanish language communication.These observations were carrying out at Multimedia University (MMU), Malaysia among Spanish language students.It can be seen that English learner's speakers are prone to committing mistakes in correctly applying the grammar patterns of tú and usted in Spanish language.There are many factors that culminate in the restriction of these students to adequately learn and apply these personal pronouns in Spanish.These are inclusive of direct and inappropriate translations, insufficient knowledge about the proper usage of tú and usted-grammar patterns and lack of learning materials for Spanish grammar.The presence of null and overt pronouns and their own grammar patterns further complicates the learning process, because there is a necessity to display or omit these pronouns as per the contextual requirement.The presence of this null-pronoun variation has been noted in Mandarin Chinese as well (Jia & Bayley, 2002) 9 .Additional factors include the influence of negative external sources in terms of learning choices and the design of specific teaching.Lack of proficiency may be attributed to ineffective learning methods that are employed by these students in the form of rote learning and memorization tactics.Such methods are extremely ineffective in helping students to gain a comprehensive understanding of how language is to be applied according to different contexts (Flores-Ferrán, 2004) 10 .In this case, the students were not able to correctly apply the pronouns in the appropriate situations.It suggests that a transformation is needed in the learning and teaching approaches that are currently employed by students and teachers respectively.Inductive teaching and learning approaches were discussed by studies to be an effective approach in the linguistic application of languages.
Conclusion
This study attempted to conduct an investigation pertaining to the efficacy of teaching and learning practices related to Spanish grammar with non-native speakers, particularly English native speakers.The grammar components selected to conduct and demonstrate the veracity of this research article are as follow: Subject personal pronouns Tú and Usted.This study pertained to the appropriate use of these pronouns in the Spanish language and contained an explicit explanation about the formal and informal usage of these Spanish personal pronouns.Additionally, this study intended to emphasize other linguistic elements associated with the usage of tú and usted and pointed out their significant role.In conclusion, the study has explained the influence of socio-cultural, orthography, pragmatic and linguistic and grammatical aspects that characterized the use of these Spanish personal subject pronouns in the speaking and writing context of Spanish language communication.This study also highlights the inductive learning and teaching approaches in enabling Spanish learners to devel-
Table 1 .
Examples of possessive pronouns and adjectives.
Table 2 .
Examples of direct, indirect and reflexive pronouns.
se (you) Open Journal of Modern Linguistics The Spanish grammar topics cited ranges Open Journal of Modern Linguistics from Spanish level A1-A2 according to what is prescribed by the Common European Framework of Reference for Language Learning, Teaching, Assignment (CEFR) (Consejo de Europa, 2001) 7 .Marco Común Europeo de Referencia para las Lenguas: aprendizaje, enseñanza, evaluación.In order to develop an avid interest among learners of Spanish language, it is necessary to enable students to understand the relevance of what they are learning and help them to apply it to | 5,409.6 | 2019-01-31T00:00:00.000 | [
"Linguistics"
] |
On the Generation of Plasma Jets in the Kilojoule Plasma Focus Device
Laser–optic methods were used to study the properties of plasma jets generated in the KJ Plasma Focus device. Measurements of the plasma jet velocity were conducted immediately after its appearance. During the first 10 ns, the average velocity is about 5 × 107 cm/s, which corresponds to energy of 18 keV for the ions of nitrogen, which was the working gas of the PF setup. The jet density and velocity decrease manifold over distance of 2–3 cm from its generation point. The experiments confirm that the main reason of jet generation is the necking of the pinch. It was found that after the pinch decay, a new plasma column appears, which propagates in the axial direction.
INTRODUCTION
Plasma focus (PF) is one of the first plasma electric discharge devices in which the ideas of controlled fusion were verified starting in the late 1950s [1]. At the same time as Filippov reported a record quantity of neutrons in these discharges, plasma jets propagating from anode to cathode were discovered [2]. Also at the same time, Mather discovered generation of neutrons in discharges of powerful plasma injectors, which are, in essence, plasma jet generators, during their operating on deuterium [3]. Despite their long history, the mechanisms of jet generation in PF remain unclear, despite the wide spectrum of their applications [4][5][6][7]. The theories of the origin of the jets in PF were dominated by Filippov's hypothesis [2,8,9] of the so-called cumulative mechanism of their generation. The main source of plasma jet generation was considered to be the conical (noncylindrical) shape of the compressing plasma sheath. However, lately, this hypothesis was subjected to doubts. They were first published in [10], where it was noted that "flows of matter are present (in earlier works, this effect was explained by cumulation, which is not entirely correct), which are not connected to the dynamics of the current-carrying sheath along the axis." Particular jet generation mechanisms were not considered in [10], and it was assumed that it was "probable that their nature is similar to astrophysical jets generated by stellar objects." Axial flows of matter (in case of use working gas neon) with velocity 1.3 × 10 7 cm/s were recorded, and the authors were certain that their real maximum velocity was higher still at 2 × 10 7 cm/s. In experiments, and installation with energy content of several hundreds kilojoules and flat electrode geometry was used, and measurements were carried out using rapid image tubes.
In our work [11] that was carried out at the PF device with energy content of 4 kJ, we used the laser probing method and did not record the generation of the plasma jets either during the convergence of the conical current sheath, or during its compression, or at the pinching stage. The jet appeared later still, at the stage of pinch destruction. This scenario of jet creation agrees with the model of adiabatic compression of the plasma column [12].
Until now, in our experiments, the velocity of the jets was measured at some distance from their generation point, in the working gas, where the jet was already noticeably decelerated [11,13]. The energy of ions in the jet was recorded at the level of 1 keV for nitrogen ions, but it was obvious that the initial jet velocity would have been substantially higher, if it were recorded closer to the moment of its generation. In our previous experiments, we used the one-frame variant of laser probing of the discharge. The jet velocity was measured from the difference of positions of its front at known moments in time relative to the specific feature in different pulses. This method was justified given the relatively high repeatability (±10 ns) of the discharge dynamics. Closer to the specific feature, the error of determining the velocity approached 100%. Therefore, we chose the two-frame variant of interferometry in a in the same PF discharge pulse. For this, the probing laser ray was separated in two, one of PLASMA DYNAMICS which was delayed relative to the other by the controlled difference in optical paths.
Another objective of this work was to trace the discharge evolution after the decay of the pinch and the appearance of the specific feature. Indeed, in our work [11] we determined that at this stage, a new plasma column is created, which rapidly grows upward and overtakes the shock wave. The effect of the new pinch on a sample placed at the discharge axis still has not been studied. Below, we present new results of the study of this plasma formation.
Note regarding the terminology: in our experiments, it would be more correct to call the plasma jet a plasma bunch due to its longitudinal and transverse dimensions being comparable, but the term "plasma jet," which was introduced by Filippov [2] is more commonly used in literature. We will use both terms. As is common, we will call the sharp jump on the derivative of the discharge current its specific feature, the skinned plasma current sheath of the discharge is referred to simply as the current sheath, and the neck in the plasma column that appears due to the development of the Rayleigh-Taylor instability we will call the neck.
DESCRIPTION OF EXPERIMENT
Experiments were carried out at the "Tulpan" PF-4 installation (Lebedev Physical Institute of the Russian Academy of Sciences) that is an electric discharge device of the plasma focus type with half-spherical electrode geometry. The diameter of the copper anode was of 30 mm and the diameter of the copper cathode was of 50 mm. The total capacity of the capacitor bank was C = 48 μF, the working voltage of 12 kV was not changed during all the pulses of the installation, the energy of the capacitive storage was of 3.5 kJ, the characteristic current raise time was of 3 μs, and the maximum discharge current at this voltage was of 0.3 MA. The working gas was nitrogen at a pressure of about 1 Torr.
The plasma was probed by the radiation of the second harmonic of a Nd:YaG laser with energy of about 100 mJ, pulse duration of 5 ns, and wavelength of 0.53 μm. The laser pulse was divided in two, one of which was delayed relative to the other by mirrors for intervals of 5, 18, and 46 ns of our choice. The interval between the passage of the first ray through plasma and the minimum of the specific feature on the current derivative was determined from the data of the photodiode and the magnetic probe using a Tektronix TDS 3054C oscilloscope with transmission band of 500 MHz.
The plasma focus device was built into one of the arms of a Mach-Zehnder interferometer. The interferograms were recorded by a Canon ЕОS 650D digital camera (in detail, see [10]). To separate the frames spatially on the CCD matrix of the camera, we installed quartz wedges in the focal plane of the Kaleinar-3B 2.8/150 long-focus lens (Fig. 1).
Jet Generation
Laser-optic measurements were carried out during the first and second half-periods of the discharge starting from the moment when the current sheath reached the anode's end. In the first half-period, it was found that this moment is ahead of the minimum of the specific feature of the current by 100-150 ns (point 1 in Fig. 2). This point is preceded by a slow linear decrease of the current derivative. Over interval 1-2, the rate of current decrease increases 20 times, which is explained by the sharp increase in the inductance of the conical part of the current sheath (Fig. 3). This shape of the sheath is observed until its closing near moment 2, when it becomes conical. During the entire convergence phase 1-2, no axial plasma ejections are observed. The sharp (additional 10-20 times) increase of the decay rate of the current derivative after moment 2 is accompanied by the radial deceleration of the plasma column and by it taking a cylindrical shape (Fig. 4). At this stage (2-3) as well, no axial flows of plasma were observed. Plasma formations that propagate in the axial direction were recorded after the decay of the pinch and after the minimum on the current derivative (Fig. 5). Current bunches with initial size about one millimeter and density above 10 19 cm -3 were found that traveled upward along the axis ( Fig. 1) from anode at a velocity higher than 10 7 cm/s. These bunches gave rise to a bell-shaped shock wave that propagated in the working gas above the current sheath similar to [14][15][16][17].
With time, the bunches expanded and their density and velocity decreased (Fig. 6). The jet velocity was calculated starting from the moment when the interference image was recorded relative to the time of the specific feature: -specific feature on the current derivative inside the time interval between frames. The first frame indicated the position of necking. The distance traveled by the jet was calculated from this position to the leading edge of the jet in the second frame. The time of the jet travelling this distance was calculated from the minimum of the specific feature; -specific feature on the current derivative before the first frame. The jet velocity was determined from the difference of positions of its leading and trailing edges in both frames.
The velocities determined by this method were tied to the middle of the mentioned time interval in the figures, i.e., these were the average values of velocities in the given time interval.
When calculating the velocity in the first case, we roughly estimated that the moment of current disruption and the moment of jet generation coincided with the minimum of the current derivative. This assumption is valid over relatively long time intervals, about tens of nanoseconds and longer. The real situation is, indeed, more complicated, which was described in detail in [18]. It is seen that the jet is born somewhat earlier than the disruption of the plasma column. The best agreement of both methods for calculating the jet velocity occurs under the assumption that the jet generation get ahead of the plasma column disruption by 2 ns.
The jet velocity measured by this method was about 5 × 10 7 cm/s during the first 10 ns after its appearance, which corresponds to the kinetic energy of nitrogen ions equal to 18 keV. For materials science studies carried out at our installation [5,6], it is important to know the energy flux density carried by the plasma jet in whose path studied samples are placed at a distance of 3-8 cm from the anode. Let us estimate this density at the upper edge of the diagnostic port at the maximum distance of 3 cm that is still available for observation. In the graphs shown in Fig. 6, this distance corresponds to time of 40-50 ns. In Fig. 5, the thickness of the current sheath is about 1 mm, the ion density in the sheath for the 3-4 degree of ionization (plasma temperature is comparable to the directed kinetic energy) is 10 17 cm -3 , and each nitrogen ion at the speed of 10 7 cm/s (Fig. 6) has kinetic energy about 1 keV ~ 2 × 10 -16 J. A cube of such plasma with a millimeter-long side will have the energy about 0.02 J, and the corresponding energy flow intensity will be 2 × 10 8 W/cm 2 .
Note that in experiments in argon as the working gas, the bunch was much denser and more compact, its initial density exceeding 10 19 cm -3 [11]. In earlier experiments in the heavier gas xenon [13], it was seen that the jet was denser still and its leading edge was sharper.
Axial Growth of the Plasma Column
This stage of the discharge is well illustrated by interferograms together with the computer model whose basics are described in [19]. 200-300 ns after current disruption and pinch decay, the remaining plasma is once again compressed, and a new plasma column is created at the axis (Fig. 7). This process is not rigidly tied to the specific feature and can relatively widely (>100 ns) vary from pulse to pulse. The base of the column consists of cold plasma from the ions and atoms of the anode material (copper). Above the base is the plasma from the working gas ions. The top of the column penetrates into the cavity created by the shock wave.
The frames were taken in different pulses in the described time range. In some pulses, coupling of the column top with the leading edge of the shock wave is observed (right frame, Fig. 7) that is accompanied by new disruptions of the plasma column. The plasma column overtakes the shock wave because the latter is decelerated in the working gas, while the current sheath is pushed upward by the magnetic field of the discharge current. After the closing of the plasma column with the shock wave, a new current-carrying plasma formation is created, whose shape reminds a fountain. Below, we will call it a gushing pinch.
After ~300th ns, the shock wave and the plasma column top leave the observation field (Fig. 8, time dependence of the discharge shown in Fig. 9). Still, depending on the necking of the plasma column (shown by the arrow in Fig. 8), it decays and is reformed. The electron density of the plasma in the neck (Fig. 8, right frame) is about 3 ×10 19 cm -3 , its diameter is 0.3 mm, and the radial compression velocity is not high at 3 × 10 6 cm/s. The base of the plasma column near the anode is two-layered, where the inner layer is composed of the ions of the anode material (copper) and the outer layer consists of the ions of the working gas. The copper ions are probably the result of the interaction of the electron beam and the plasma jet.
Short Overview of the Studies of Plasma Dynamics
During the Second Half-Period During the second half-period, when the polarity of the internal electrode is negative, the specific fea- tures are observed rarely and they are never as sharp as in the first half-period (Fig. 12). Accordingly, we do not observe necks as thin as in the first half-period. This is probably connected to the changing composition of the working gas and, possibly, to the smaller current amplitude compared to the first half-period, since the current does not compress the neck of the pinch that generates the jet enough to disrupt it [11]. The characteristic dome of the shock wave was not found in any of the pulses. At the axis, plasma formations are seen that move upward together with the reverse current sheath but at an appreciably lower velocity than the bunches in the first half-period. For example, in Fig. 10, the velocity of such a fragment is 4 × 10 6 cm/s and its density is ∼4 × 10 18 cm -3 .
After the column disruption, the same as in the first half-period, a new column is created (Fig. 11, time dependence of the discharge in Fig. 12) with a few differences: the vapor and plasma from the anode material are not observed in the base of the column.
This can be seen in the sharply defined shape of the anode (cf. Fig. 8 taken at similar time during the first half-period). Therefore, the plasma column is onelayered and it consists only of the ions of the working gas. The plasma density in the neck marked by the arrow is about 2 × 10 19 cm -3 , which is close to the value measured in the first half-period in this region. The current density at this moment is about half the maximum current, ~150 kA.
DISCUSSION OF EXPERIMENTAL RESULTS
Note that the phase of the sharpening of the leading edge of the specific feature (the 2-3 region in Fig. 2) coincides with the phase of the radial deceleration of the current sheath. This means that during the deceleration and compression of the current sheath, its resistance, both active and inductive, increases. Even more obviously, this fact is described in [18], where the compression phase of the current sheath occurs at the same time as the minimum of the specific feature of the current. In our experiments, the specific feature is at the end of compression and start of pinch decay (Figs. 4, 5).
These experiments confirmed the conclusion of [11]: the axial plasma jets are already present during the cumulation stage of the current sheath. Let us explain this fact. We will separate this stage into the contraction phase of the current sheath and the compression phase of the sheath.
Contraction phase. After the current sheath reaches anode's end, it acquires supersonic speed in the medium of weakly ionized working gas, which is either collected by it or passes through. The gas is compressible, and its thermal velocity is much lower than the velocity of the approaching sheath, so it is not reflected in the axial direction from the inclined surface of the conical current sheath. Therefore, there are no substantial motions of matter and no cumulation.
As is well said in [10]: "cumulation in its usual sense is possible for non-compressible matter, which plasma is not." Compression phase. Let us estimate the main parameters of the plasma column near the moment of the specific feature in the range -38…0 ns using the information shown in Figs. 3, 4 and the following general considerations: -the discharge current is 300 kA; -the radial velocity of current sheath contraction decreases from 10 7 cm/s to zero; -the radius of the plasma column is about 1 mm; -the electron density determined from interferometry is about 10 19 cm -3 ; -the temperature of the column calculated by Bennet's relationship [1] is 300 eV; -the average ion charge is Z = 3; -the skin depth for classical conductivity [1] is of the order of 1 mm.
In this context, it is important that the skin depth is the same as the radius of the plasma column. The eigen magnetic field of the discharge inhibits the axial motion of the plasma that is frozen into it. Let us make a numerical estimate of the conditions under which the plasma of the pinch, through whose entire cross section a uniform current is flowing, is frozen into the magnetic field. The plasma is magnetized when its electrons make a complete rotation in the magnetic field between two collisions with ions [1], in other words, when the electron cyclotron frequency ω ce exceeds the electron-ion collision frequency ν ei = 1/τ ei , i.e., ω ce τ ei > 1. By substituting τ ei = 5 × 10 4 T 3/2 /(n e Z 2 ), ω ce = eB/mc, and the magnetic field in the axial cross section B = 0.2I/R [1], we get ω τ × 11 3/2 2 ce ei ẽ 2 10 /( ),
T I n RZ
where R is the pinch radius in cm; n e is the electron density in cm -3 , I is the discharge current in A, T is the plasma temperature in eV, m is electron mass, e is electron charge, and c is the speed of light. At the typical parameters for the compression phase ( Fig. 4) (R = 0.1 cm, I = 300 kA, Т = 100 eV, n = 10 19 cm -3 , and Z = 3), ω ce τ ei = 10. During uniform current flow, the magnetic field is known to increase linearly from the axis. Therefore, only the plasma in a small region near the axis with size less than R/10 and, consequently, a volume less than 1/100 of the pinch volume remains unmagnetized (i.e., with ω ce τ ei < 1), and crude estimates allow for plasma being magnetized in the entire volume of the plasma column during the compression phase. Thus, one can assume that the eigen magnetic field of the current flowing through the pinch will inhibit the propagation of axial plasma flows.
Consequently, axial jets are not observed during plasma sheath contraction for three possible reasons: the compressibility of the working gas, the supersonic motion of the sheath and the plasma being frozen into the magnetic field.
It is only close to the moment of current disruption that the reconnection of magnetic field lines helps with the creation of magneto-plasma formations [14] that can propagate in the axial direction.
The observed dynamics of plasma jet formation is close to the model of adiabatic compression of the plasma column that is described by Vikhrev, e.g., in [12]. Here, the process of plasma flowing out of the necks is the key mechanism of the compression and heating of the plasma column and the kinetic energy of the jet ions is comparable with the plasma temperature in the column, ~10 keV. In our experiments, we recorded the velocity of plasma bunches at the level of 5 × 10 7 cm/s, which corresponds to kinetic energy of 18 keV.
After the first observed current disruption and generation of the shock wave, a new component of the axial plasma flow was observed. This is a rapidly growing plasma column of the discharge. Until now, it was assumed that the samples are only affected by the shock wave and the plasma jet [2,10,15]. The velocity of axial growth of the plasma column is in the range between the velocity of the shock wave, ∼10 7 cm/s, and the axial velocity of the current sheath, ∼5 × 10 6 cm/s. The above-described measurements showed the presence of necks in the growing plasma column, where the plasma density was about 10 19 cm -3 . If one assumes that the entire current (300 kA) or at least its major part flows through this column, then the temperature in the neck should be of the order of 100 eV, the magnetic pressure 10 4 -10 5 atm and a fraction of its energy can be deposited in the sample. The energy transfer mechanism has not yet been studied. Similar processes of column growth are also observed in the second half-period of the discharge.
The propagation of the gushing pinch and its necking lead to its separation into bunches with frozen in magnetic field. Similar plasma formations were observed in [14] at the powerful Mather focus. This mechanism probably also is the basis for the formation of glowing bunches observed at substantial distances in the megajoule Filippov Plasma focus [16,17].
CONCLUSIONS
The initial velocity of the plasma jet generated in the kilojoule PF installation was measured. In the first 10 ns after its formation, the average velocity is about 5 × 10 7 cm/s, which corresponds to kinetic energy about 18 keV for the nitrogen ions. The jet dynamics agrees with the model of adiabatic heating of the necks in plasma focus discharges [12] while the order of magnitude of the values agrees with experimental results.
Apparently, the studied samples placed in the materials science experiments [4][5][6] are not affected either by the shock wave that accompanies the plasma jet or the jet itself that rapidly loses velocity and density, but by the gushing pinch. Its dynamics is not yet well-studied.
CONFLICT OF INTEREST
The authors declare no conflicts of interest.
OPEN ACCESS
This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/. | 5,632.2 | 2022-04-01T00:00:00.000 | [
"Physics",
"Engineering"
] |
Mathematical Modeling of Drain Current Estimation in a CSDG MOSFET, Based on La2O3 Oxide Layer with Fabrication—A Nanomaterial Approach
In this work, three-dimensional modeling of the surface potential along the cylindrical surrounding double-gate (CSDG) MOSFET is proposed. The derived surface potential is used to predict the values of electron mobility along the length of the device, thereby deriving the drain current equation at the end of the device. The expressions are used for modeling the symmetric doped and undoped channel CSDG MOSFET device. This model uses Pao-Sah’s double integral to derive the current equation for the concentric cylindrical structure of the CSDG MOSFET. The three-dimensional surface potential estimation is performed analytically for doped and undoped device parameters. The maximum oxidant concentration of the oxide layer is observed to be 4.37 × 1016 cm−3 of the thickness of 0.82 nm for (100) and 3.90 × 1016 cm−3 of the thickness of 0.96 nm for (111) for dry oxidation, and 2.56 × 1019 cm−3 of thickness 0.33 nm for (100) and 2.11 × 1019 cm−3 of thickness 0.49 nm for (111) for wet oxidation environment conditions. Being an extensive analytical approach, the drain current serves the purpose of electron concentration explicitly inside the concentric cylindrical structures. The behavior of the device is analyzed for various threshold conditions of the gate voltage and other parameters.
Introduction
In recent years, the double-gate (DG) MOSFET design has been prominent in planar design structures. However, the limitations of the double-gate MOSFET have put an end to further advances in the regime [1]. New device structures are needed to overcome the conventional structures' issues and enhance performance. Some new devices concentrate more on solving performance issues oriented with the short channel effects (SCEs) [2,3]. Most of the new devices are silicon-on-insulator (SOI) based on the packaging density and the suppressing capacity of the SCEs. Many multiple gate structures have been proposed in recent times, such as double-gate, tri-gate FET, gate-all-around FET, cylindrical gate-allaround FET, and the CSDG MOSFET [4][5][6]. Device modeling is the fundamental step of designing a device since it has the capacity to better understand the characteristics of the FET under various theoretical and boundary conditions. The multi-gate FET has been a promising feature of new-age devices to enhance performance and improve immunity to SCEs. Significant works have been undertaken by various researchers in the field of the double-gate with symmetrical and asymmetrical geometry [7][8][9][10]. Among these, symmetric geometrical structures are modeled in this work and analyzed for the improvement of their characteristics.
In the existing DG FET models [11], approximations with numerical iterations are used to derive the results from the mathematical models. The mobility model has been developed for all operation regions of a transistor. In all modeling, the transistor with an undoped structure has been modeled, with doping concentration added to reduce the complexity in
Extensive Modeling of the CSDG MOSFET for Fabrication Perspective
The CSDG MOSFET has evolved from the basic double-gate MOSFET by taking the rotational axis outside the device, as shown in Figure 1. This resultant three-dimensional device will be coordinated in cylindrical dimensions [19,20]. The device follows the concentric cylindrical geometry with symmetry along the length of the device [21][22][23]. The outer gate layer is represented by the blue color. The next layer adjacent to the gate is a yellow oxide layer, followed by a spacer in red. The bulk is represented as a pink layer where the dopant concentration is optimum. The next layer to the bulk is another small layer of spacer and oxide that leads to the second gate at the center. The inner gate is in pale blue. The inner gate has a small core of 2D electron gas (2DEG) which reduces the skin effect and maintains electric potential to flow in the inner gate. The 2DEG layer provides enough flow path to the charge carriers. and excites the electrons to the Fermi energy level [28]. Secondly, the layers with highe threshold voltage are turned on, and the energy excitation is modeled. The position alon the length of the channel where the potential is low is called a virtual cathode. It is presen in the channel to create mobility of electrons. The surface potential is calculated from th point that extends inside the core of the FET [30][31][32][33][34]. The modeling was performed analytically, and the simulation was coordinated an performed using an electronic simulator. The previous version of the simulation tool ut lized higher system capacity and had limitations to developing the characteristics. How ever, the newer version has the potential to simulate the device with added features t simulate various characteristics of the device with a considerable amount of performanc enhancement. Figure 2 shows the enhancement in the performance of the two differen versions of the simulation tool. In lower current characteristics, the newer version show a bigger difference than the older version. The proposed structure of the CSDG MOSFET is a cylindrical concentric solid devic with various layers which extends on all the three axes. The capacitive modeling and i estimation were carried out by Gowthaman et. al. in [6]. The three-dimensional surfac potential of the cylindrical structure, drain current flows in the CSDG and the electro The proposed structure modeling involves the following assumptions: Silicon body floats; hence, the electrons possess energies in Fermi energy levels, and the Fermi energy level of the source terminal is considered for all mathematical modeling [24]. The threshold voltage of the proposed device is derived analytically to simplify the drain current expression [25][26][27][28][29]. Firstly, the FET switches the layers on with lower threshold voltages and excites the electrons to the Fermi energy level [28]. Secondly, the layers with higher threshold voltage are turned on, and the energy excitation is modeled. The position along the length of the channel where the potential is low is called a virtual cathode. It is present in the channel to create mobility of electrons. The surface potential is calculated from this point that extends inside the core of the FET [30][31][32][33][34].
The modeling was performed analytically, and the simulation was coordinated and performed using an electronic simulator. The previous version of the simulation tool utilized higher system capacity and had limitations to developing the characteristics. However, the newer version has the potential to simulate the device with added features to simulate various characteristics of the device with a considerable amount of performance enhancement. Figure 2 shows the enhancement in the performance of the two different versions of the simulation tool. In lower current characteristics, the newer version shows a bigger difference than the older version.
The proposed structure modeling involves the following assumptions: Sili floats; hence, the electrons possess energies in Fermi energy levels, and the Ferm level of the source terminal is considered for all mathematical modeling [24]. Th old voltage of the proposed device is derived analytically to simplify the drai expression [25][26][27][28][29]. Firstly, the FET switches the layers on with lower threshold and excites the electrons to the Fermi energy level [28]. Secondly, the layers wi threshold voltage are turned on, and the energy excitation is modeled. The posit the length of the channel where the potential is low is called a virtual cathode. It in the channel to create mobility of electrons. The surface potential is calculated point that extends inside the core of the FET [30][31][32][33][34]. The modeling was performed analytically, and the simulation was coordin performed using an electronic simulator. The previous version of the simulation lized higher system capacity and had limitations to developing the characterist ever, the newer version has the potential to simulate the device with added fe simulate various characteristics of the device with a considerable amount of per enhancement. Figure 2 shows the enhancement in the performance of the two versions of the simulation tool. In lower current characteristics, the newer versi a bigger difference than the older version. The proposed structure of the CSDG MOSFET is a cylindrical concentric so with various layers which extends on all the three axes. The capacitive modelin estimation were carried out by Gowthaman et. al. in [6]. The three-dimension potential of the cylindrical structure, drain current flows in the CSDG and the The proposed structure of the CSDG MOSFET is a cylindrical concentric solid device with various layers which extends on all the three axes. The capacitive modeling and its estimation were carried out by Gowthaman et al. in [6]. The three-dimensional surface potential of the cylindrical structure, drain current flows in the CSDG and the electron mobility model are discussed analytically. Table A1 shows the notations of the symbols used in this work.
Three-Dimensional Surface Potential Modeling
The 3D Poisson's distribution for the three-dimensional CSDG MOSFET is given as: where the channel potential, ϕ(x,y,z) is given by The potential used for band bending ψ(x) varies in the x-direction and the electrostatic potential V(y) fluctuates along the y-direction. Since the proposed structure extends in the z-direction, which is a circular disc, the net potential in the z-direction constitutes zero and is negligible. Moreover, ψ(z) = 0, V(0) = 0, and V(Leff) = V DS . The updated electrostatic potential across the y-direction along the channel length L is given as: Utilizing (1) and (3) in (2), the equation of the channel potential subjected to the differential is given as: The electrostatic potential along the y-direction is reduced to V, and (4) can be given as: The thin concentric layers of the CSDG MOSFET have an approximation for the bending potential, ψ = ψ0 and dψ/dx = 0. Then, (5) can be rewritten as: After integrating (5) twice with applying boundary conditions, the expression of the band bending potential can be given as: By way of can result as: In the undoped CSDG MOSFET device, the mathematically derived surface potential by the independent arbitrary potential technique is given as: where V arbitrary = 0 at the source terminal, and V arbitrary = V DS − V bi is the drain terminal.
The junction between the drain and the channel influences the depleted charge carriers, which is the reason for the presence of potential at the drain terminal. The threshold voltage, V T , is given by, For a doped channel, the CSDG MOSFET behaves as per the 3D Poisson's expression given in (1), but it has an additional term for the dopant concentration. The dopant concentration is directly proportional to the surface potential. Poisson's expression for the doped device is given as: The surface potential is derived from (8) and is substituted in (11), giving: Integrating (12) two times (double integration) with optimum boundary conditions suitable for the CSDG MOSFET, the band bending potential can be rewritten as: The surface potential is derived from (13) by substituting the boundary condition as, The surface potential of the CSDG MOSFET with a doped channel has been derived in (13b), and it is a function of dopant concentration Na and potential at the center of the core of the CSDG MOSFET ψ0.
Mobility Modeling in the Cylindrical Structure
The effective electron mobility model for an undoped CSDG MOSFET which extends in 3D space is given as, This is the basic equation for deriving electron mobility in the CSDG MOSFET paradigm. Initially, the mobility model for the devices that have > 10 nm channel length has been discussed, and by adding suitable boundary conditions, two inferences have been made. The mobility of electrons in the silicon layer µ e − si is 1500 cm 2 V −1 s −1 . The effective mobility of electrons (µ eff ) is given as: The electron mobility by considering the device operates just above the flat band voltage is given as: If the device operates in the sub-threshold region, (15b) becomes :
For weak inversion region
:
For moderate inversion regions
: For channel thickness <= 10 nm, the flat band voltage is less than the V GS , and it is displayed as: V GS <= flat band voltage, (17) becomes: These are the mobility variations present in the CSDG MOSFET with various conditions of voltage across gate and source terminals. The effective mobility is shown in (18) and is used for further derivation of the drain current.
Drain Current Modeling for the Cylindrical Structure
The drain current estimation follows Pao-Sah's distribution theory which involves both drift and diffusion charge carriers along the length of the device [35][36][37][38]. The independent mobility of an electron has been derived from: The mobility modeling is used in estimating the drain current in the cylindrical structure of the CSDG MOSFET. The effective mobility in (18) is applied to the threedimensional space with independent position nature to obtain: gives the elementary current equation of the transistor in several working regions [39,40]. The capacitance estimation was carried out by the authors in [6,8,40], and applied to (19b), it gives: However, (20) in (19) yields the current equation for the linear region of the transistor as: The fixed charge distribution is not present in the silicon-based devices [41]; hence, it is given as: where H S is the surface electrical field [42], and two indicates the device has symmetrical geometry. Substituting (22) in (19a) gives: where η is the intrinsic carrier concentration, H is the electric field at the drain terminal, and κ is the coupling coefficient [43]. These terms are given as: The final equation of current at the drain terminal is: The equation for the final drain current can be substituted with (20) to be influenced by the oxide layer capacitance that exists in a cylindrical structure.
Fabrication Model of the CSDG MOSFET
By considering the surface potential, mobility concentration, and drain current parameters, the novel CSDG MOSFET has been proposed. The fabrication steps follow atomic vapor deposition under various ion concentrations in the controlled chamber [8,44]. The CSDG MOSFET has been designed using lanthanum oxide as a gate oxide layer. This layer gives better immunity to the short channel effects (SCEs).
The fabrication methodology is the extension of the authors' work carried out in ref. [6]. The fabrication of the CSDG MOSFET (as shown in Figure 3) was a challenging method since it involved careful involvement of the parameters to create a layer-by-layer approach [16,31]. The core was grown over the concentric discs (as in Figure 3a) placed in the chamber base. The core ranges from 2 nm in diameter and with uniform distribution (Step II). The next layer is the gate-1 terminal, which is 6 nm in diameter (Step III). The high-Îdielectric layer was placed next to the gate-1 terminal from 6 nm to 10 nm thickness to avoid SCEs (Step IV). The spacer extends for another 4 nm from the dielectric material (Step V). The concentric cylindrical bulk is the largest region of the device which extends from 14 nm to 22 nm in thickness (Step VI). The second spacer layer has an extension from 22 nm to 26 nm with 4 nm in thickness (Step VII). The second high-Îdielectric terminal was placed next to the second spacer layer, and it extends to a diameter of 30 nm (Step VIII). The last layer is the gate-2 material, and it acts as a surrounding layer with the largest diameter of 34 nm from the dielectric material (Step IX).
atomic vapor deposition under various ion concentrations in the controlled cham [8,44]. The CSDG MOSFET has been designed using lanthanum oxide as a gate o layer. This layer gives better immunity to the short channel effects (SCEs).
The fabrication methodology is the extension of the authors' work carried out in [6]. The fabrication of the CSDG MOSFET (as shown in Figure 3) was a challen method since it involved careful involvement of the parameters to create a layer-by-l approach [16,31]. The core was grown over the concentric discs (as in Figure 3a) (St placed in the chamber base. The core ranges from 2 nm in diameter and with unif distribution (Step II). The next layer is the gate-1 terminal, which is 6 nm in diameter ( III). The high-ƙ dielectric layer was placed next to the gate-1 terminal from 6 nm to 10 thickness to avoid SCEs (Step IV). The spacer extends for another 4 nm from the diele material (Step V). The concentric cylindrical bulk is the largest region of the device w extends from 14 nm to 22 nm in thickness (Step VI). The second spacer layer has an ex sion from 22 nm to 26 nm with 4 nm in thickness (Step VII). The second high-ƙ diele terminal was placed next to the second spacer layer, and it extends to a diameter of 30 (Step VIII). The last layer is the gate-2 material, and it acts as a surrounding layer with largest diameter of 34 nm from the dielectric material (Step IX). The fabricated CSDG MOSFET can be cut into the desired length, which maintains the L/W ratio and can be scaled and applied to different systems [32][33][34][35]. The desired length of the device is fixed as 100 nm in this work. The transport model used in the fabrication is uncoupled, and phonon scattering is allowed. The results were recorded and compared with the conventional methods of fabrication. The symmetric structure of the CSDG MOSFET was used in simulation to obtain the expected results as described in the next section.
Results and Discussion
The mobility of the device was modeled using the doping dependencies, velocity saturation at the transverse electric field, and high-electric field saturation. The ID versus VG curves is plotted below to help understand the characteristics of the CSDG MOSFET device. The double gate structure of the CSDG MOSFET reduces the effect of the SCEs to a greater extent. The SCEs were tackled by the CSDG MOSFET by lowering the subthreshold leakage current. The results were obtained for the symmetric CSDG MOSFET in the The fabricated CSDG MOSFET can be cut into the desired length, which maintains the L/W ratio and can be scaled and applied to different systems [32][33][34][35]. The desired length of the device is fixed as 100 nm in this work. The transport model used in the fabrication is uncoupled, and phonon scattering is allowed. The results were recorded and compared with the conventional methods of fabrication. The symmetric structure of the CSDG MOSFET was used in simulation to obtain the expected results as described in the next section.
Results and Discussion
The mobility of the device was modeled using the doping dependencies, velocity saturation at the transverse electric field, and high-electric field saturation. The I D versus V G curves is plotted below to help understand the characteristics of the CSDG MOSFET Nanomaterials 2022, 12, 3374 9 of 15 device. The double gate structure of the CSDG MOSFET reduces the effect of the SCEs to a greater extent. The SCEs were tackled by the CSDG MOSFET by lowering the subthreshold leakage current. The results were obtained for the symmetric CSDG MOSFET in the threedimensional space. The results attained from the proposed model were compared with the simulation results, and it is shown in the plots. The bulk of the device is assumed as a floating layer in all the simulations. When the thickness of the oxide layer becomes thin (<10 nm), ion volume inversion takes place due to the quantization of the electrons in the channel. The thickness of the oxide layer is always controlled. If it goes beyond 10 nm, the channel splits, and it results in a larger drain current. The model for the inversion region as in the earlier sections, was calculated by assuming the charge in the channel is fixed. The validity of the model was validated using the simulation of the practical device after fabrication. The electron density profile is shown in Figure 4, and it is evident that it shows the dependency between gate voltage and drain voltage. The minor difference present in the proposed and simulated data is mainly due to the expression in (19a) and the variable nature. This shows that it is suitable for the symmetric doped channel CSDG MOSFET. For a doped bulk symmetric CSDG MOSFET, variation between the model and simulation value includes the fixed charge value in weak and inversion regions. This uses the drift-diffusion transport model in the CSDG MOSFET of 100 nm channel length. The conduction band profile is illustrated in Figure 5. The characteristics of the cylindrical structure transistor were simulated, and they are plotted in Figure 6. The minor difference present in the drain current measurement is due to the difference in finite mesh density and linear voltage drop. This effect was neglected in the proposed model, making it unsuitable for DG MOSFET. The proposed model is highly suitable for the CSDG MOSFET regime. For a doped bulk symmetric CSDG MOSFET, variation between the model and simulation value includes the fixed charge value in weak and inversion regions. This uses the drift-diffusion transport model in the CSDG MOSFET of 100 nm channel length. The conduction band profile is illustrated in Figure 5. The characteristics of the cylindrical structure transistor were simulated, and they are plotted in Figure 6. The minor difference present in the drain current measurement is due to the difference in finite mesh density and linear voltage drop. This effect was neglected in the proposed model, making it unsuitable for DG MOSFET. The proposed model is highly suitable for the CSDG MOSFET regime. linear voltage drop. This effect was neglected in the proposed model, making it unsuitable for DG MOSFET. The proposed model is highly suitable for the CSDG MOSFET regime. Figure 7 shows the comparison of the doped channel of symmetrical FET between measurements and simulation outputs (for Tsi = 30 nm); IDS versus VGS in the CSDG MOSFET: The oxidant concentration plays a major role in performing uniform oxidation in the cylindrical walls of the heterostructure. The maximum oxidant concentration is observed to be 4.37 × 10 16 cm −3 of thickness 0.82 nm for (100) and 2.56 × 10 19 cm −3 of thickness 0.33 nm for (100) at dry oxidation and wet oxidation, respectively. The maximum oxidant concentration of the oxide layer is observed to be 3.90 × 10 16 cm −3 of thickness 0.96 nm for (111) and 2.11 × 10 19 cm −3 of thickness 0.49 nm for (111) at dry oxidation and wet oxidation, respectively. The transmission deviations in the simulation compared to the modeled The oxidant concentration plays a major role in performing uniform oxidation in the cylindrical walls of the heterostructure. The maximum oxidant concentration is observed to be 4.37 × 10 16 cm −3 of thickness 0.82 nm for (100) and 2.56 × 10 19 cm −3 of thickness 0.33 nm for (100) at dry oxidation and wet oxidation, respectively. The maximum oxidant concentration of the oxide layer is observed to be 3.90 × 10 16 The oxidant concentration plays a major role in performing uniform oxidation in the cylindrical walls of the heterostructure. The maximum oxidant concentration is observed to be 4.37 × 10 16 cm −3 of thickness 0.82 nm for (100) and 2.56 × 10 19 cm −3 of thickness 0.33 nm for (100) at dry oxidation and wet oxidation, respectively. The maximum oxidant concentration of the oxide layer is observed to be 3.90 × 10 16 cm −3 of thickness 0.96 nm for (111) and 2.11 × 10 19 cm −3 of thickness 0.49 nm for (111) at dry oxidation and wet oxidation, respectively. The transmission deviations in the simulation compared to the modeled CSDG MOSFET are plotted in Figure 8a-j with varying drain voltage. Being an extensive analytical approach, the drain current serves the purpose of electron concentration explicitly inside the concentric cylindrical structures. The characteristics of the proposed CSDG MOSFET simulated version were compared with the existing research, and it is illustrated in Figure 9. The fabrication masks for various heterostructures are illustrated in Figure 10. The fabrication masks vary with the unique structures involved in the design of the CSDG MOSFET. The performance of the device was analyzed for various threshold conditions of the gate voltage and other parameters. The characteristics of the proposed model were compared and presented.
Conclusions and Future Considerations
Three-dimensional surface potential was presented elaborately considering the mobility of the ions. It was derived from the undoped and the doped channel CSDG MOSFETs. These equations are expedient with Pao-Sah's integral to solve the drain current across the device length. The proposed model was consistent in terms of three-dimensional surface potential, the mobility for varying electric fields at the gate terminal, and the channel's thickness. The equations for the surface potential, mobility of ions, and drain current were developed using the physics and mathematical equation simplification noting proper boundary conditions. Better accuracy was achieved using the fitting parameters with boundary conditions. This work can be further continued by adding a quantum mechanical effect in the Fermi level using several high-κ dielectric materials. In addition, the CSDG MOSFET can be modeled using the effect of electron distribution along the channel and can be validated using various other semiconductor alloys for enhanced performance. The insertion of high-ƙ dielectric in the same structure can give numerous insights towards nano- The performance of the device was analyzed for various threshold conditions of the gate voltage and other parameters. The characteristics of the proposed model were compared and presented.
Conclusions and Future Considerations
Three-dimensional surface potential was presented elaborately considering the mobility of the ions. It was derived from the undoped and the doped channel CSDG MOSFETs. These equations are expedient with Pao-Sah's integral to solve the drain current across the device length. The proposed model was consistent in terms of three-dimensional surface potential, the mobility for varying electric fields at the gate terminal, and the channel's thickness. The equations for the surface potential, mobility of ions, and drain current were developed using the physics and mathematical equation simplification noting proper boundary conditions. Better accuracy was achieved using the fitting parameters with boundary conditions. This work can be further continued by adding a quantum mechanical effect in the Fermi level using several high-κ dielectric materials. In addition, the CSDG MOSFET can be modeled using the effect of electron distribution along the channel and can be validated using various other semiconductor alloys for enhanced performance. The insertion of high-ƙ dielectric in the same structure can give numerous insights towards nano- The performance of the device was analyzed for various threshold conditions of the gate voltage and other parameters. The characteristics of the proposed model were compared and presented.
Conclusions and Future Considerations
Three-dimensional surface potential was presented elaborately considering the mobility of the ions. It was derived from the undoped and the doped channel CSDG MOSFETs. These equations are expedient with Pao-Sah's integral to solve the drain current across the device length. The proposed model was consistent in terms of three-dimensional surface potential, the mobility for varying electric fields at the gate terminal, and the channel's thickness. The equations for the surface potential, mobility of ions, and drain current were developed using the physics and mathematical equation simplification noting proper boundary conditions. Better accuracy was achieved using the fitting parameters with boundary conditions. This work can be further continued by adding a quantum mechanical effect in the Fermi level using several high-κ dielectric materials. In addition, the CSDG MOSFET can be modeled using the effect of electron distribution along the channel and can be validated using various other semiconductor alloys for enhanced performance. The insertion of high-Îdielectric in the same structure can give numerous insights towards nano-technological advancements. Going forward, it will be fabricated as a cylindrical structure and tested for various environmental conditions. | 6,441.4 | 2022-09-27T00:00:00.000 | [
"Engineering",
"Materials Science",
"Physics"
] |
The Household Enterprise Sector in Ghana: Overview and Challenges
Household Enterprises (HEs) have not received much consideration in the enterprise literature even though they are crucial for the development of an economy. These enterprises have been the main source of livelihood for most families in the informal sector and their contribution to reduction in unemployment is pivotal to growth of developing economies. This paper explores the nature of HE sector in Ghana and the challenges they face in their daily operations. The study employed an informal enterprise survey of 729 household enterprises conducted in 2013 by the World Bank in Ghana. With the use of systematic review and descriptive analysis, the study outlined financial constraint as the main challenge faced by HEs and discussed the linkage between HEs and the financial sector in Ghana. Based on these findings recommendations were made to the major stakeholders in the sector (entrepreneurs, financial institutions and government).
Definition of Household Enterprises (HEs)
Household Enterprises (HEs) have not received much consideration in the enterprise literature even though they are crucial for the development of an economy. The definition of HE remains varying or unclear (Kayanula and Quartey, 2000). It is a matter of literature. The inconsistency in the definition of HE may lead to complications in the calculation of income and assets, and also the rate of return on HE (Samphantharak & Townsend, 2012). Kayanula and Quartey (2000) stated that: "There is no single, universal, or uniformly acceptable definition of enterprises" (p.225).
Therefore, quite a number of criteria have been employed to help define HE. A review of the literature on the definitions of HE is based on diverse criteria such as the number of workers employed (household members employed), the proportion of returns to the household, and the value of fixed assets. To classify a business as a HE, standard practice (International Labour Organisation [ILO], 2011) obliges that the following conditions have to be met: a) The ownership condition (owned by a member of the household) and at least b) The size criteria (limit of the number of employees), or c) The legal status (non-registration of the enterprise or its workers).
The last criterion (legal status) is mostly inconsistent since the rules on the registration of enterprises vary by country. The word 'registration' may also differ in meaning depending on the country. For example, in Uganda, registration means a certain level of legitimacy from the state, but this is not the case in Tanzania and Rwanda. Also, in some countries, it is legal to do business in an individual's own name even without registering. Therefore, it is only the first two criteria that are mostly used by most researchers in order to maintain consistency (Fox & Sohnesen, 2012). The World Bank in collaboration with Women in Informal Employment: Globalising and Organising (WIEGO) on a study on Policies and Programmes for Household Enterprises in Africa defined HE as: "Self-employed persons together with any family members or casual workers assisting them (not involving contractual workers)" (WIEGO, 2008, p.1). According to the World Bank (2012), HEs are self-employed enterprises working in non-agriculture, which may employ contributing family workers. It also stated that HEs together with Micro Enterprises (MEs) form what is known as Non-farm Enterprises (NFEs). bricks, village blacksmiths and tinsmithing, ceramics, beverages, food processing and bakeries, tailoring and clothing, wood furniture, electronic assembly, agro-processing, mining and timber, mechanics, chemical-based products, but does not involve farming, fishing, hunting and forestry (Kayanula & Quartey, 2000;Abor & Quartey, 2010;Quainoo, 2011).
The HEs are also classified based on the number of years they have been in operation. A study by Abor and Biekpe (2006) categorised them in this manner: (i) Infant -less than 1 year.
The majority of HEs in Ghana are not formally registered. Most of HEs run by females are more likely to operate from the home. The HEs owned by females are likely to be overlooked since they are home-based and do not operate directly in the traditional market. Therefore, these owners tend to be invisible entrepreneurs. Household savings is the main source of capital for HEs. After household savings, is assistance from friends or relatives, and then followed by the banks (GSS, 2014). HEs are usually more labour-intensive, and more efficient in developing countries like Ghana where labour is abundant and capital is scarce. Most of these HEs operate with low technological know-how and innovation.
In addition, income generated by the financial and physical capital of HEs cannot be straightforwardly separated from that generated by the human capital of members of the household (wage earnings). Also, they are not secured by limited liability, therefore, the owners are not different entities from their enterprises. This affirms what was established by Samphantharak and Townsend (2012) that, business assets and household assets are legally inseparable, therefore they are collectively used between household and business.
Another characteristic of HEs in Ghana is that their products and services are delivered to only the local market. They lack the ability to access the international market even if they wanted to. This is mainly because of the massive capital requirement for operating in the export market, low level of education, informal nature of the business, and lack of training for entrepreneurs (Gariba, 2015). The lack of entry barriers has created competition which has led to the closure of inefficient and poorly managed HEs, making the HEs in the trading (retail) sector face the highest closure risks.
Nevertheless, because of higher capital and skill requirements in the manufacturing sector, it has made it less competitive (GSS, 2014). The HEs in services and manufacturing are more likely to grow than those in trading.
Contribution of HEs to Economic Growth and Development
In the early 2000s, there has been a resurgence of economic growth and development in low-income SSA countries, including Ghana. Fox and Sohnesen (2012) postulated that, between the years of 2000-2008, countries like Ghana, Rwanda, Mozambique, Uganda, and Tanzania all recorded GDP per capita growth above 3 percent per annum. This growth was partly attributed to the increase in non-farm private enterprise employment, which included owners and family members in HEs.
Household Enterprises creates most of the new jobs outside of agriculture (GSS, 2014). The movement of labour outside of the agricultural sector in the recent decade shows up as HE employment, and just a little showing up as wage employment. The principal reason for the increase in HE employment over the previous years was due to the debt crisis, during which many developing countries underwent a laying off of workers in the public sector, and the private sector was not capable of absorbing the growing labour force (Fox & Gaal, 2008). Employment in HEs of SSA countries undergoing growth and poverty reduction is the rapid growing part of such economies. These enterprises have been the key solution to diversification by transforming labour from subsistence agriculture to non-agriculture activities (World Bank, 2012). In Ghana, the GSS (2014) stated in the GLSS report that, more than six million people are engaged in non-farm enterprises, including both HEs and MEs.
Another key contribution of the HEs to both developed and developing countries is poverty alleviation and diversification of income. Although 40 percent of household rely on HEs as an income source, they (HEs) are often disregarded in low-income SSA development strategies (Fox & Sohnesen, 2012). This is because the majority of the informal enterprises are often believed to be unproductive, hence described as a poverty trap. Contrary to this assertion, a study by Barrett, Reardon and Webb (2001) evaluated household livelihoods in rural SSA and concluded that HEs (non-farm activities) aided in the reduction of household poverty. It was also noted by Fields (2012) that, the only way for poor households in SSA to eradicate poverty is by earning more money ijbm.ccsenet.org International Journal of Business and Management Vol. 15, No. 8;2020 from employment. He further argued that most non-farming employment in SSA countries like Ghana is now in HEs and has helped alleviate poverty.
In Ghana, the majority of HEs in rural areas are often seasonal ventures, since investments in the agricultural sector (farming) have not reduced risk or increased productivity enough for households to particularly specialize in one sector or the other (Fox & Sohnesen, 2012). This enables poor households to diversify their income, leading to a rise in income and making them less poor.
Policies, Institutional and Support Environment for HEs
Household Enterprise improvement campaign in Ghana was not a major priority of the government during the 1960s and 1970s. This is because, during the first republic era (1960)(1961)(1962)(1963)(1964)(1965)(1966), the president (Dr. Kwame Nkrumah) emphasized on policies in the direction of industrialisation and modernisation at the state level but did not support the micro domestic indigenous sector. The economic crunch (high inflation) that hit Ghana in the early 1980s pushed numerous employees in the formal sector into alternative self-employment in order to make a decent income (Kayanula & Quartey, 2000). Self-employment and small scale enterprise employment recorded 2.9 percent growth per annum; this was more than that of employment growth in large firms (Steel & Webster, 1991).
The government then got interested in the expansion of the small business sector. The National Board for Small Scale Industries (NBSSI) was also established in 1985, to cater for the needs of small businesses; this was through training programs such as the Entrepreneurial Development Programme, which is aimed at training and assisting individuals with potential entrepreneurial capabilities into self-employment (Kayanula & Quartey, 2000).
A Mutual Credit Guarantee Scheme was established for entrepreneurs, who for the reason of no collateral could not access bank loans, to access loans. Also, a Rural Finance Project was established to provide long-term loans for craftsmen and small-scale farmers (Kayanula & Quartey, 2000). The National Vocational and Training Institute (NVTI) was also founded by the government to train and enhance the skills of elementary and secondary school leavers, and such other people through master craftsmanship, apprenticeship and career development (NVTI, 2009). The World Bank in collaboration with the Programme of Action to Mitigate the Social Costs of Adjustment (PAMSCAD) made special funds available to support microenterprises in accumulating finances. This was founded on the belief that, the main reason why the private sector had not grown as it should have was because of unavailability of loans from the formal financial institution (Abor & Biekpe, 2006).
In recent times, the National Committee on the Informal Economy (NCIE) support HEs through the Business Advisory Centres (BACs) and the local authorities such as Metropolitan, Municipal and District Assemblies (MMDAs). The BACs main responsibilities are, to support them in the form of training and counseling in areas like record-keeping, preparation for the NVTI professional tests, visiting other HEs to learn from them and also to encourage HEs to form their own associations (Quainoo, 2011). The MMDAs are responsible for zoning and giving HEs a workplace in places like the local market area and they also undertake local training with the aim to build the capacity of HE operators. Some of the training programs are; handicrafts making, shea butter extraction, livestock rearing, soap making, among others (Quainoo, 2011). The challenge encountered with the implementation of these policies is that they require complex legal processes to be eligible for the package they come with. Also, many of the loan schemes are mostly centralised in the capital cities like Accra and Kumasi, making it difficult for rural-based HEs to access (Baah-Nuakoh, 2003).
Nature of the HEs in Ghana
This study employed the World Bank's Informal Enterprise Survey (IFS) in Ghana for the year 2013. This is a survey that covered non-agricultural enterprises which are informal and privately owned by households. By informal, they are enterprises that are not registered with the Registrar's General Department. The data fits the description of a HE according to the ILO (2011). The World Bank's IFS used a stratified sampling technique. Enterprises were stratified based on the sector of activity and geographical location. The sectorial stratification was designed as follows: four manufacturing sectors (food and beverages, chemicals and plastics, textiles and garments, other manufacturing) and two service sectors (retail and other services). For geographical location, enterprises were stratified based on the distribution of economic activities taking place in the four main regional urban centres namely; Accra, Tema, Takoradi, and Northern Sector (Kumasi and Tamale). The regions were then divided into 180 zones where at least four enterprises were randomly sampled per zone. A total of 729 enterprises were surveyed. The distribution of the enterprises among the four regions is as follows: Accra 176, Northern Sector (consisting of Kumasi and Tamale) 189, Takoradi 180 and Tema 184.
This section gives a detailed statistical distribution and overview of some variables of the HE sector in Ghana based on the World Bank's Informal Enterprise Survey (as shown in Table 1).
Owner's Age: To begin with, the owner's age distribution of the survey ranges from 18 years to 80 years with an average age of about 39 years. The majority (over 50%) of the entrepreneurs were between 31 to 45 years, with just about 5% who were above 60 years of age. Approximately 23% and 21% were in the age brackets 18-30 years and 46-60 years respectively.
Household Size: The household size of the entrepreneur ranges from 1 to 65 people with an average of approximately 6 people. Most of the households were within the size bracket of 1-5 people (approximately 59%), followed by 6-10 people (approximately 36%) and finally those households with size more than 10 people are just about 5%.
Owner's Experience: The entrepreneurs' experience average 8 years which ranges from no experience (0 years) to 50 years of experience. The majority (about 44%) of the entrepreneurs were in the range of 0-5 years of experience, followed by 6-10 years and more than 10 years which approximated 26% and 30% respectively.
Number of Household Workers:
The number of household workers range from 0 to 10 members, with an average of approximately 1 member. 426 enterprises (about 58%) employed no household member, 292 enterprises (about 40%) employed 1 to 3 members and 11 enterprises (about 2%) employed 4 to 10 members of their household.
HE age: The survey showed that age of the enterprise ranges from less than a year old to 53 years with an average of 8 and half years. The study then followed the categories used by Abor and Biekpe (2006) to further group them. There were 2.74% infant enterprises (less than 1 year), 44.03% young enterprises (1 to 5 years), 27.57% adult enterprises (6 to 10 years) and 25.65% matured enterprises (more than 10 years). This distribution of the age of the enterprise confirms the results of Fox and Sohnesen (2012) which indicated that survival of HEs tends to reduce as the enterprise approaches maturity.
Gender:
The survey results show that there are 37.17% male-owned enterprises and 62.83% female-owned enterprises.
Marital Status: The survey shows that 470 (about 64%) of the entrepreneurs are married.
Education:
The results of the survey also categorizes education into five main groups which are no education (13%), basic education (45%), secondary education (30%), vocational education (8%) and tertiary education (4%). But for the sake of this study, education was categorized into high education (secondary, vocational and tertiary education) and low education (no education and basic education).
Diversification: From the survey, the majority (approximately 95%) of the entrepreneurs are not diversified. This confirms the findings of previous studies (Haggblade, Hazel, & Reardon, 2010;Fox & Sohnesen, 2012) which indicate that HEs often serves as the only or main source of livelihood for most of the household of the entrepreneurs.
Sector: The survey covered an approximately equal number of enterprises in manufacturing, and retail and services sectors; 365 and 364 respectively. Those in the retail and services sector have a higher rate of access to loans (approximately 47%) than those in the manufacturing sector.
Base of Operations:
The survey revealed that 585 enterprises (about 80%) are market-based whereas 144 enterprises (20%) are home-based.
Financial Records: Just about 33% of the enterprises kept records. This supports the findings of Samphantharak and Townsend (2012) which states that most HEs do not keep any financial records and keep their operations at the informal level.
Savings Account: In addition to the fact that they operate at the informal level, they do not have bank accounts for the operations of the enterprise. The survey showed that about 60% do not have a saving account and just 40% of the HEs save with formal financial institutions.
Asset: Concerning assets ownership, the majority (approximately 60%) of the HEs do not own assets. The assets in this survey entailed machinery and vehicles. Among the 295 (about 40%) enterprises that own assets, 182 (about 62%) of them own machinery, 72 (about 24%) own vehicles and 41 (about 14%) own both machinery and vehicle.
Problems Facing Household Enterprises (HEs)
This section reports on the challenges most HEs face in starting and the daily running of their businesses.
Inadequate Capital and Lack of Finance
Inadequate capital and lack of finance are the challenges repeatedly mentioned by most HEs (GSS, 2014). It covers the several challenges confronted by HEs in their daily operations as well as the following: (i) inability to acquire a suitable worksite; (ii) difficulties in securing tools and material inputs; (iii) high cost of raw materials; (iv) inability to meet customer demands; (v) high costs of utilities and fuel.
The challenge of lack of finance includes a circumstance where HEs experience hitches in starting and in running the affairs of the business due to delays or failure to obtain loans. Many HEs try but fail to obtain loans from formal financial institutions. Even those granted the loans, encountered a lot of complexities in the process. A World Bank study showed that 71 percent of the urban HEs and 65 percent of the rural HEs reported difficulties in accessing loans. In all, 68 percent of all entrepreneurs surveyed claimed to be experiencing difficulties in acquiring finance for their businesses (Bakeine, 2009). The main difficulties faced in their effort to access loans include finding acceptable collateral; very high interest rate; the maximum loan size allowed for micro businesses being too small; the loan process is too long and tedious to deliver the required funds at the time needed; and the repayment terms being unfavourable (Stephanou & Rodriguez, 2008;Bakeine, 2009;Alhassan & Sakara, 2014). Resulting from the inability to raise finance, numerous HEs survive on a very insignificant capital base and ultimately collapse. Because of this, many HEs resort to the informal sector, including borrowing from friends and relatives to accumulate some capital (Nkuah, Tanyeh, & Gaeten, 2013;GSS, 2014). In several cases these alternatives fail to deliver, and should they even deliver, they only make available just a fraction of what the enterprise actually needs.
Poor Infrastructure
The problem of poor infrastructure entails HEs experiencing poor road network and inconsistencies in power supply. The problem of access, reliability, and cost of electricity (power) in Ghana is a critical challenge particularly among HEs in the manufacturing, services, and trade (retail) sectors. Whereas rural based HEs are almost always affected by inaccessibility to electricity, urban HEs may have access to electricity but are affected by the unreliable nature of the supply and high cost of electricity (Bakeine, 2009). The direct consequences of this problem on HEs' operations are lost employment and a decline in income. The common remedy most of the HEs resort to is buying generators to operate their business. This often is out of their reach since the cost of buying and maintaining a generator is expensive and therefore most of the enterprises' production reduces drastically.
Lack of a Proper Worksite
Lack of a proper worksite, in this case, comprises of lack of a work place; unsuitable work place; and lack of storage space. Unsuitable work place includes worksites without a shelter and opened to hash weather (hot sun and rain), and worksites considered as unsafe and insecure. This is a general challenge among entrepreneurs in quest of starting a business. However, after discovering a place and starting operations, HEs sooner or later are faced with a similar problem when rent increases or they need relocation to bigger sites to accommodate the expansion. Bakeine (2009) argues that the majority of HE entrepreneurs do have premises to operate in, but their key setback is the high cost of rent. With increasing costs in most SSA economies, landlords periodically increase rent, and many of the HEs cannot pay such rapidly increasing rent.
Lack of Business Knowhow
The lack of business knowhow unfolds in two main branches. These are: (a) finding buyers; (b) problem of bad debts (Bakeine, 2009). Lack of buyers is one of the main challenges of HEs on the lookout to sell their goods and services. The concerns, in this case, are insufficient buyers, high level of competition for the limited buyers Business and Management Vol. 15, No. 8;2020 when it comes to loan acquisition. However, loans from such sources are limited and often come at high interest rates (Aryeetey, 1992;Amissah & Gyeke-Dako, 2016). On the other hand, there is no financial constrain when it comes to the formal financial sector. But such loans always come with complex paperwork and collateral requirements making it difficult for HEs to acquire loans from such sources.
According to the GSS (2014), among the Non-Farm Enterprises that applied for credit, 31% of them had access to bank loans. In the informal financial sector, we see that loans from family and friends were the highest (29%) and those from Money Lenders were the least (8%). This is because loans from money lenders come at a high-interest rate and it is usually the last resort for most entrepreneurs. The pie chart shows that most of the HEs have access to informal loans and are more active in the informal financial sector . From fig 3, we see that the formal financial sector shows 30% of access to loans whilst the informal sector shows 70%.
Figure 3. A Pie Chart showing the Source of Credit for Non-Farm Enterprises
A study by De la Torre, Peria and Schmukler (2010) indicated that most of the micro and small enterprises opting for the informal source of finance does not necessarily enhance greater output and revenue. They argued that it is common sense to find most of the small enterprises being financed by informal loans, but in the end, most of them fail and collapse in no time. Aryeetey (1998) also argued that informal institutions are unstable, collapse overtime and their delivery of credit is not appropriately done. In addition, Amissah and Gyeke-Dako (2016) stipulated that formal financing of small enterprises are better than informal financing. They found that in Ghana, there is a positive significant relationship between formal financing and enterprise performance and also added that, although formal financing has a higher impact on the performance of large firms it also has a high significant impact on MEs and HEs performance as well. This is because the formal institutions closely monitor the performance of the small enterprises to prevent defaulting of the loans. But this does not mean that informal financing and self-financing is not important.
The decision as to which sector to apply for a loan goes beyond only growth and expansion of the enterprise. It also involves proximity to which of the financial sectors; the urgency of the demand for the loan; and also the requirements the lenders may demand. Aryeetey (1992) stated that informal loans are often demanded after the rejection of bank credit application and this is because bank credit is cheaper than informal loans (except for loans from friends). Although the financial market in Ghana is differentiated, the demand for loans is not exclusive of each sector. In applying for loans from the formal and informal financial sector, sometimes these applications serve as a substitute for one another, but other times they serve as complements (Munira, 2013).
Conclusions and General Recommendations
This section will elaborate on some strategies which can be used to finance HEs. Financing of HEs may vary from country to country depending on the nature and structure of the HE sector (World Bank, 2018). Therefore, the strategies in this study were drawn based on the descriptive statistics and the nature of HEs in Ghana. In order to properly make these strategies efficient, the various actors have to be involved.
Entrepreneurs
Entrepreneurs should understand the dynamics of loan application. They need to know that no lender would invest in a business without potential. So, there is the need for HEs to present themselves as viable enterprises and be convincing enough by proving to be creditworthy. They can do this by preparing project proposals and keeping records. The entrepreneurs should also embark on training to improve their skills in order to make them more efficient in the management and allocation of resources. Also, entrepreneurs should be educated on the need for keeping financial records because the majority (67%) of them do not keep financial records. Since approximately 60% of the entrepreneurs in the HE sector have at most basic education, there is the need to educate them on the importance of keeping a financial record. They may see it as challenging, but they can adopt the simple bookkeeping method which reports on inventory and profit. Furthermore, when entrepreneurs were asked what would increase their chances of accessing a loan, over 70% indicated that by formalizing their activities. This increases their chances of accessing a loan by signaling to the lender their creditworthiness.
Financial Institutions
The formal financial institutions (banks) need to see HEs as a strategic sector for expansion of their operations. It is a sector with great potentials and if the banks see it as such they will also benefit greatly. Although it is a sector full of risk, the profits and benefits are undeniable. The banks, therefore, need to ease down a bit on the issue of collateral and also focus on the potential of the business proposal of the entrepreneur. They need to also make the repayment conditions quite flexible by increasing the maturity period of loans for HEs. Also, lending is not the only service banks can provide for HEs. The banks should go beyond the lending services by organising training programmes to educate entrepreneurs who bank with them and those who do not. They can educate them on the loan application process, writing of a business plan, capacity building, how to keep financial records, and many more. The experience of formal financial institutions over the years by working with large enterprises far exceed that of the informal financial sector, hence making them the best choice for a long-term financial relationship. Their understanding of enterprise survival skills, surviving start-ups and other enterprise related issues will certainly be beneficial to the growth of HEs. This will improve the HEs' survival rate, by making them more profitable and less credit constrained. The banks will also benefit since those entrepreneurs will recommend them to their colleague entrepreneurs.
Government and NGOs
The government should provide education for entrepreneurs of HEs on how to manage their business in a manner to attract investments. The government should focus on improving the financial literacy of entrepreneurs. This will help entrepreneurs take advantage of the available financial services and also avoid risks. Depending on the level of sufficient financial education, entrepreneurs can then take advantage of the existing government and non-government financial schemes. In most cases, entrepreneurs in the informal sector are not aware of the various financial options at their disposal. Over 53% of HEs have been in business for 5 years or more but they are ignorant of the available financial schemes except for bank loans. There are the likes of Promotion of Small and Micro Enterprise Fund (PSME), Support for Private Enterprise Expansion and Development (SPEED), and Funds for Small and Medium Scale Enterprise Development (FUSMED), but most of the entrepreneurs are ignorant. This is because often times awareness of these schemes is done only in a few capital cities, such as Accra and Kumasi. The issue of awareness has been talked about in most research (Abor & Biekpe, 2006), but the problem is the scope of awareness. The government and NGOs who provide these schemes should embark on an awareness which goes beyond the capital cities to small towns and villages.
One of the main reasons for HEs' credit constraint is because of the nature of risk which is associated with their operations. Therefore, the government should encourage the formation of enterprise associations to serve as a credit guarantee for those that may apply for loans. Through a large number of members of these associations, the risk related to HE loans can then be spread out. The study reveals that operating a HE serves as the only livelihood of majority (96%) of the household. Hence, the government needs to produce an enabling environment for more HEs to spring up since this can solve the problem of unemployment and eradicate poverty. The government must focus on providing uninterrupted power and water supply. This is because power and water are also major obstacles facing HEs. By this their quest for obtaining loans to solve power and water problems is curtailed. This will indirectly prevent the need for the loan for some HEs. | 6,834.8 | 2020-07-26T00:00:00.000 | [
"Economics",
"Business"
] |
Retrospective analysis of the impact of respiratory motion in treatment margins for frameless lung SBRT based on respiratory‐correlated CBCT data‐sets
Abstract Purpose To investigate the impact of respiratory motion in the treatment margins for lung SBRT frameless treatments and to validate our treatment margins using 4D CBCT data analysis. Methods Two hundred and twenty nine fractions with early stage NSCLC were retrospectively analyzed. All patients were treated in frameless and free breathing conditions. The treatment margins were calculated according to van Herk equation in Mid‐Ventilation. For each fraction, three 4D CBCT scans, pre‐ and postcorrection, and posttreatment, were acquired to assess target baseline shift, target localization accuracy and intra‐fraction motion errors. A bootstrap analysis was performed to assess the minimum number of patients required to define treatment margins. Results The retrospectively calculated target‐baseline shift, target localization accuracy and intra‐fraction motion errors agreed with the literature. The best tailored margins to our cohort of patients were retrospectively computed and resulted in agreement with already published data. The bootstrap analysis showed that fifteen patients were enough to assess treatment margins. Conclusions The treatment margins applied to our patient’s cohort resulted in good agreement with the retrospectively calculated margins based on 4D CBCT data. Moreover, the bootstrap analysis revealed to be a promising method to verify the reliability of the applied treatment margins for safe lung SBRT delivery.
(Mid-V), 8,9 in which the predominant breathing phase closest to the time-weighted mean tumor position is selected for the planning, thus ensuring small treatment margins. However, when calculating dose and appropriate margins for lung SBRT, motion, baseline shifts and low-density media must also be considered. Van Herk et al. 10 proposed a probabilistic approach to create the margins. The key of this approach is to include the systematic and random errrors based on clinical practice when computing the margins, in order to ensure adequate tumor dose coverage for a high percentage of patients.
The systematic and random errors for lung tumors can be defined by statistical analysis of the distribution of changes in tumor position during a course of radiotherapy. Therefore, the 4D CBCT 11 makes it possible to assess, prior to each fraction treatment, the mean position and the 3D trajectory of the tumor, and then to verify the applied treatment margins on a daily basis. Moreover, breathing-related variations in tumor positions can appear during the treatment intra-and inter-fractionally. The intra-fraction variation describes the variation in the tumor position during one treatment fraction, [12][13][14] while the inter-fraction variation describes the variation of the tumor position between fractions. These two types of tumor motion variations are mainly manifested as tumor baseline shifts and introduce additional errors in the treatment. For this reason, 4D CBCT images taken at different moments in the treatment session are an appropriate way to quantify such errors; they also allows to track the 3D trajectory of the tumor, therefore veryfing the applied treatment margins on a daily basis. Within this context, the van Herk approach is commonly used to prospectively define setup margins for lung SBRT. However, this approach relies on statistical analysis of prospective data, assuming that no changes in the process occurs in the future. In this paper we propose two approaches that proactively re-examines the margins when the process is changed by a modification in contention, treatment technique, etc. In those cases, it is indeed crucial to verify the applied margins to ensure safe SBRT delivery.
2.A | Patients
Thirty patients (for a total of 229 fractions) with lower (n = 6), upper (n = 9) and mid-lobe lesions (n = 15) and stage T1-T2 nonsmall-cell lung cancer were treated with SBRT. For each patient, a planning CT was acquired (16-slices Aquilion LB; Toshiba, Japan) using a 4D acquisition protocol. Ten respiratory phases were retrospectively reconstructed from the 4D CT with the phase sorting algorithm. All patients were scanned in head-first supine position using an arm and knee support. No additional immobilization devices were used, and none of the patients received any instructions for regular breathing before scan and treatment. The tumor motion characteristics, described as amplitude and trajectory, were assessed in the three directions. To determine the Mid-V phase, 10 GTVs were contoured on the ten phases and the center of the mass of the GTV was determined for each phase. The phase providing the minimum distance between the center of mass of the GTV on each phase and the average center of mass of the GTV among the ten phases was selected as the Mid-V phase. Once the Mid-V 9 phase was identified then it was used for the delineation of the tumor and organs at risk as well as treatment planning. The patient-specific tumor motion characteristic was used to calculate planning target volume (PTV) margins, with the van Herk equation. 10
2.B | Target volumes and planning
The Gross Target Volume (GTV) was delineated on the Mid-V phase, in the Velocity software™ version 2.8 (Varian Medical Systems, USA), using a pulmonary level window (WW: 1224; WL: −412). No margins for microscopic extension were added to the GTV to form a Clinical Target Volume (CTV). 15 The PTV was created by applying margins to the GTV based on the van Herk equation 10
2.C | Target motion assessment
Target motion amplitude was individually quantified for all patients before the start of the treatment ( Table 1). The amplitude of the target measured from the 4D CT was defined as the maximum coordinates minus the minimum coordinates of the target centroid in the left-right (LR), cranial-caudal (CC), and anterior-posterior (AP) directions. The 3D scalar amplitude was defined as the distance in 3D coordinates and calculated as ffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffi ffi . The 4D CT parameters were 120 kV, 150 mA, a detector width of 320 mm and a rotation time of 0.5 seconds. The pitch was less than 0.1 in order to ensure that at least one complete respiratory cycle was included in the scan acquisition. 16 Images were reconstructed with 2 mm slice thickness and 2 mm slice separation. The respiratory signal was tracked with the AZ-733 V ANZAI belt (ANZAI Medical Solutions, Japan) measuring the variation of pressure on the belt generated by the breathing motion. Ten respiratory breathing phases were sorted retrospectively. bony anatomy (i.e. vertebrae) and of the GTV (soft-tissue) with an expansion of 5 mm was chosen in order to create a 3D shape of the region of interest (ROI). That ROI was automatically registered to each phase of the 4D CBCT. The goal was to verify that the overall tumor motion excursion measured on the ten phases was within the PTV margins applied on the Mid-V phase. In case a shift was detected, only the translation corrections relative to the GTV isocenter were applied to the couch, because rotation corrections were not supported by our treatment couch. A second 4D CBCT was acquired after couch correction to assess the residual setup errors.
Again, a dual automatic registration of both bony anatomy and ROI was performed in order to visually validate the target alignment. A posttreatment 4D CBCT scan was acquired at the end of the treatment delivery to quantify the intra-fraction motion errors, obtained as the difference in target alignment between the second and the third 4D CBCT scan. To reduce the additional dose to the patient, the first 4D CBCT was acquired with the standard protocol of 4 minutes, while the second 4D CBCT was reduced to 2 minutes by downsizing the number of projections and the final 4D-CBCT to only 1 minute. The resulting image quality was good enough to evaluate the intra-fraction motion errors. 18 Finally, the 3D couch shifts from the three 4D CBCTs using soft-tissue and bony registration were collected for all treatment fractions and for all patients and used to retrospectively determine the margins according to our data as described in the Margins section.
2.E | Margins
The 3D couch shifts using soft-tissue and bony registration were collected for all treatment fractions for all patients. The mean and standard deviation were calculated for each patient. From these data, the standard deviation of the systematic error (∑), and standard deviation of the random error (σ) were calculated. The ∑ was obtained by calculating the standard deviation of the mean for each patient, and the σ was the root mean square of the standard deviations for each patient.
To analyze the difference between the bony and soft-tissue registration, the couch shifts obtained using soft-tissue registration were subtracted from the couch shifts obtained using bony registration in each direction. Finally, the PTV margins, M(PTV), for frameless SBRT patients with online 4D CBCT image guidance were calculated for each patient by applying the van Herk equation 10 : where ∑ TOT and σ TOT are the overall systematic and random errors (as defined in Equations 2 and 3) 19 and σ p is the width of the penumbra modeled by a cumulative Gaussian.
Sum of the standard deviations of the systematic errors calculated from delineation, localization and intra-fraction.
Sum of the root mean square of the random errors calculated from localization, intra-fraction and respiratory motion.
For the lung, σ p was taken equal to 0.64 cm as analytically estimated by Mexner et al. 20 initially taken from the data of systematic and random errors reported in the literature 17 (target localization accuracy, intra-fraction motion and target delineation uncertainty, intra-fraction motion and respiratory motion, see Table 2). Then the errors obtained from the retrospective analysis of the patients treated at our institution were used to compute customized margins.
2.F | Iterative analysis
To assess the robustness of our data, the margins were recalculated with an iterative method for different subsets of 10, 15, 20, 25 and 30 patients taken in chronological order (p + 1) with respect to their treatment. The scope was to determine whether or not the margins calculated were converging for samples with increasing number of patients. This approach has been chosen at first due to its rather simple implementation; however it presents a major drawback, the lack of large data to build good statistics. This was a clear limitation to validate our results.
2.G | Bootstrap analysis
The principle of the bootstrap method is that inference regarding a population can be modeled by resampling with replacement a subset of this population. 24,25 In this way, it is possible to expand the sampling from a limited pool of data and better estimate the statistical parameters of the population. In particular, for each patient error (target localisation accuracy, intra-fraction motion, and target delin-
3.D | Iterative analysis
The margins calculated with the iterative analysis using different subsets of patient samples are reported in Figure 4, along with their corresponding standard error. An asymptotic margin reduction trend is observed as the number of patients involved in the calculation increases.
| DISCUSSION
The aim of our study was to provide centers, which are either implementing frameless lung SBRT or still using literature margins, a method to calculate personalized margins. The method proposed in this paper takes into account changes in the process due to it is crucial to verify the applied margins to ensure continued safe SBRT delivery. We therefore retrospectively analyzed our patient cohort to assess the margin uncertainties induced by respiratory motion during frameless stereotactic radiotherapy, and then compared them with already published data. We also determined the minimum number of patients required to validate our treatment margins based initially on literature data with an iterative method and a bootstrap method. The bootstrap method performed better than the iterative method. The former having larger data than the latter was capable to provide better statistics and so to better converge.
At first, we assessed the target motion excursion for each patient by analysing 4D CT data. As expected, we found that the most important motion was in the superior-inferior direction, with a maximum tumor motion of 2.2 cm, in agreement with other authors. 13,14 The tumors located in the lower lobe were the most impacted by the large motion amplitude, while the upper and median lobes were giving similar results. In this specifc case, the reliability of the frameless approach with respect to the breathing managing technique might be questionable. However, in our cohort we found only one patient where the motion amplitude was superior to 2 cm that would have justified the benefit of using breathing management technique. Moreover, we found a correlation between motion excursion detected in the 4D CT and in the 4D CBCT data, with a correlation coefficient of R 2 = 0.96 in the LR and SI directions, and R 2 = 0.92 in the AP direction. The observed differences may be due to the different techniques used for phase sorting, i.e belt for 4D CT and diaphragm motion for 4D CBCT. Nevertheless, the respiratory motion assessed from the 4D CT scan was mostly reproducible during the treatment delivery for our patient cohort (see Figure 1). [28][29][30][31] As also found in a recent paper of Liang et al. 32 if the baseline shift can be corrected by treatment couch, the target motion range is comparable to the one assessed with the 4DCT. Regarding the use of the 4D CBCT, it should be noted that for an ITV approach, the 3D CBCT alone may be sufficient since the blurred target volume on the 3D CBCT can be associated to an ITV; however for a Mid-V approach, a 4D CBCT is highly recommended as confirmed by others. [33][34][35] From the retrospective 4D CBCT data analysis, we observed that the target delineation was the largest error as was found by others. 26,27 It is well-known, 10 using first an iterative method. As shown in Figure 4, the results did not converge for 30 patients; in particular, a monotone decreasing function with associated large errors bars was observed. As a consequence, the bootstrap method was chosen, providing more statistics.
This method was recently implemented in radiation oncology to estimate toxicity, setup errors, organ motion, or in other applications 43,44 , but it was never applied to the context of margin validation. The analysis showed that, independently from the initial patient sample size, a sample of at least 15 patients was needed to observe a convergence (see Figure 5). This is in agreement with a similar study conducted by Matsumoto et al. 45 Chaikh et al. 46 where they also reported that the bootstrap method can be considered as a practical solution to simulate a larger population in case of a small sample size. In their paper, the authors recommended the use of the bootstrap for a sample size larger than 10 to provide good estimation in case of heterogeneous and not normally distributed data. The main difference between the iterative and bootstrap methods is that with the iterative method we can only extrapolate the data to obtain the correct margins, while it is possible with the bootstrap method to reach a convergence (plateau in Figure 5) with at least 10 patients, 28 and so to define the correct margins in each direction.
A limitation of this study is that rotational errors were not taken into account in the margins computation, because our linear accelerator was not equipped with a 6 degrees of freedom (DOF) couch.
However, in our study we did not observe rotation angles larger than 1°. Besides, it is important to notice that the lung SBRT tumors are generally small and spherical in shape; thereby the value of rotational shifts is further minimized, by placing the isocenter within the GTV. Indeed, as found by Ottoson et al. 47 CTV to PTV margins were approximately the same, regardless if the CBCT matches were performed with 3 or 6 DOF. Finally a robotic couch wouldn't lead to further margin reduction.
If we now consider the impact of the type of technique VMAT or IMRT to the margins, in the publication of Rana et al. 48 it has been shown that the major advantage of VMAT over IMRT is in the reduction of the number of monitor units leading to a faster treatment delivery times without compromising the quality of the treatment plans. Hence, faster delivery time is more patient-friendly and minimizes intra-fraction patient motion enabling the reduction of the treatment margins. 49,50 In line with this study, in our center all SBRT are delivered with VMAT technique.
| CONCLUSIONS
The study presented here is a retrospective margins analyisis collected on a group of patients. We believe that this analysis could be beneficial to centers that want to apply personalized margins or simply adapt their margins.
The minimum number of patients needed to reach a convergence in the margin definition was evaluated using both iterative and bootstrap methods. The two methods provided similar results within the uncertainties. However, the iterative method was not converging because the number of patients of our cohort was not enough to reach conclusions on the margins. On the contrary, the bootstrap method showed that the required patient sample size to validate our treatment margins for frameless lung SBRT on a population scale was 15 patients.
To conclude, when implementing lung SBRT treatments, or when adapting the lung SBRT treatment protocol due to changes in local practice, an analysis based on the bootstrap method is suggested to verify the safe delivery of the treatment, without adding extra dose to the patient and increasing the treatment time. | 4,044.6 | 2020-09-30T00:00:00.000 | [
"Medicine",
"Physics"
] |
Accuracy of five different 3D printing workflows for dental models comparing industrial and dental desktop printers
Objectives The aim of this study was to evaluate the accuracy, in terms of trueness and precision, of printed models using five different industrial and dental desktop 3D printers. Materials and methods Full-arch digital models with scanbodies of 15 patients were printed with five different 3D printers. The industrial printers were 3D system Project MJP2500 (3DS) and Objet30 OrthoDesk (Obj). The dental desktop printers were NextDent 5100 (ND), Formlabs Form 2 (FL) and Rapidshape D30 (RS). A total of 225 printed models were analysed. The printed models were digitized and compared with the reference cast model using the Control X software (Geomagic). The descriptive statistics and one-way ANOVA with the post hoc Tukey test were performed (α = 0.05). Results The one-way ANOVA for the trueness and precision of the printed model presented the best results for the 3DS, followed by ND, Obj, FL and RS (P < 0.01). In the scanbody zone, the best results were for the 3DS group, followed by Obj, ND, FL and RS (P < 0.01). Comparing the technologies, the Multijet technology used in industrial printers presented better results than the DLP and SLA technologies used in dental desktop printers (P > 0.01). Conclusions There were statistically significant differences in terms of the accuracy of the printed models, with better results for the industrial than the dental desktop 3D printers. Clinical relevance The industrial 3D printers used in dental laboratories presented better accuracy than the in-office dental desktop 3D printers, and this should be considered when the best accuracy is needed to perform final prosthetic restorations.
Introduction
In recent years, dentistry has undergone a digital revolution, and computer-aided design and computer-aided manufacturing (CAD/CAM) technology is now a daily practice in any field of dentistry. Using an extraoral or intraoral scanner, we obtain an STL file with the three-dimensional (3D) data of our patients' mouths [1][2][3]. After that, with various CAD software available and supported by the dental technician, the dentist obtains a range of devices, such as surgical guides, orthodontics splints, prosthetic structures (crowns or bridges) and models, among others [4]. To move from the virtual to the real environment, designs must be manufactured using CAM systems [5]. In this step, a fast-growing alternative to milling methods is 3D printing, also called additive manufacturing or rapid prototyping. This technology allows the fabrication of objects layer by layer in crosssections from digital designs or impressions [6,7]. 3D printing manufacturing, compared to subtractive methods, allows the construction of objects with complex geometries, and no material is wasted, leading to a more sustainable process [8]. In addition, there are processes that allow for working with different raw materials, which may be grouped into binder/ powder material combinations, including polymers (resins and thermoplastics), metals and ceramics [7].
One of the most common applications for 3D printing using polymeric materials is producing dental models. There are different types of 3D printers depending on the technology used [9,10]. The American Society for Testing and Materials (ASTM) divides the available 3D printing technologies into seven categories, ISO/ASTM 52,900: 2015 1 3 [11,12], three of which are the most popular for generating dental models: stereolithography (SLA), material jetting (Multijet) and material extrusion or fused deposition modelling (FDM). The SLA category includes digital light processing (DLP). SLA and DLP have similarities since the objects are built layer by layer by immersing a build platform in a resin tank containing light-cured liquid resin [13]. The key difference between these two technologies is the type of light source: SLA uses an ultraviolet (UV) laser light to draw a pattern of a cross-section of the 3D object [14,15], and DLP uses a digital light projector screen to project the entire cross-section of the 3D object at once [16]. Multijet or material jet technology uses materials extruded from nozzles or photopolymers jetted over the workspace, and then the object is polymerized with a UV light source [9,13]. FDM technology builds parts layer-by-layer from the bottom up by heating and extruding a thermoplastic filament from a printing nozzle. The nozzle repeats the extruding and melting layer by layer until the object is complete [17,18]. The industrial 3D printers that are used in the dental field use Multijet, whereas the dental desktop 3D printers available use SLA or DLP technology. The scientific literature in the dental field mainly analyses printers specifically designed for dental use. These dental 3D printers are smaller in terms of volume and cheaper due to their simplified building technology and lower resolution and velocity than industrial 3D printers.
In addition to the printing technology, many other factors can influence the results of the printed model, such as the type of material, layer thickness, depth of cure, build orientation, platform position, amount of support structures and postprocessing procedure [19]. Therefore, the accuracy of a printed model is influenced by many factors. According to the ISO, accuracy consists of two parameters: trueness and precision. (ISO 5725-1: 1994, ISO 12836: 2015 [20,21]. The trueness of a 3D printer is described as the deviation of the printed object from its actual dimensions, and the precision of a 3D printer is the deviation between repeated prints [22][23][24]. High trueness describes the proximity of the original dimensions of the measured object, and high precision defines a 3D printer´s ability to manufacture the same product with the same dimensions in repetitive prints [25].
To date, the number of studies related to the accuracy of 3D-printed working models is limited, and no differences between industrial or dental desktop printers are normally considered. Therefore, the aim of this study was to evaluate the accuracy, in terms of precision and trueness, of the physical models obtained after digitization with an intraoral scanner of the maxillary arch of patients using different 3D printing media.
The proposed null hypothesis was that there would be no statistically significant differences in terms of accuracy, expressed as precision and trueness, of the physical models obtained after digitization with an intraoral scanner of the full-arch of patients using different 3D printing technologies, both industrial and in office dental desktop printers.
Materials and methods
The study protocol was approved by the Ethics Committee of the Hospital Clinic San Carlos in Madrid (C.P. AVINENT -C.I. 21/484-E) and followed the ethical principles established in the Declaration of Helsinki. A total of 15 patients with 15 Biomimetic Ocean IC single implants (Avinent) gave their informed consent to use their models for the in vitro study. Subsequently, a digital impression with the Trios 3 intraoral scanner (3Shape) and the corresponding scanbody Avinent IC (ref. 2801, Avinent) of the implant was obtained from each patient. Digital impressions were obtained following the manufacturer's instructions and were performed by the same operator (J.V.), starting with posterior occlusal from distal to mesial, making vestibule-palatine movements in the anterior area, following the palatal or lingual zone, and finally going through the vestibular part. The operator used an OptraGate (Ivoclar Vivadent) for retraction of the lips and avoided any direct impact of the equipment light during the digital impression with the intraoral scanner.
3D impression of the study samples
In this in vitro study, the industrial 3D printers with Multijet technology were the 3DS Projet MJP2500 (3DS group) and Objet30 OrthoDesk (Obj group). The dental desktop 3D printers were NextDent 5100 (ND group) and Rapidshape D30 (RS group) with DLP technology and Formlabs Form 2 (FL group) with SLA technology ( Table 1).
The digital impressions were sent to the Avinent CAD/ CAM Centre (Barcelona, Spain), where the split cast of the digital impression prior to 3D printing was designed with Model Builder software (vs. 2019). The 3D nesting programs recommended by the manufacturer of each study group were used following the protocol for the model printing (3D sprint basic in the 3DS group, Objet studio in the Obj group, 3D sprint basic in the ND group, Preform in the FL group and Netfabb Professional in the RS group). The models were printed with the dental model resin and layer thickness recommended for each 3D printer workflow ( Table 1). All of the models were hollow and placed horizontally with a 0° inclination to the platform. The total sample size was 225 printed models, 45 models per study group obtained from printing the patient's digital models 3 times with each printer.
The postprocessing protocol was the same in the ND, RS and FL groups, where the models were cleaned with C3H8O and air-dried for 30 min. In the 3DS group, the models were cleaned with pressurized water, and in the Obj group, they were cleaned with steam, oil and pressurized water. The curing times were between 20 and 60 min at 60 °C following the manufacturer's indications.
Analysis and comparison of the study samples
The 225 printed models were digitized with the same extraoral scanner as the RM of the patients (3Shape Lab-Scan Model D2000) ( Fig. 1). Due to the known shrinkage and deformation of the resins used with 3D printing, the time of analysis and digitalization of the printed models was 10 days after the postprocessing protocol was finished. Subsequently, the digital files were analysed using Control X software (vs. 2018.1.0., Geomagic, 3D systems). The alignment and superposition of the models were performed in two phases: an initial alignment with volume recognition and in the second alignment with a best fit algorithm to obtain the maximum adjustment of the surfaces. One of the limitations of the best fit algorithms is that it tends to underestimate the real discrepancies found when searching for the maximum fit between the surfaces. The first comparison of the full-arch models and their global surface was made within a discrepancy of less than 1 mm and a measurement tolerance selected in ± 100 microns (µm). A second comparison selecting only the scanbody zone was performed to study the scanbody discrepancies with the 3D-printed surface using the same analysis parameters ( Table 2). The scanbody area selected for comparison was the entire cylinder volume, and in the case of the RM, the scanbody was screwed on the implant analogue prior of its digitization. Each of the 3D-printed models was compared with the RM of each patient to obtain the intergroup results and the trueness. The intragroup values analysed the precision of each study group, comparing the printed models of each study group. A colour scheme range was obtained where positive discrepancy values (yellow to red) depicted areas where the printed model was larger than the RM, and negative values (turquoise to blue) presented areas where the printed model was undersized.
Statistical analysis
Descriptive statistics (mean values, standard deviations, medians and 95% confidence intervals) of variables were calculated for each group using a statistical software program (SPSS version 22.00). The sample size was calculated with an effect size of 0.55 with a standard deviation (SD) of 0.035, an alpha error of 0.05 and a statistical power of 90%. The resulting sample size was at least 70 samples with 14 samples per group. Finally, our final sample size was 225 samples, 45 printed models per group with 3 printings of each 15-patient digital model. To assess the reliability data, the precision and trueness of the models were obtained by comparing the groups using the ANOVA test with the post hoc Tukey test and nonparametric analysis (median test) with a significance level of 95%. The median test was performed to analyse the external and internal mean discrepancies.
Results
Trueness and precision of the full-arch printed model of each study group (Fig. 2) According to the trueness of the printed model, the RMS one-way ANOVA test was statistically significant (F = 27.094; P < 0.01) ( Table 3 and Figs. 3 and 4). Although the RMS values have been used for the statistical evaluation, the linear mean values have also been reflected for analysis and comparison with other research groups. The post hoc Tukey test showed that the best trueness was obtained by the 3DS group, followed by ND, Obj, FL and RS.
The analysis of the precision of the printed models with one-way ANOVA was statistically significant (F = 23.125; P = 0.001) ( Table 4 and Fig. 5) when analysing the standard deviation of the root mean square (RMS). According to the post hoc Tukey test, the best precision of the printed models was obtained by the 3DS group, followed by ND, Obj, FL and RS.
Trueness and precision of the scanbody zone of each study group (Fig. 3) According to the trueness of the scanbody, the RMS oneway ANOVA test was significantly different (F = 48.258; P < 0.01) ( Table 5 and Fig. 6). Although the RMS values have been used for the statistical evaluation, the linear mean values have also been reflected for analysis and comparison with other research groups. The post hoc Tukey test showed that the best trueness in the scanbody zone was obtained by the 3DS group, followed by Obj, ND, FL and RS.
The analysis of the precision of the scanbody zone with the one-way ANOVA test was statistically significant (F = 47.305; P < 0.01) when analysing the standard Percentage of the STL model that is oversized from the RM Internal mean discrepancy (lower total %) Percentage of the STL model that is undersized from the RM (Table 6 and Fig. 7). The post hoc Tukey test showed that the best precision in the scanbody zone was obtained by the 3DS group, followed by Obj, ND, FL and RS.
Trueness and precision depending on the 3D printer type: industrial vs. dental desktop
The industrial printers are represented by the 3DS and Obj group with the Multijet technology and the dental desktops by the FL groups with SLA technology and the ND and RS groups with DLP technology. After the analysis of the trueness and precision of each study group, they were analysed by comparing their industrial or dental desktop design with ANOVA. The one-way ANOVA test was statistically significant (P ≤ 0.01) for all of the groups in terms of trueness (F = 27.155) and precision (F = 12.153) of the full arch model and in the scanbody zone (trueness F = 33.626 and precision F = 24.656). The Bonferroni post hoc test defined between which groups the 3DS and Obj groups presented statistically significant differences from the RS (P = 0.00) and FL (P = 0.01) groups. The RS group with all of the groups and the FL group presented statistically significant differences from all of the groups except for the ND group (P = 0.508). According to these results, the 3DS group presented better results, followed by Obj, ND, FL and RS. Multijet printing technology, which is normally used with industrial 3D printers, presented better results than the DLP and SLA technologies used in dental desktop 3D printers.
Analysis of the volume above or below the printed model
The percentage of the STL model that was above (OVER TOT. %) and below (LOWER TOT. %) the reference once the alignment was carried out was used to analyse the percentage of the printed model that was bigger or smaller than the
Discussion
According to the results of the present study, significant differences in terms of trueness and precision were found between industrial and dental desktop printers. The industrial printers used the Multijet technologies (3DS and Obj groups) and presented lower mean values for trueness and precision (P < 0.01) both in the complete-arch model and scanbody surface analysis. Therefore, the null hypothesis that there would be no statistically significant differences in terms of accuracy, expressed as precision and trueness, of the printed models obtained after digitization with an intraoral scanner of the maxillary arch of patients using different 3D printing media, including industrial or dental desktop printers, was rejected. The results were interpreted taking into consideration the RMS mean deviation values for the accuracy evaluation and its standard deviation for the precision evaluation according to the ISO 5725 standards [20]. This method is frequently used in the scientific literature on this topic [10,24,26]. This is the preferred method chosen for the accuracy evaluation as opposed to the average deviation values method, where positive and negative values in the arithmetic mean can neutralize each other and preclude any actual difference. The RMS formula squares them and therefore prevents the neutralization of the opposite signs.
There is great heterogeneity in the scientific literature about 3D printing, and we found it difficult to compare our results to previous studies. The reference scanners used, materials, master models, printing technologies and parameters varied. Analysing the trueness and precision of different 3D printers in full-arch impressions, Kim et al. presented data in concordance with our results, obtaining the best results in terms of precision and trueness of industrial Multijet technology (69 ± 18 μm and 86 ± 17 μm; P < 0.05) compared to dental desktop printers with DLP (74 ± 34 μm and 469 ± 49 μm) and SLA technology (176 ± 73 μm and 141 ± 35 μm) [10]. Emir and Ayyildiz in 2021 also obtained statistically significant differences in the precision of the Multijet group (30.4 μm) when compared with the SLA (37.6 μm) and DLP (43.6 μm) groups [24]. In contrast with our results, they reported the highest trueness in the DLP group (46.2 μm) rather than in the Multijet group (58.6 μm), P = 0.005. They used a master model digitally designed with cylinders instead of teeth. These simplified geometry characteristics are less challenging to reproduce than a natural dental arch [24]. The analysed results of the scanbody zone of our study showed lower RMS values and better accuracy and precision for all of the study groups and technologies, which could also be explained by its simplified geometry. Even so, it presented the best result with the Multijet technology groups.
In the dental desktop printers, the ones with SLA technology seemed to have higher trueness than the DLP technology for full arch measurements, as it involves a smaller layer thickness and laser point of curing; however, it had lower precision. The DLP technology uses a projector to cure the material layer by layer, reducing the error with repeated impressions. The best results obtained for the Multijet technology could be explained by the new resin cartridge used in each impression and the industrial volume characteristics of the printer [27]. In the SLA and DLP dental desktop printers, the nonpolymerized resin is stored in the printer's tank, and it was repeatedly used. Industrial printers and Multijet technology can print smaller layer thicknesses than SLA printers, resulting in smoother surfaces and greater detail [28]. Another parameter to consider is the build angle in each 3D printing workflow for different clinical applications, which could influence the dimensional accuracy of 3D-printed restorations [26,[29][30][31]. The horizontal nesting of the full-arch model is recommended in the 3D printing workflow of the printers used in our study. Nevertheless, some studies have suggested an oblique angle of 30-45° to print the models, as the build angle and layer height presented statistically significant interactive effects on the accuracy of the printed models [26,[29][30][31]. Another parameter that should be considered in the protocols is the time of analysis, as some studies achieved a lower trueness in models when they were analysed 3 or 4 weeks after printing, suggesting a dimensional contraction of the resin over time [32,33]. There is a lack of information about this topic in the scientific literature, and more studies are needed about the influence of different parameters in the different 3D printing technologies.
Some authors concluded that 3D-printed models showed the highest RMS mean values in the accuracy (trueness and precision) of the complete arch and the trueness of preparation, although they cannot yet completely replace conventional stone models. A systematic review performed by Etemad-Shahidi in 2020 analysed six DLP printers, five SLA printers and one Multijet printer [28]. All SLA and DLP printers consistently produced oversized 3D-printed models compared to the control and reported an error measurement of < 100 μm, demonstrating high trueness and clinically acceptable results [28]. We obtained similar results in the different groups when comparing the final volume of the printed models with the reference model. The studies that used orthodontic models had more relaxed thresholds for clinical acceptability (up to 500 μm) than those intended for prosthodontic applications (up to 200 μm) [28]. Accordingly, the choice of 3D printing technology should also be guided by its intended application.
As mentioned above, a standardised protocol for 3D printing of dental models is necessary to facilitate performance comparison involving all printing parameters, resins used, postprocessing protocol and time of assessment. In our study, we did not compare models printed with equal resolution, and we could not use equal layer thickness, x-y resolution or postprocessing due to the manufacturers and resin protocol followed, which could be a limitation. We selected 3D printers that are clinically applicable in the laboratories or industrial manufacturing centres as well as in the dental clinic due to their desktop format. The Multijet technology used in the industrial 3D printers implies bigger machines in volume and more expensive due to their building system, higher resolution and speed. We hope that the industry will research in this field in order to improve the technology in an affordable way that could be applied as a desktop printer and used in the dental field among others. This technological advance can also come with the current SLA and DLP desktop printers used in dentistry, improving their resolution and manufacturing properties.
To obtain the digital models used in the comparisons, both reference model and of the printed models, a state-ofthe-art extraoral scanner has been used instead of a palpation CMM-type system. Although CMM-type palpation systems are the gold standard for calculating volumes of objects, these industrial systems were difficult to use with such a large sample size and with real patient models, since they use standard size probes that do not adapt correctly to all encountered surfaces. For this reason, the same extraoral scanner has been used in all the groups. The possible bias resulting from the measurement method should be the same in all the groups.
Conclusions
Within the limitations of this study, there were statistically significant differences in terms of accuracy, trueness and precision, of the full-arch models of patients using five different 3D printers, both industrial and dental desktop printers. Multijet printing technology, which is normally used with industrial 3D printers, presented better results than the DLP and SLA technologies used in dental desktop 3D printers. A standardized protocol for 3D printing of dental models is necessary to facilitate performance comparison involving all printing parameters, the material used, the postprocessing protocol and the time of assessment. | 5,303.2 | 2022-12-03T00:00:00.000 | [
"Materials Science",
"Medicine"
] |
Neural pathways of attitudes toward foreign languages predict academic performance
Learning attitude is thought to impact students’ academic achievement and success, but the underlying neurocognitive mechanisms of learning attitudes remain unclear. The purpose of the present study was to investigate the neural markers linked to attitudes toward foreign languages and how they contribute to foreign-language performance. Forty-one Chinese speakers who hold differentiated foreign language (English) attitudes were asked to complete an English semantic judgment task during a functional magnetic resonance imaging (fMRI) experiment. Multimethod brain imaging analyses showed that, compared with the positive attitude group (PAG), the negative attitude group (NAG) showed increased brain activation in the left STG and functional connectivity between the left STG and the right precentral gyrus (PCG), as well as changed functional segregation and integration of brain networks under the English reading task, after controlling for English reading scores. Mediation analysis further revealed that left STG activity and STG-PCG connectivity mediated the relationships between English attitudes and English reading performance. Taken together, these findings suggest that objective neural markers related to subjective foreign language attitudes (FLAs) exist and that attitude-related neural pathways play important roles in determining students’ academic performance. Our findings provide new insights into the neurobiological mechanisms by which attitudes regulate academic performance.
Introduction
Attitude is generally defined as a person's evaluation toward a(n) entity, object, target, or subject matter on a negative to positive (or favorable to unfavorable) continuum (Gjicali and Lipnevich, 2021), and it is a critical factor in predicting individual academic achievement (Credé and Kuncel, 2008). Appropriate attitudes are widely believed to maximize ability and consequently optimize results (Gardner, 1985;Anderman and Wolters, 2006;Oroujlou and Vahedi, 2011). At the behavioral level, evidence has shown that academic attitudes are closely related to academic success across domains, such as reading, math, and science (Masgoret and Gardner, 2003;Chen et al., 2018;Demir-Lira et al., 2019;Gjicali and Lipnevich, 2021). Moreover, a positive attitude is usually associated with good academic performance, whereas a negative attitude often correlates with poor academic outcomes (Masgoret and Gardner, 2003;Demir-Lira et al., 2019;Gjicali and Lipnevich, 2021). For foreign language (or second language, L2) learning, learners' attitudes also play important roles. Accumulating evidence from cross-sectional studies shows that learners' attitudes toward foreign languages are closely related to individual foreign language proficiency, achievement, and other performance (Merisuo-Storm, 2007;Oroujlou and Vahedi, 2011). Importantly, a meta-analysis involving 10,489 individuals demonstrated a significant positive correlation between attitudes toward language learning and second language achievement (Masgoret and Gardner, 2003), and evidence from longitudinal studies further confirmed that positive foreign language attitude (FLA) accounts for the most variance in L2 reading comprehension (Kozaki and Ross, 2011;Smith et al., 2017) and the growth of oral proficiency (HernÁNdez, 2010). More importantly, studies of various age groups (e.g., school-aged children and adults) and sociocultural backgrounds (e.g., Western culture and Eastern culture) support this stable correlation between FLA and academic performance (Masgoret and Gardner, 2003), irrespective of the script of the target language (alphabetic or graphic). That is, the closed relationship between FLA and academic performance is age-and culture-independent.
Explanations for these behavioral findings vary. For example, Merisuo-Storm (2007) argued that negative attitudes toward language learning can reduce learners' motivation and harm language learning, whereas positive attitudes can do the opposite. Similarly, Oroujlou and Vahedi (2011) supposed that students hold general positive attitudes and beliefs that are reflected in positive emotions in learning and greater persistence, whereas the negative attitudes accompanied by passive feelings inhibit students' interest and determination to perceive knowledge (Oroujlou and Vahedi, 2011).
However, these explanations might simplify the relationships between attitudes and behavior. First, attitude is a psychological tendency that is expressed by evaluating a particular entity with some degree of favor or disfavor (Eagly and Chaiken, 1993), and it includes a cognitive component (learners' evaluative beliefs), an affective component (learners' feelings and emotions regarding the object to be learned), and a conative component (learners' action readiness and behavioral intentions; Fishbein et al., 1977;Sardegna et al., 2018). Second, attitude often intermixes or interacts with other psychological constructs, such as belief (self-efficacy), emotion (anxiety and enjoyment), and motivation (Masgoret and Gardner, 2003;Oroujlou and Vahedi, 2011;Saito et al., 2018;Sardegna et al., 2018). Third, the roles of attitude in regulating attainment might be antecedent, outcome, and mediating or moderating variable(s) (Asakawa and Oller, 1977). In this sense, clarifying the potential interaction mechanisms between FLA and L2 performance purely based on behavioral studies is difficult.
Crucially, despite decades of behavioral studies, the underlying neural pathways that can explain the effects of learning attitudes on learning performance have yet to be identified. To our knowledge, only three studies in the domain of mathematics have explored the neurocognitive mechanisms of math attitudes to date (Chen et al., 2018;Demir-Lira et al., 2019;Suarez-Pellicioni et al., 2021).
In a pioneering study related to the neurocognitive mechanisms of math attitude, Chen et al. (2018) investigated the neural mechanisms underlying the link between positive attitude and academic achievement in 6-11-year-old children who solved single-digit additions. Specifically, they tested competing hypotheses regarding the differential roles of affective-motivational and learning-memory systems and found that a positive attitude was associated with increased hippocampal learningmemory system engagement, but it was not associated with an enhanced response in the amygdala and ventral striatum. Notably, the increased hippocampal response during numerical tasks observed in their study mediated the relationship between positive attitude and efficient problem solving, leading to academic success in children.
In a second study focused on math attitudes, Demir-Lira et al. (2019) investigated the effects of the interaction between math skill and math attitudes on the neurocognitive basis of arithmetic processing (single-digit multiplication) in 8-15-year-old children. They observed that positive math attitudes were correlated with less activation in the left IFG. Moreover, they found that the relationship between math attitudes and the neural basis of multiplication varied depending on math skill. Positive math attitudes were associated with a greater activation of the left IFG only among children with lower math skills. They interpreted the greater left IFG activation as reflecting effort invested in problem solving.
In a third study of math attitudes, Suarez-Pellicioni et al. (2021) longitudinally followed some of the participants in Demir-Lira et al. (2019) study to examine the neurocognitive mechanisms underlying math attitudes and math improvement. They found that for improvers, more positive math attitudes were related to greater left IFG activation, but this effect was not identified in nonimprovers. They proposed that greater left IFG activation was associated with the investment of effort and represented the neurocognitive mechanisms by which positive math attitudes lead to improvement in multiplication skill over time. Taken together, these findings suggest that learning attitudes might function by modulating the activation of domain-general learning-memory systems or effort-related brain regions during mathematical processing. Although these studies of math attitudes provide some insights for understanding the neurocognitive mechanisms of academic attitudes, no study has directly investigated the neural basis related to foreign language attitudes. Unlike math attitudes, attitudes toward foreign language might be more complex and are related to a learner's preferences for the subject (foreign language or L2) or the associated culture (Wright, 2006;Sakuragi, 2008).
The current study aimed to examine the underlying neural markers and pathways of FLA and how they contribute to language performance during a foreign language (English) reading task. To investigate these questions, we used functional magnetic resonance imaging (fMRI) to study a sample of Chinese college students who learned English as a foreign language (EFL) when they performed an English semantic judgment task. It is well known that both L1 and L2 (foreign language) reading recruited the dorsal and ventral networks (Oliver et al., 2017;Verhoeven et al., 2019). The dorsal network includes the parietal lobe, superior temporal gyrus (STG), and inferior frontal gyrus (IFG), and the ventral one includes the occipitaltemporal (vOT) and anterior IFG regions. The former is thought to subserve phonological processing, and the latter supports mapping of orthographic-lexical stimuli onto semantic representations (Oliver et al., 2017). To explore neural markers of FLA, we first applied brain activation and seed-based functional connectivity analyses to investigate differences between students with positive and negative FLA after controlling for behavioral performance. We then further employed a complex brain network analysis based on graph theory to characterize topological differences between the two groups Sporns, 2009, 2012). If potential neural markers related to FLA were identified, we expected to observe differences in brain activation and functional connectivity between the two groups. At the wholebrain network level, we also expected that positive attitudes might enhance brain network efficiency during foreign language processing. To examine the potential neural pathways by which FLA contribute to language performance, we further conducted a mediation analysis to identify whether brain activation and functional connectivity mediate the relationship between attitudes and foreign language performance. Previous work on math attitudes demonstrated that the effects between positive math attitudes and math achievement are mediated by memory strategy and greater hippocampal activation (Chen et al., 2018). Therefore, we expected that the brain's activation and functional connectivity also constitute the link between attitudes and foreign language achievement. Exploring the neural substrates of FLA can not only help us determine attitude-related effects in the specific domain but also expand our understanding of the domaingeneral or domain-specific mechanisms of learning attitudes This exploration will provide important insights for understanding the fundamental mechanisms of attitudes toward foreign languages and their association with language achievement and other performances, which might help us develop proper interventions to increase the efficiency of foreign language teaching and inspire learners' potentials.
Participants
Forty-one college students (20 females, average age = 18.46 ± 0.75 years) were enrolled in the study. All participants were native speakers of Chinese and began to learn English as a second language starting in the first grade of primary school (age of acquisition = 6.02 ± 1.59 years). They all came from Beijing and had highly similar second language education backgrounds. All participants were healthy, right-handed and had normal or corrected-to-normal vision (Yuan et al., 2021;Li et al., 2023). All participants signed an informed consent form before the experiment, which was approved by the Institutional Review Board of Beijing Normal University.
Behavioral tests 2.2.1. Foreign language attitudes
To qualify the participants' attitudes toward foreign languages, we used the Attitudes Toward English Learning Scale (ATELS; Pae and Shin, 2011), an eight-item self-assessment questionnaire aimed to measure learners' attitudes toward a foreign language (e.g., I truly enjoy learning English). The participants were asked to evaluate how much they agreed or disagreed with each item using a five-point scale (from 1-strongly disagree to 5-strongly agree). The Cronbach's alpha of the scale is 0.87. The total score of the ATELS was regarded as an indicator of learners' FLA, and all participants were divided into the positive FLA group and negative group based on the median ATELS. The two groups did not differ significantly in age, sex, IQ, age of acquisition, or L1 proficiency (see Table 1).
Reading fluency test
English reading performance was assessed using the reading fluency test (RFT) of the Woodcock Johnson-III (Woodcock et al., 2001), which has been widely used to probe English reading fluency and ability in previous studies Francis et al., 2006). The test consists of 98 items that evaluate learners' general English reading ability, especially reading fluency (e.g., you can eat an apple). The participants were asked to judge whether the meaning of each English sentence was reasonable, and the total RFT score was used as the indicator of a learner's reading fluency (see Table 1 for more details on demographics and behavioral performances).
fMRI experimental procedure
The participants performed an English semantic judgment task in the scanner, in which they were asked to decide whether two visually presented English words were semantically related or not. All words were 4-6 letters long (mean = 4.4). An arrow direction judgment task was used as a control task, in which the participants were asked to judge whether the arrow was pointing upward or downward, and both the experimental task and the control task were successfully used in a previous study (Tan et al., 2011). A block design was used, in which the semantic task was alternated with the baseline task (arrow direction judgment). Each experimental block consisted of 12 trials, whereas each baseline block consisted of eight trials. In each trial, stimuli (word pairs or an arrow) in white were displayed on a black background for 1,500 ms, followed by a 500 ms fixation interval. The participants were instructed to press a yes button for semantically related word pairs (or an upward arrow) using their right index finger or press a no button with the right middle finger for semantically unrelated word pairs (or a downward arrow). Half of the word pairs were semantically related, and half were not. The participants were asked to perform the task as quickly and accurately as possible.
MRI acquisition
All images were acquired using a 3 T Siemens Trio Scanner at Beijing Normal University. An echo planar imaging (EPI) sequence was used for functional imaging with the following parameters: TR = 2,500 ms, TE = 30 ms, flip angle = 90°, and scan order = interleaved. Matrix size = 64 × 64, slice thickness = 3 mm, and voxel size = 3 mm × 3 mm × 3 mm. Additionally, a high-resolution T1-weighted 3D image (MPRAGE) was acquired with the following parameters: TR = 2,530 ms, TE = 3.39 ms, flip = 7°, matrix size = 256 × 256, slice thickness = 1 mm, and voxel size = 1 mm × 1 mm × 1 mm. Frontiers in Psychology 04 frontiersin.org 2.5. fMRI data analysis 2.5.1. Whole-brain activation analysis SPM 12 was used for image preprocessing and statistical analysis. 1 Functional images were first corrected for slice acquisition delays and realigned to the first image of the first run to correct for head movements. The images were further spatially realigned and coregistered to their corresponding anatomical images. The resultant images were then spatially normalized to the Montreal Neurological Institute (MNI) space. After normalization, all images were resampled into 3 mm × 3 mm × 3 mm voxel sizes and further spatially smoothed using a Gaussian kernel with 8 mm full width at half maximum (FWHM). An individual participant's activation t map was generated using the general linear model, in which time series were convolved with the canonical hemodynamic response function and were highpass-filtered at 128 s.
The individual contrast images of the semantic judgment minus arrow judgment were computed as a first-level analysis, and the contrast maps were then subjected to a second-level analysis to compare activation differences between the positive and negative groups by performing two-sample t tests. An FWE-corrected clusterlevel threshold of p = 0.05 (defined using a voxel-level threshold of p = 0.001) was applied to all whole-brain statistical maps to assess brain activations.
Functional connectivity analysis
We performed seed-to-voxel analysis to identify differences in the functional connectivity among the clusters identified through the activation analysis and other regions between the positive FLA group and the negative group. To this end, seed ROIs were created using the clusters that were significantly related to FLA. Using the DPABI toolbox v4.2 (http://rfmri.org/dpabi; Yan et al., 2016), we first averaged the time series of all voxels in each seed. We then temporally correlated the seed ROIs and all the other voxels in the brain, and participantlevel correlation maps were obtained. For standardization purposes, the correlation maps were normalized to z maps. At the group level, we conducted a two-sample t test between group z maps to detect the association between FC and FLA, with English reading score as a controlling variable. Functional connectivity maps survived a corrected cluster-level threshold of p < 0.001 (single voxel p < 0.001, and a minimum cluster size of 50 voxels) using the Gaussian random field approach (Worsley et al., 1992).
Graph theoretical analysis 2.5.3.1. Network construction
The graph theoretical analysis was performed using the GRETNA toolbox (graph theoretical network analysis: http://www.nitrc.org/ projects/gretna; Wang et al., 2015). Based on the automated anatomical labeling (AAL) atlas with 90 ROIs, we extracted the time series for each AAL ROI by calculating the mean (across voxels) signal for each time point, and a 90 × 90 Pearson correlation matrix was created for each participant for the semantic judgment condition. We constructed binary undirected functional networks using a sparsity threshold 1 http://www.fil.ion.ucl.ac.uk/spm (5% ≤ sparsity ≤50%, interval = 5%) to comprehensively estimate topological properties covering a wide range of sparsity and remove spurious edges as much as possible.
Network properties and group comparisons
We calculated graph properties characterizing the global-level network organization for each participant, including the following: (1) functional segregation, which is the ability for specialized processing within densely interconnected groups of brain regions, including the metrics of local efficiency and clustering coefficient Sporns, 2009, 2012); (2) functional integration, which refers to the capacity of the network to rapidly combine specialized information from distributed brain regions and includes the metrics of characteristic path length and global efficiency Sporns, 2009, 2012); and (3) small-worldness, which reflects an optimal balance of functional integration and segregation Sporns, 2009, 2012). To examine the group differences of all the network metrics mentioned above, ANCOVA was used for betweensubject comparisons and regressed-out covariates of English reading fluency. To correct for multiple comparisons, we used a Bonferroni corrected threshold at a significance level of 0.05.
Brain-behavior mediation analysis
For brain activation and functional connectivity showing a significant association with FLA, we used mediation analysis to examine whether neural correlates of FLA mediate the association between behavioral FLA and English reading performance. Mediation analysis was conducted using the PROCESS macro in SPSS (Hayes, 2013).
During mediation analysis, FLA and English reading fluency were defined as the independent (predictor) variable and dependent (outcome) variable, respectively. We defined the mediator variables based on the brain statistical maps resulting from the group differences in activation and seed-based connectivity analysis described above. The significance of the indirect effect was determined using a bootstrapping method with 5,000 iterations. If a 95% confidence interval (CI) did not contain zero, then the indirect effect was significant (Preacher and Kelley, 2011;Hayes, 2013).
Behavioral results: FLA predicted foreign language performance
To reveal the relationships between FLA and English reading performance, we correlated individuals' FLAs with English reading scores. The results showed a significant positive correlation between FLA and English reading proficiency (fluency; r = 0.34, p < 0.001). Critically, the association between FLA and language performance remained significant after adjusting for age and IQ in a multiple regression analysis.
FLA-related activation differences
First, we performed a univariate analysis to investigate group differences during English semantic decisions. After controlling for Frontiers in Psychology 05 frontiersin.org English reading scores, the two-sample t test of the whole-brain analysis revealed that, compared with the positive attitude group (PAG), the negative attitude group (NAG) showed increased activation in the left STG (BA 48, MNI: −54, −21, 6; p < 0.05, clusterwise FWE corrected; cluster size = 40 voxels). Relative to NAG, we failed to find stronger brain activation in the PAG (Figure 1).
FLA-related functional connectivity differences
Since a significant between-group activity difference was identified in the left STG, the left STG was taken as a seed region to compare the seed-to-voxel functional connectivity differences between PAG and NAG, with English reading scores as the nuisance covariate (p < 0.001, GRF corrected). The results showed that the NAG exhibited significantly stronger functional connectivity between the left STG and right precentral gyrus (PCG) than the PAG. For the opposite comparison, we did not observe any difference in functional connectivity between the two groups ( Figure 2).
FLA-related topological properties
To explore FLA-related topological properties, we applied graph theoretical analysis to test whether topological properties during the English semantic task can distinguish the PAG from the NAG. The results showed significant group differences in network integration and segregation at the sparsity-integrated level. Specifically, the network engaged by the positive group exhibited significantly higher global efficiency (for 0.05 < T < 0.15 and 0.4 < T < 0.5) but lower characteristic path length (for 0.05 < T < 0.2 and 0.4 < T < 0.5) and clustering coefficiency (for 0.5 < T < 0.5) than that engaged by the negative group. For the network local efficiencies and small-worldness, we failed to find any difference between the two groups (see Figure 3 for a summary of these findings).
Brain-behavior relationships
To reveal the brain-behavior relationship, we applied mediation analysis to examine whether the relationships between FLA and foreign language performance could be explained by attitude-related brain activity and functional connectivity.
At the activity level, adding activation in the left STG as a mediator showed that left STG activation significantly and indirectly mediated the relationship between FLA and foreign language reading performance (see Figure 4A; indirect effect = −0.60, 95% CI = [−1.18, −0.12], p < 0.05).
At the connectivity level, adding FC of the left STG and right PCG as a mediator showed that the association between FLA and reading performance was mediated by FC (see Figure 4B; indirect effect = −0.69, 95% CI = [−1.43, −0.16], p < 0.05). Taken together, our findings indicated that the FLA influenced foreign language performance through task-related brain activity and connectivity.
Discussion
In the present study, we first used task-based fMRI to investigate the neurobiological correlates of FLA from brain activation, functional connectivity, and large-scale brain network levels and the roles of FLA-related brain activity and connectivity in connecting FLA and foreign language achievement. Overall, our study identified the neural markers of the FLA and the neural paths of the FLA that influence foreign language learning and achievement.
Brain activity markers differentiating PAG from NAG
At the whole-brain level, we found that NAG showed enhanced activation in the left STG in the English semantic judgment task compared to the PAG. Brain activation differences between the PAG and NAG in the English semantic judgment task. After controlling for English reading fluency, increased activation in the left STG was observed when comparing the NAG with the PAG.
Frontiers in Psychology 06 frontiersin.org
The left STG is generally considered a core brain region in language function, and it is primarily involved in auditory processing and speech comprehension (Gernsbacher and Kaschak, 2003;Martin, 2003). Importantly, the left STG and adjacent gyral regions have repeatedly been related to audiovisual print-speech integration, especially grapho-phonological conversion (Blau et al., 2009;Kronschnabel et al., 2014;Ye et al., 2017). In addition, previous studies found that this area played important roles in integrating phonological decoding and semantic information to facilitate semantic access in the process of English word reading (Hu et al., 2010). For example, increased left STG activation has been observed when bilingual participants performed English semantic tasks (Tan et al., 2005). In other words, the left STG plays important roles in both audiovisual print-speech integration and phonology-semantics integration. More importantly, as an important region of the core language system, the activation in the left STG was supramodal or modality independent and showed shared cortical activation across spoken, written and signed languages in Dutch speakers, Chinese monolinguals, and Chinese speech-sign bilinguals (Liu et al., 2020).
Generally, brain systems that involve affect, motivation, learning, and memory have been hypothesized to underpin the influence of positive attitudes on academic learning and achievement (Chen et al., 2018). Indeed, Chen et al. (2018) studied math attitudes by employing a single-digit-addition task and found that a positive attitude was associated with increased engagement of the MTL learning-memory system (bilateral hippocampus) but not the affective-motivational system (amygdala or ventral striatum).
In addition to the hippocampal memory system, previous studies on math attitudes also reported that math attitudes correlated with activation in the left IFG when the participants performed a singledigit multiplication task, but this attitude-related IFG activity was observed only for children with positive math attitude but low math skill, and they argued that IFG activity might reflect controlled effort and the retrieval of multiplication facts (Chen et al., 2018;Demir-Lira et al., 2019;Suarez-Pellicioni et al., 2021).
In our dataset, we only observed attitude-related activation in the NAG, and this finding is generally consistent with Demir-Lira's results.
In their study, they observed that positive attitudes toward math correlated with less activation in the left IFG. With respect to activity intensity (e.g., increased or decreased), the neural function of academic attitudes seems to be partly domain independent. Since the current study employed different tasks from previous studies (e.g., Chen et al., 2018), it is likely that the different observations are process-driven instead of domain-driven. It is worth mentioning that these two driven might be intermixed and hard to separate from each other. Based on evidence from math attitudes, the larger involvement of the left STG might indicate that negative learners require more effort to recruit phonological processing and semantic integration during English word reading and facilitate task performance.
Functional connectivity markers differentiating PAG from NAG
In addition to differentiating the PAG from the NAG, the activity of the left STG also differed in terms of functional connectivity (FC). Specifically, the seed-based correlation analysis revealed that the FC between the left STG and right precentral gyrus (PCG) was stronger in the negative group than in the positive group. The left PCG has been well documented to be implicated in many functional MRI studies of language and reading (Dehaene et al., 2001;Yen et al., 2019), and some studies related the right PCG to higher-order cognitive mechanisms, such as language production and comprehension (Dickens et al., 2019). Specifically, the right PCG was activated during phonetic planning and concrete semantic representations (Papeo et al., 2015), and it played an important role in sound-motor integration during word generation (Alario et al., 2006). In addition, the right PCG has been reported to be one of the crucial regions for bilingual language control (Luk et al., 2012), and connectome analysis found that early Japanese-English bilinguals showed dense connectivity between the right putamen and PCG compared to Japanese monolinguals and late bilinguals (Mitsuhashi et al., 2020).
Because the left STG is also related to a variety of language processing, the reinforced STG-PCG connectivity in the negative Seed-based functional connectivity differences between the PAG and NAG in the English semantic judgment task. After controlling for English reading fluency, increased FC between the left STG and right PCG was observed when comparing the NAG with the PAG.
Frontiers in Psychology 07 frontiersin.org learners may reflect increased investment in reading-related cognitive resources. Furthermore, the negative learners exhibited reinforced FC between the left and right hemispheres to improve their performance during semantic decision-making. Indeed, a previous study supported this possibility and showed that interhemispheric functional brain connectivity could predict new language learning success in adults (Sander et al., 2022). In short, although the role(s) of the right PCG in foreign language attitudes remains unclear, we speculate that the FC between the left STG and right PCG plays a critical role in maintaining reading performance, especially for negative learners.
The topological properties of the large-size brain network differentiating PAG from NAG
To reveal brain network properties that differentiate the PAG from the NAG, we compared the network topology between the positive and negative learners using graph theory analysis.
The results showed that the positive group displayed significantly higher global efficiency (Eg) and shorter characteristic path length (Lp) in the whole-brain network than the negative group, suggesting that positive learners have more efficient and Between-group comparisons in graph properties of functional networks. (A) functional integration: global efficiency (E glob ) and characteristic path length (L p ), (B) functional segregation: clustering coefficiency (C p ) and local efficiency (E loc ), and (C) small-worldness. Inset maps (with mean and standard error) show significant group effects of the area under the curve (AUC) in E glob , L p , and C p , p < 0.05.
Frontiers in Psychology 08 frontiersin.org extensive neural pathways to bring them an advantage in network integration capability (Achard and Bullmore, 2007;Rubinov and Sporns, 2010). In contrast to the PAG, the NAG showed an increased clustering coefficient (Cp), which indicates a greater tendency for functional segregation and the formation of clustered connections (Bullmore and Sporns, 2012). Although the relevance between network topology properties and academic attitudes has not yet been established, evidence from other domains showed that a brain network with intensifying integration and weakening segregation was associated with cognitive advantages. For example, compared with L2 reading, L1 reading recruited a more globally efficient but less clustered functional network topology, which represents more optimized functional network organization during L1 processing (Feng et al., 2015), and individuals with more active moods and less anxiety have larger global efficiency and shorter path length during tasks (Park et al., 2014(Park et al., , 2016. In addition, evidence from short-term language training suggested that less segregation (smaller clustering coefficient) was associated with successful language learning (Sheppard et al., 2012;Yang et al., 2015), and children with L2 reading impairment exhibited higher local network efficiency (Liu et al., 2016). In the context of this study, English semantic judgment is a complex cognitive process that requires the interactive collaboration of several brain networks involved in orthographic, phonological, and semantic processing (Xu et al., 2005;Binder et al., 2009;Friederici et al., 2009;Price, 2012). Therefore, positive learners likely could easily and flexibly use long-range neural pathways to integrate whole-brain resources, and this coherent and cost-efficient network organization could help them more efficiently complete the foreign language task. Notably, we could not infer causal relationships between FLA and brain network properties in the present cross-sectional study. In this sense, future studies should explore this issue based on longitudinal designs.
The neural pathways connecting FLA with academic performance
Behaviorally, stable associations between FLA and foreign language achievement have been repeatedly reported in previous investigations (Masgoret and Gardner, 2003;Zhang et al., 2020;Papi and Khajavy, 2021). What are the potential neural pathways underlying these associations? To answer this question, we performed brain-behavior mediation analysis. Our results showed the critical roles of left STG activation and STG-PCG functional connectivity in mediating the relationship between FLA and foreign language performance, and these findings provide important insights for understanding the roles of FLA-related brain activation and FC in foreign language processing and learning. Since the left STG and right PCG are important regions for lexical-semantic processing (Tan et al., 2005;Hart et al., 2012), and the left STG plays a hub-like role in successful second language learning (Yang et al., 2015), we speculate that negative attitudes related to STG hyperactivation and intensive STG-PCG connectivity might reflect a higher effort or requirement for lexical-semantic processing in the NAG to compensate for the global inefficiency of the brain network and further promote in-scanner foreign language performance, and the results from mediation analysis supported this possibility. Although negative correlations were identified between FLA and left STG activation and STG-PCG connectivity, positive correlations were revealed between reading performance and brain activation as well as functional connectivity. These findings suggest that although we failed to find attitude-specific activity in the learning-memory system (e.g., hippocampus) or emotionmotivation system (e.g., amygdala or ventral striatum), academic attitudes might exert their effect through task-related brain regions (e.g., STG) or networks (e.g., STP-PCG connectivity). In summary, our study indicated that left STG activity and STG-PCG connectivity might be potential neural pathways that explain the impact of FLA on foreign language achievement. More specifically, the FLA might affect STG activity and functional connectivity and further influence individual academic performance.
It is worth mentioning that the sample size of the present study is relatively small, which may increase the probability of false positive effects (Ioannidis, 2005) and lead to low power (Ioannidis, 2005;Bossier et al., 2020). Future studies with a larger sample size or longitudinal design could deepen our understanding of the mechanism of FLA. The potential pathways of FLA-related neural markers that mediate FLA and foreign language performance. (A) Pathways of left STG activity that mediate FLA and foreign language performance (reading fluency) and (B) pathways of FC of STG-PCG that mediate FLA and foreign language performance (reading fluency). FC, functional connectivity; PCG, precentral gyrus. *p < 0.05, **p < 0.01, ***p < 0.001.
Conclusion
In conclusion, the current study demonstrated, for the first time, that subjective academic attitudes have objective neural signatures and can reshape individuals' brain activities in the task state. The FLA is associated with changed activity of the left STG, FC of the STG-PCG, and the topological properties of the brain network during the English reading task. Since the STG and PCG play important roles in language and reading, these findings imply that FLA-related neural signatures might not rely on the learning-memory system or emotion-motivation system but depend on task-related brain regions or networks. Importantly, compared with existing studies of math attitudes, the neural signatures of academic attitudes seem to be domain specific. More importantly, academic attituderelated neural predictors underlie the potential pathways that contribute to individuals' foreign language performance.
Data availability statement
The raw data supporting the conclusions of this article will be made available by the authors, without undue reservation.
Ethics statement
The studies involving human participants were reviewed and approved by the Institutional Review Board of Beijing Normal University. The patients/participants provided their written informed consent to participate in this study.
Author contributions
YPW and DL designed the study. DL and XW analyzed the data, drew the figures, and wrote the manuscript. YPW checked and,revised and edited the manuscript. YZW, YC, and DL performed the experiments. All authors contributed to the article and approved the submitted version.
Funding
This study has been supported by the Scientific and Technological Innovation 2030 -the major project of the Brain Science and Brain-Inspired Intelligence Technology (2021ZD0200500).
Conflict of interest
The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.
Publisher's note
All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher. | 7,952 | 2023-07-26T00:00:00.000 | [
"Psychology",
"Linguistics"
] |
Analysis of Polycyclic Aromatic Hydrocarbons in Ambient Aerosols by Using One-Dimensional and Comprehensive Two-Dimensional Gas Chromatography Combined with Mass Spectrometric Method: A Comparative Study
Advanced separation technology paired with mass spectrometry is an ideal method for the analysis of atmospheric samples having complex chemical compositions. Due to the huge variety of both natural and anthropogenic sources of organic compounds, simultaneous quantification and identification of organic compounds in aerosol samples represents a demanding analytical challenge. In this regard, comprehensive two-dimensional gas chromatography with time-of-flight mass spectrometry (GC×GC-TOFMS) has become an effective analytical method. However, verification and validation approaches to quantify these analytes have not been critically evaluated. We compared the performance of gas chromatography with quadrupole mass spectrometry (GC-qMS) and GC×GC-TOFMS for quantitative analysis of eighteen target polycyclic aromatic hydrocarbons (PAHs). The quantitative obtained results such as limits of detection (LODs), limits of quantification (LOQs), and recoveries of target PAHs were approximately equivalent based on both analytical methods. Furthermore, a larger number of analytes were consistently identified from the aerosol samples by GC×GC-TOFMS compared to GC-qMS. Our findings suggest that GC×GC-TOFMS would be widely applicable to the atmospheric and related sciences with simultaneous target and nontarget analysis in a single run.
Introduction
Human health research associated with polycyclic aromatic hydrocarbons (PAHs) has raised concerns because certain PAHs are classified as probable human carcinogens [1][2][3][4] and have shown tumorigenic activity and endocrine disrupting activity in mammals [5]. e US EPA has included 16 of them in the list of priority pollutants and has established a maximum contaminant level of 0.2 μg/L for benzo [a]pyrene in drinking water [6]. In the European Union (EU), eight PAHs have been identified as priority hazardous substances in the field of water policy [7]. e EPA priority 16 PAHs and two additional PAHs are now being monitored by European agencies, and they have sought to quantify the individual concentrations of benzo [e] pyrene and perylene in environmental samples [6]. PAHs are found in ambient air in the gas phase and as sorbents to aerosols [8]. us, air monitoring of PAHs to quantify inhalation exposure and to identify other organic compounds is important for insight into photochemical reactions. e quantification and identification of organic compounds in air samples is an important feature of atmospheric chemistry and represents some demanding analytical challenges [9].
For these reasons, a key issue in current analytical methods is the ability to measure a large number of compounds with quantitative analysis for target analytes. Comprehensive two-dimensional gas chromatography (GC×GC) coupled with mass spectrometry (MS) can screen for nontarget compounds with fast identification of the compounds in an entire sample [10]. erefore, previous studies applied GC×GC-MS for the identification of numerous compounds present in air samples [11][12][13]. However, there are limitations on the validation of simultaneous quantification and identification of analytes in air samples. Correspondingly, a validation of simultaneous identification and quantification of PAHs and other compounds in air samples by GC×GC-MS is required. A TOF mass spectrometer was used to acquire sufficient data from a comprehensive two-dimensional chromatographic technique that generated multiple narrow peaks from the short secondary column [14,15]. Generally, GC coupled with quadrupole MS (GC-qMS) in the selected ion monitoring (SIM) mode has been used for quantitative analysis of PAHs in air samples because of its selective detection for specific target compounds [16,17]. However, a GC×GC-TOFMS validated method suitable for the quantification of target PAHs in an aerosol sample compared with GC-qMS in the SIM mode has not yet been reported. e aim of this study was to evaluate the effectiveness of GC×GC-TOFMS in the quantitative analysis of target PAHs as well as the fast identification of multiple compounds for aerosol samples. e validity of the quantitative results obtained by both GC×GC-TOFMS and GC-qMS in the SIM mode was demonstrated by several method performance parameters such as linearity, accuracy, and repeatability.
Air Sampling.
e total suspended particle (TSP) samples were collected at Asan Engineering Building, Ewha Womans University, Seoul, South Korea (37.56°N, 126.94°E, 20 m above ground level), with a PUF sampler (Tisch, TE-1000) on a quartz fiber filter (Quartz fiber filter, QFF, Ø10.16 cm, Whatman, UK). e sampling site is located in the mixed resident area, commercial area, forest area, and nearby roadside. A total of 67 filter samples were obtained during summer (August 12-30, 2013) and winter (January 27-February 16, 2014) and day (9 a.m.∼6 p.m.) and night (8 p.m.∼6 a.m.). Prior to sampling, the quartz fiber filters were baked for 8 h in an electric oven at 550°C to remove possible organic contaminants. e sampled filters were wrapped in aluminum foils and stored in a freezer at −20°C until analysis.
Chemicals.
All organic solvents were of GC grade and purchased from Burdick and Jackson (Phillipsburg, NJ, USA). Standard solutions of target PAHs (Table 1 for their full chemical names and information) except Per and BeP for quantitative analysis were purchased as a mixture at a concentration of 2000 µg/mL in dichloromethane from Supelco (Bellefonte, PA, USA). Per and BeP standards (>99%) were purchased from Aldrich (St. Louis, MI, USA), and a standard mixture of eighteen PAHs was prepared at a concentration of 1000 µg/mL. Deuterium-labeled internal standards of seven PAHs were purchased from Aldrich (St. Louis, MI, USA) and Chiron (Trondheim, Norway) and used for the spiking test as listed in Table 1. Working standard solutions (0.01∼10 µg/mL) were prepared and then stored at −20°C prior to use.
Preparation of Samples.
Air sampling filters were extracted with a mixture of dichloromethane and methanol (3 : 1, v/v) two times using an accelerated solvent extractor (ASE) (Dionex ASE-200) at 40°C and 1700 psi for 5 min. Prior to the extraction, seven deuterated internal standards (Nap-d8, Ace-d10, Phen-d10, Fla-d10, Chr-d12, Per-d12, and BghiPer-d12) were spiked in the filters to compensate for matrix effects during the extraction procedure. Extracts were blown down to 1 mL using a nitrogen evaporator Table 2.
GC-qMS and GC×GC-TOFMS for Characterization of Aerosol Samples.
In most studies, separation and quantification of PAHs in aerosol samples have been analyzed using a conventional GC-qMS [18]. Flame ionization detection (FID) has also been widely used for quantification as it features a higher response to PAHs which contain only carbon and hydrogen, while oxygenates and other species that contain heteroatoms tend to have a lower response factor [19]. However, this nonspecific detector may not distinguish inferences, which include a large fraction of aliphatic and aromatic compounds in aerosol samples from alkylated PAH homologues. e coupling of GC with MS is increasingly becoming the analytical tool of choice in this regard because of its superior selectivity and sensitivity. Among the most common analyzers including TOF [20], ion trap, and qMS [21,22], qMS is the most widely adopted technique for routine analysis of PAHs [23]. GC-qMS data acquisition takes advantages of both a full mass scan range (scan mode) and specific ion masses for target analytes (SIM mode). e sensitivity in the SIM mode is higher than that in the scan mode of GC-qMS due to the increased dwell time on each monitored ion for trace analysis in some matrices such as in atmospheric aerosols [24,25]. GC-TOFMS has a much faster spectral acquisition rate than GC-qMS does, which is up to 500 full mass scans per second [26]. Consequently, this system is able to widen the application of GC×GC techniques providing very narrow chromatographic peaks, typically 50∼600 ms at the baseline with sufficient density of data points per chromatographic peak [27]. Environmental samples are generally complex, often with more than hundreds of compounds containing structural isomers and homologues spread over a wide range of concentration and volatility. Accordingly, multidimensional separation is an advanced technique offering the possibility of greatly enhanced selectivity using different separation mechanisms for the analysis of complex environmental samples [28][29][30]. In this study, a set of columns DB-5×DB-17 ms was applied to increase the resolution and peak capacity. e fast scanning Pegasus 4D TOFMS system was combined to allow efficient processing of data acquisition, handling, peak detection, and deconvolution. In the one-dimensional column, a 30 m-long DB-5 ms (5% diphenyl/95% dimethyl polysiloxane) stationary phase was used to separate analytes based on volatility and combined with a 1.17 m-long DB-17 ms column (50% diphenyl/50% dimethyl polysiloxane) allowing relative polarity-based separation. Figure 1 shows GC×GC-TOFMS chromatograms of aerosol samples collected at day and night during winter in Seoul, South Korea. To compare the identification ability of GC×GC-TOFMS with GC-qMS, analysis with GC-qMS in the scan mode was performed. A comparison of the one-dimensional chromatograms of the same samples obtained by GC-qMS is shown in Figure 2. 2D chromatograms enable the visual classification of chemically related compounds into groups. It was rare to see that the early-eluting analytes have an extreme volatility in the chromatogram, as shown in Figure 2. Because of the large losses of these analytes during sample extraction and concentration, particle-associated semivolatile analytes were mainly detected and classified according to their aromatic and aliphatic hydrocarbon groups. Meanwhile, analytes from the GC-qMS chromatogram were separated based on their vapor pressures or boiling points. e GC×GC technique is rather well suited for group separations, and classifying compounds into chemical-related groups could be useful for source identification of atmospheric aerosols by means of the large amount of chemical data handling. e combined use with TOFMS provides rapid and reliable identification of analytes using their deconvoluted pure mass spectra. e major limitation of qMS is its limited scan rate; therefore, quantification and identification is seriously compromised because of the mass spectral skew due to the variations in ion abundances at different regions of a chromatographic peak [31,32]. e numbers of identified chromatographic peaks analyzed by GC-qMS using the same signal threshold setting from the aerosol samples collected at day and night were 35 and 64, respectively. In the case of results obtained by GC×GC-TOFMS, 251 and 297 peaks from the day-and night-time aerosol samples were, respectively, assigned by individual spectral deconvolution. As a result, phthalic anhydride and 1,2-naphthalic anhydride as the markers of secondary formation for gas-phase PAH reactions were identified in the aerosol sample, as shown in Figure 3. Since the products formed through photochemical reactions are often more toxic than their parent PAHs in atmosphere [17], significant efforts have been expended to identify the photochemical products with PAHs in the fields of atmospheric or environmental sciences. In the case of results obtained using GC-qMS, phthalic anhydride and 1,2-naphthalic anhydride were not detected in the same sample. Limitations of one-dimensional separation have been reported for these photochemical products and complex mixtures of the aerosol sample because of their diverse polarities in a single run [33,34]. Contrastively, two anhydrides associated with secondary organic aerosol formation were clearly separated and detected by GC×GC-TOFMS. erefore, it showed advantages for nontarget screening to identify molecular markers or chemical patterns more representative of the aerosol state observed in ambient air.
Validation of GC-qMS and GC×GC-TOFMS for Quantification of PAHs.
GC-qMS and GC×GC-TOFMS were tested individually in order to evaluate their analytical performances. e calibration linearity (regression coefficient, R 2 ) and relative response factor (RRF) are presented in Table 3. e RRF is the ratio between a signal produced by an individual native analyte and the corresponding isotopically labeled analogue of the analyte (as an internal standard). For calculating RRF, 2 ng of each target PAH and each corresponding deuterated internal standard was spiked, and the relative sensitivity in both the methods was compared. Despite the high-speed scanning performance of GC×GC-TOFMS, the RRFs obtained by this method were approximately equivalent to those obtained by GC-qMS. RRF expresses the sensitivity of a detector for a given substance relative to a standard substance [35,36].
us, it indicated that the sensitivity of GC×GC-TOFMS relative to target PAHs is comparable in quantitative analysis. Calibration curves were generated using the peak area for the 18 PAHs at seven concentrations ranging from 0.01 to 10 μg/mL. e linearity was assessed by calculating the regression equation and the correlation coefficient by the least squares method, as shown in Table 3. e R 2 values were greater than 0.999 for GC-qMS and 0.99 for GC×GC-TOFMS. Although data processing for quantification by GC×GC-TOFMS was derived from the combined peak areas Journal of Analytical Methods in Chemistry 5 for the slices of modulated peaks in contrast to production of the single measured peak by GC-qMS, the results meet the criteria for acceptable linearity within this calibration range.
Naturally, the development of quantitative GC×GC studies based on the quantitative results associated with sophisticated implementation for modulated peaks has been delayed where A x is the peak area of a quantifying ion for a given analyte being measured; A is is the peak area of a quantifying ion for its corresponding internal standard; C x is the concentration of a given analyte; and C is is the concentration of its corresponding internal standard. compared with qualitative reports. Recently, the approach to quantifying multiple analytes at once with comprehensive two-dimensional GC has been extensively studied in accordance with the improvement of data processing for the integration of modulated peaks [37,38]. In this study, the modulated peaks of each PAH was automatically combined and integrated by the ChromaTOF software based on a similarity of spectra within an allowable time difference between the second dimension peaks in the neighboring slices of the chromatogram. Recovery test was performed by spiking known amounts of the 18 PAH compounds in a prebaked clean filter at a final concentration of 2 μg/mL and analyses of each through all the experiment procedures were compared using the two different methods. Six duplicate tests were performed, and the results of the recovery are shown in Table 4. e average recoveries were in the range of 90.3 to 158% with relative standard deviations (RSDs) ranging from 3.9 to 28% for GC-qMS, while the recoveries were from 86.3 to 135% for GC×GC-TOFMS, with RSDs ranging from 5.7 to 45%. Most of the targeted PAH compounds were afforded acceptable recoveries, excluding F and Nap by using the two analytical methods due to the high volatility of these compounds. Compared with the reproducibility as expressed in %RSDs, the values obtained by GC-qMS were slightly lower than those obtained by GC×GC-TOFMS; however, the %RSD values of the targeted PAHs excluding F and Nap were acceptable (<20% RSD). ese observations may vary for the versatile GC×GC technique, since the reproducibility of the modulation phase is dependent on the type of modulator, the stability of the stationary phases, and the chemistry of the analyte, regarding interaction with the stationary phase as presented in several prior studies [39,40]. e LOD and LOQ were determined based on the standard deviation (SD) of the intersection of the analytical curve (s) and the slope of the curve (S) as LOD � 3.3 × (s/S) and LOQ � 10 × (s/S). e LOD and LOQ for each PAH compound obtained from both the methods are shown in Table 4. e LOD and LOQ values of the 18 PAH compounds obtained by GC-qMS were similar to the results of previous studies [10,41,42]. us, the suitability of GC×GC-TOFMS for quantification of PAHs was proven by comparing the results with those obtained using GC-qMS.
Conclusion
A fast scanning GC×GC-TOFMS was compared to a GC-qMS for the determination of PAHs in aerosol samples. For separation, identification, and characterization, GC×GC-TOFMS was advantageous over GC-qMS owing to the increased peak capacity, and its results showed enhanced detectability and structured chromatograms for nontarget analysis. e qualitative mass separation by TOFMS combined with an automated peak-finding capability provided the resolution of complex mixed mass spectra, resulting from overlapping chromatographic peaks and spectral deconvolution of individual mass spectra for unknown analytes. Furthermore, the obtained quantitative results such as LODs, LOQs, and recoveries of the 18 target PAHs were approximately equivalent for both the analytical methods. us, GC×GC-TOFMS had advantages for the simultaneous quantification and qualification of PAHs and other organic compounds in a single run. Because of its high degree of separation and capability of spectral deconvolution of overlapping peaks in highly complex samples, comprehensive GC×GC-TOFMS may become a useful platform in many other fields of research.
Conflicts of Interest
e authors declare that they have no conflicts of interest. Journal of Analytical Methods in Chemistry 7 | 3,774.4 | 2018-04-01T00:00:00.000 | [
"Environmental Science",
"Chemistry"
] |
XSAnno: a framework for building ortholog models in cross-species transcriptome comparisons
Background The accurate characterization of RNA transcripts and expression levels across species is critical for understanding transcriptome evolution. As available RNA-seq data accumulate rapidly, there is a great demand for tools that build gene annotations for cross-species RNA-seq analysis. However, prevailing methods of ortholog annotation for RNA-seq analysis between closely-related species do not take inter-species variation in mappability into consideration. Results Here we present XSAnno, a computational framework that integrates previous approaches with multiple filters to improve the accuracy of inter-species transcriptome comparisons. The implementation of this approach in comparing RNA-seq data of human, chimpanzee, and rhesus macaque brain transcriptomes has reduced the false discovery of differentially expressed genes, while maintaining a low false negative rate. Conclusion The present study demonstrates the utility of the XSAnno pipeline in building ortholog annotations and improving the accuracy of cross-species transcriptome comparisons. Electronic supplementary material The online version of this article (doi:10.1186/1471-2164-15-343) contains supplementary material, which is available to authorized users.
Background
The accurate characterization and quantification of orthologous transcripts across species are critical for understanding the evolution of gene expression and the transcriptome-phenotype relationship. Previous comparative studies have shown that the evolutionary changes in gene expression play a key role in phenotypic changes between species, including the differences between human and closely related non-human primates [1,2].
The development of sequencing technology, such as RNA-seq, has provided significant advantages over previous microarray technology, for quantifying expression divergence. RNA-seq does not rely on specific predesigned probes or a priori knowledge of the transcriptome under investigation, thereby theoretically allowing unbiased whole transcriptome profiling of any species and performing cross-species comparisons [3]. Furthermore, in contrast to microarray, where even a single nucleotide mutation in probe sequence may affect the efficiency of probe hybridization, RNA-seq is more robust to sequence variations between species. However, comparing transcriptomes of different species using RNA-seq is challenging. One critical challenge is the lack of high-quality annotation of orthologous genes. Although multiple databases, such as Ensembl homologs [4], OrthoDB [5] and eggNOG [6], provide a catalog of orthologs between species, none of them provide coordinates of corresponding orthologous regions on reference genomes, which makes it difficult to employ them for RNA-seq analysis. Prevailing annotations for cross-species RNA-seq analysis are based on sequence conservation through either whole genome alignment or local alignment, and have been previously implemented in analyzing transcriptional differences between humans and non-human primates [7][8][9][10].
Another challenge in cross-species transcriptome comparisons is the variation of short-read mappablity to orthologs among species. Although the leading short read mapping algorithms all try to identify the best mapping position for each read, a read may still map equally well or nearly equally well to multiple positions because of paralogous sequences in the reference genome [11]. Furthermore, a previous study has shown that mappability varies greatly between species and gene classes [12]. In RNA-seq analysis, the quantification of gene expression will thus be affected by the existence of paralogous sequences. The problem becomes apparent when we perform differential expression analysis between species. A gene may be falsely identified as differentially expressed gene due to differences in mappability between species.
Here, we first analyzed the bias in estimating interspecies difference in expression caused by inter-species difference in mappability based on current annotations, using a published dataset consisting of RNA-seq and high-density exon array. We then created a pipeline named XSAnno, which generated a model of orthologs by combining whole genome alignment, local alignment and multiple filters to remove regions with difference in mappability (DIM) between species. The steps in our computational pipeline are inspired by common practice for annotating orthologous regions, but were modified to suit the specific aim of comparative transcriptome analysis. To assess our method, we performed RNA-seq on dorsolateral prefrontal cortex (DFC) of 5 humans, 5 chimpanzees and 3 rhesus macaques and benchmarked the performance of XSAnno on identifying differentially expressed (DEX) genes between species, by comparing with annotations used in previous studies [7][8][9][10]. Validation by ddPCR revealed that our approach greatly reduced the false positives, while keeping the number of false negatives low.
Results and discussion
Differences in mappability between species skew gene expression comparisons To assess the effects of inter-species difference in mappability on estimating inter-species difference in expression using current annotations, we took advantage of a published dataset including RNA-seq and high-density human exon junction array data from cerebellum of human, chimpanzee and rhesus macaque [8]. The RNAseq data included a total of five lanes of 36 bp single-end reads with two technical replicates for human and macaque and one lane for chimpanzee (Additional file 1: Table S1). The microarray data included 3 replicates of human, chimpanzee and rhesus macaque cerebellum samples (Additional file 1: Table S1). To avoid bias in gene expression quantification, only microarray probes that perfectly matched the genome sequences of all three species were used. As microarray probes were designed to uniquely detect a set of known genes, microarrays are less biased by inter-species differences in mappability than RNA-seq. Therefore, we tested the performance of annotations generated by two most widely used approaches by comparing them with the microarray data. One set of annotation was built based on Ensembl annotation (V64) [4] through whole genome alignment as described in the original study and other studies [7,9] (WGA annotation, see Methods). The other set was originally built in Blekhman et al. [10] and updated in Primate Orthologous Exon Database (POED), which includes a catalog of unique, non-overlapping, 1:1:1 orthologous exons of human, chimpanzee and rhesus macaque indentified through local alignment from Ensembl annotation.
In the WGA annotation, 11,420 human-chimpanzee orthologs and 11,461 human-macaque orthologs were shared with microarray. In POED annotation, 11,266 1:1:1 human-chimpanzee-macaque orthologs were shared with microarray. To identify genes with difference in mappability (DIM genes), we generated ten lanes of simulated RNA-seq (s-RNA-seq) reads per species based on each set of annotation, with the setting that all the transcripts were equally expressed. DIM genes were identified by DESeq [13] with FDR < 0.01, using s-RNA-seq data. We then plotted the inter-species difference estimated by RNA-seq data against inter-species difference estimated by microarray data ( Figure 1). DIM genes in WGA annotation showed larger inter-species difference than genes with consistent mappability between species (consistent genes) based on RNA-seq (human-chimpanzee p < 2.2 × 10 −16 , human-macaque p < 2.2 × 10 −16 ; see Methods). On the contrary, DIM genes showed similar inter-species difference to consistent genes based on microarray (human-chimpanzee p = 0.90, human-macaque p = 0.94; see Methods; Figure 1a, b). The difference between RNA-seq and microarray suggested that variations in mappability affected the estimation of inter-species difference. As expected, POED annotation included fewer genes with variant mappability between species, because it is a set of orthologs shared by three species and built with local alignment, which is more stringent in terms of sequence conservation, compared with WGA annotation (Figure 1c, d). We observed similar larger interspecies difference of DIM genes estimated by RNA-seq than by microarray using POED annotation (RNA-seq: human-chimpanzee p = 0.005, human-macaque p = 0.09; microarray: human-chimpanzee p = 0.88, human-macaque p = 0.22; see Methods). Besides, more genes with no s-RNA-seq reads aligned were identified using POED annotation, suggesting shortened gene length during the process of ortholog identification (Additional file 2: Figure S1). The inter-species differences of these genes were also more dispersed from 0 in RNA-seq than in microarray (Figure 1), suggesting that the gene expression cannot be well represented if the gene model is truncated too much in the process of ortholog identification.
Another problem with using only local alignment is the loss of syntenic information of genome. In POED annotation, we found some human orthologs in chimpanzee or macaque with exons located in unreasonably distant genomic regions. For example, in POED, the length of RIN3 is around 130 kb in human, but1 25 Mb in macaque, including an 125 Mb intron.
Outline of the XSAnno framework
To fit the aim of RNA-seq analysis, we developed the XSAnno framework for annotating orthologous regions for cross-species gene expression comparisons. XSAnno integrates whole genome alignment, which preserved syntenic information of genome and local alignment, which removes exons that are not highly conserved in sequence with multiple filters, which filters out exons and genes with varied mappability between species ( Figure 2): (i) Our pipeline started with whole-genome alignment (WGA), which preserves syntenic information of the genome. We use UCSC liftOver tool [14], which converts the genome coordinates between species based on whole genome alignment. We select one species (Sp1), usually the one with better annotation, as reference species and lift the annotation to the other species (Sp2). The lifted annotation on Sp2 is then lifted back to the genome of Sp1. The parameters of liftOver are carefully selected by bootstrapping (Supplementary Methods & Additional file 2: Figure S2). In the process, we filter out exons that cannot be lifted from Sp1 to Sp2, exons cannot be lifted back to the original genomic location of Sp1, and transcripts without all exons lifted to the same chromosome or strand. (ii)We then perform local alignment (LA) to remove exons that are not highly conserved in sequence and exons that may cause ambiguity in RNA-seq read mapping. We align the exons from step one of both species to their reference genome and the reference genome of the other species, respectively, using BLAT [15]. Only exons with a unique conserved ortholog but without highly conserved paralogs are Figure 1 The effects of different mappabality between species on estimating inter-species gene expression differences. Inter-species gene expression differences estimated by RNA-seq were plotted against inter-species differences estimated by microarray, using WGA annotation (a, b) and POED annotation (c, d). The inter-species differences were calculated as log2 fold change of RPKM (RNA-seq) or intensity (microarray). The rug plots along x and y axes show the distribution of interspecies differences estimated by microarray and RNA-seq, respectively. DIM genes (red) and genes without simulated reads mapped (green) show larger inter-species variation in RNA-seq than in microarray. Figure S3). (iii)Finally, we filter out DIM exons and genes. We generate simulated RNA-seq data using simNGS [16] (http://www.ebi.ac.uk/goldman-srv/simNGS/), incorporating sequencing errors, and setting all transcripts to be equally expressed. With this setting, exons and genes with different mappability of s-RNA-seq reads show statistically significant differential expression and are therefore removed. Besides, we remove genes that are truncated too much (see Methods).
Generation of human-chimpanzee and human-macaque annotations by XSAnno
As an example of comparisons between closely-related species, our pipeline was first applied to generate humanchimpanzee orthologous genes based on human gene annotation (Ensembl v64) [4], human reference genome (hg19) [17], and chimpanzee reference genome (panTro2) [18]. Starting with 54,127 genes (21,165 protein-coding genes) in Ensembl human gene annotation, we identified 37,662 human-chimpanzee orthologous genes, including 16,774 protein-coding genes ( Table 1 & Additional file 1: Table S2). Higher conversion rates were observed for protein-coding genes and lincRNAs, 79.3% and 73.7%, respectively (Additional file 1: Table S2). As expected, the application of XSAnno to human and rhesus macaque, a pair with a more distant evolutionary relationship, identified fewer orthologs. We identified 24,285 human-macaque orthologous genes, including 15,051 protein-coding genes ( Table 1 & Additional file 1: Table S2). Compared with human-chimpanzee orthologs, the decrease in human-macaque orthologs mainly occurred in non-protein-coding genes, particularly pseudogenes (Table 1 & Additional file 1: Table S2) due to the existence of highly conserved paralogs.
Testing the performance of XSAnno on differential expression analyses Since the above used published dataset consists of only two technical replicates for human and macaque and no replicates for chimpanzee, it lacks statistical power to identify differentially expressed (DEX) genes. Furthermore, the samples were sequenced as 36 bp single-end reads.
Therefore, we performed mRNA-seq (75 bp single-end reads) of DFC tissue from 5 chimpanzee and 3 rhesus macaques (Methods and Additional file 1: Table S3) and compared with the complementary mRNA-seq dataset of 5 human DFC samples generated by the BrainSpan project (www.brainspan.org) (Additional file 1: Table S3). The resulting sequencing reads have been deposited to the National Center for Biotechnology Information (NCBI) shortread archive under the accession number PRJNA233428.
The XSAnno human-chimpanzee annotation covered 70.1% chimpanzee RNA-seq reads, which was lower than 77.1% in WGA annotation as expected, but greater than 59.1% in POED (Additional file 2: Figure S5). 90.0% of the human-expressed XSAnno orthologs were also expressed in chimpanzee. Similarly, the XSAnno annotation for human and macaque covered 62.9% macaque RNA-seq reads, greater than 61.6% in POED (Additional file 2: Figure S5). 90.0% of the human-expressed XSAnno orthologs were also expressed in rhesus macaque. Besides, WGA annotation annotates 95.3% and 96.7% junctions identified by TopHat [19] in chimpanzee and macaque, Figure 3 Assessment of filtering steps in XSAnno using published data. Comparison of inter-species difference estimated by RNA-seq and inter-species difference estimated by microarray, using WGA annotation (a, b) and using WGA+LA annotation (c, d). Genes filtered out in step 2 (a, b) and step 3 (c, d) are labelled red. These genes display larger inter-species difference using RNA-seq data than using microarray data. respectively, indicating that the gene structures were preserved in the first step of ortholog identification in our pipeline. The filters applied later reduced the coverage of junctions, but still maintained majority of the junctions, suggesting that our annotation can also be implemented in analyzing alternative splicing (Additional file 2: Figure S6).
To assess the filtering steps in XSAnno pipeline, we first compared the inter-species difference of included genes with that of excluded genes. The genes filtered out in each step showed larger estimated inter-species variation than that of genes remained (p < 2.2 × 10 −16 in each filtering step in both human-chimpanzee and human-macaque comparisons; see Methods; Additional file 2: Figure S7). To rule out the possibility that our filters selectively removed differentially expressed genes, we compared the inter-species variation of exons from the same gene. Similar to the expression of genes, the expression of retained exons was less variable between species than that of excluded exons from the same gene (p < 2.2 × 10 −16 in each filtering step in both human-chimpanzee and human-macaque comparisons; see Methods; Additional file 2: Figure S8).
Since our annotation was designed for cross-species expression comparison, we first assessed the performance of each filtering step in our pipeline. The number of DEX genes was dramatically reduced after filtering (Additional file 2: Figure S9). For validation, we intersected the humanchimpanzee DEX gene list and the human-macaque DEX gene list to differentially expressed in human compared with both chimpanzee and macaque (human DEX genes). The top 10 human DEX genes found only in the WGA annotation, the top 10 human DEX genes in the WGA + LA annotation but not in the XSAnno annotation, and the top 10 human DEX genes in the XSAnno annotation were selected for validation by droplet digital PCR (ddPCR) (Additional file 1: Table S4). As expected, our approach performed better between species with closer evolutionary distance. In the comparison between human and chimpanzee, the number of false positives reduced from 20 using WGA annotation to 2 using XSAnno annotation, while the number of false negatives remained at 0 (Figure 4 & Additional file 1: Table S5). In the comparison between human and macaque, the number of false positives reduced from 14 using WGA annotation to 2 using XSAnno annotation, while the number of false negatives rose to 5 (Figure 4 & Additional file 1: Table S5). Sequence analysis of the genes identified as human DEX only in WGA or WGA + LA annotation revealed the existence of highly conserved paralogs in one species but not in the other, which explained the difference in mappability between species (Additional file 1: Table S6). Among the genes we validated, our pipeline reduced the false positives and kept the false negative rate low, compared with WGA and POED annotations (Figure 4).
Conclusions
We described a pipeline to build ortholog annotations for comparative transcriptome analysis between closelyrelated species. The XSAnno pipeline incorporates previous whole genome alignment and local alignment methods with multiple filters to eliminate false positives caused by differences in mappability. Even though our pipeline was tested on human and non-human primate brain transcriptome data, it is not limited to these species.
Our pipeline aims to generate annotation of a conservative set of orthologs to avoid false positives in crossspecies analysis. Therefore, it excludes genes with high rate of DNA changes and genes with highly conserved paralogs. Although the level of conservation can be adjusted by tuning parameters in the pipeline to meet specific requirements of each study, separate approaches would be necessary to study genes with large structure changes and duplicated genes.
Compared to existing ortholog databases, the XSAnno pipeline provides a more flexible way to identify orthologs between any pair of closely-related species. It generates gene models that are specifically designed for comparative transcriptome analysis. RNA-seq and ddPCR validation suggest that our approach reduced false positives in cross-species expression analysis, while keeping the false negative rate low. The XSAnno package and pre-processed ortholog annotations of selected species are available in Additional file 3 and can be downloaded at http://medicine.yale.edu/lab/sestan/ resources/index.aspx.
WGA annotation
To keep syntenic information, human exons from all transcripts were lifted to genomic locations on reference genome of chimpanzee and macaque by liftOver tool [14], using pair-wise alignment files downloaded from UCSC genome browser. The liftOver parameter "-minMatch" was set to 0.98 for chimpanzee and 0.913 for macaque, based on bootstrapping (Supplementary Methods & Additional file 2: Figure S2). The lifted exons on reference genome of chimpanzee and macaque were then mapped back to human reference genome, using lift-Over tool. During the reciprocal mapping, the following exons/transcripts were excluded: (i) exons cannot be lifted from human to the other species were filtered out; (ii) exons cannot be lifted back to the original genomic location of human genome were filtered out; (iii) transcripts with exons mapped to different chromosomes or strands were filtered out. The process can be completed in one step by running AnnoConvert in our pipeline.
POED annotation
The orthologous exons of human, chimpanzee and macaque were downloaded from Primate Orthologous Exon Database (POED, Version 2; http://giladlab.uchicago.edu/ orthoExon/). To be consistent with other databases, we converted genomic coordinates on chimpanzee genome panTro3 to panTro2 by liftOver.
XSAnno annotation
Step1: The first step is the same as how we build WGA annotation.
Step2: Exons from WGA annotation were aligned to the reference genomes of both the same and the other species by BLAT [15]. Percent identity (PID) and percentage of aligned length (PL) were calculated as measures of local alignment. The thresholds of inter-species and intra-species PID and PL were chosen separately to maximize the number of exons retained (Supplementary Methods and Additional file 2: Figure S3). The interspecies PID and PL were selected to filter out exons without unique, highly conserved orthologs. For human and chimpanzee, the inter-species PID and PL were both set to 0.95. For human and macaque, the inter-species PID and PL were both set to 0.9. Exons that were not aligned to the same genomic location as WGA annotation or were aligned to multiple genomic locations using current cutoff were removed. The intra-species PID and PL were selected to filter out exons with highly conserved regions, which may cause ambiguity in mapping. For both chimpanzee and macaque, the intra-species PID was set to 0.97 and the intra-species PL was set to 0.95. Exons that were aligned to multiple genomic locations of their own reference genome at current cutoff were filtered out. The process can be finished by running BlatFilter combined with R [21] functions of threshold determination and filtering.
Step3: To eliminate exons and genes with large interspecies difference in mappability, we generated simulated RNA-seq data with the setting that all transcripts are equally expressed, using simNGS. To run simNGS in parallel with Step Two, we generated simulated HiSeq 100 bp single-end reads based on WGA annotation and then calculated expression only for exons in WGA + LA annotation. Coverage of all transcripts was set to 10X. Ten simulated RNA-seq fastq files were generated for each species. The simulated reads were then mapped to their own genome, using TopHat [19] without providing junction annotation. The number of reads mapped to each exon was counted and used for differential expression analysis with DESeq package [13] for R. Exons and genes that are significantly different between species (FDR < 0.01) were filtered out. Besides, we filtered out genes with length smaller than one third of original length and shorter than 1 kb.
The example scripts to generate simulated reads and to filter exons and genes are available in our pipeline.
Analysis of published data
Affymetrix Human Exon Junction array data were downloaded from GSE15665. Gene expression was estimated using probes perfectly conserved in nonhuman primates and normalized by quantile normalization as described in the original study.
RNA-seq data were downloaded from SRA023554.1. RNAs were sequenced as 36 bp (human) and 35 bp (chimpanzee and macaque) single-end reads by Illumina GAII. Reads were aligned by TopHat, allowing 2 mismathes, without providing transcriptome annotation. Read count and RPKM of genes were calculated by RSEQTools [22].
Ten lanes of simulated RNA-seq data per species were generated by simNGS, using different sets of annotations. DIM genes were identified by DESeq with FDR < 0.01.
To compare inter-species differences of DIM genes with that of genes with consistent cross-species mappability, we performed the F test for equality of variances. In detail, if mappability affects estimation of inter-species differences, we expect larger variance in inter-species differences of DIM genes than in inter-species differences of consistent D and S 2 C represent the sample variances of inter-species differences of DIM genes and consistent genes, respectively). The F test was conducted using R function var.test, with alternative hypothesis S 2 D > S 2 C .
RNA sequencing and data analysis RNA extraction
Postmortem human brain specimens were obtained from tissue collections at the Department of Neurobiology at Yale University School of Medicine and the Clinical Brain Disorders Branch of the National Institute of Mental Health. Tissue was collected after obtaining parental or next of kin consent and with approval by the institutional review boards at the Yale University School of Medicine, the National Institutes of Health, and at each institution from which tissue specimens were obtained. Tissue was handled in accordance with ethical guidelines and regulations for the research use of human brain tissue set forth by the NIH (http://bioethics.od.nih.gov/humantissue.html) and the WMA Declaration of Helsinki (http://www.wma. net/en/30publications/10policies/b3/index.html). Appropriate informed consent was obtained and all available nonidentifying information was recorded for each specimen. Specimens range in age from 21 to 40 years. The postmortem interval (PMI) was defined as hours between time of death and time when tissue samples were frozen. All experiments using nonhuman primates were carried out in accordance with a protocol approved by Yale University's Committee on Animal Research and NIH guidelines.
DFC tissue samples were dissected from postmortem adult chimpanzee and macaque brains using the criteria previously described [23,24]. Human DFC RNA-seq data were generated as a part of the BrainSpan project (www. brainspan.org). Together, the RNA-seq dataset includes DFC samples from 5 humans, 5 chimpanzees, and 3 macaques. A bead mill homogenizer (Bullet Blender, Next Advance) was used to lyse the pulverized DFC tissue samples. Each pulverized tissue sample was transferred to a chilled safe-lock microcentrifuge tube (Eppendorf ). A mass of chilled stainless steel beads (Next Advance, cat# SSB14B) equal to the mass of the tissue was added to the tube. Two volumes of lysis buffer were added to the tissue and beads. Samples were mixed in the Bullet Blender for 1 min at a speed of six. Samples were visually inspected to confirm desired homogenization and then incubated at 37°C for 5 min. The lysis buffer was added up to 0.6 ml, and samples were mixed in the Bullet Blender for 1 min. Total RNA was extracted using RNeasy Plus Mini Kit (Qiagen) for mRNAsequencing. Each sample was subjected to a DNase treatment (TURBO DNase, Ambion) as per manufacturers' instructions.
Optical density values of extracted RNA were measured using NanoDrop (Thermo Scientific) to confirm an A260: A280 ratio above 1.9. RIN was determined for each sample using Bioanalyzer RNA 6000 Nano Kit (Agilent), depending upon the total amount of RNA.
Library preparation for mRNA-sequencing cDNA libraries were prepared using the mRNA-Seq Sample Kit (Illumina) as per the manufacturer's instructions with some modifications. Briefly, polyA RNA was purified from 1 to 5 μg of total RNA using (dT) beads. Quaint-IT RiboGreen RNA Assay Kit (Invitrogen) was used to quantitate purified mRNA with the NanoDrop 3300. Following mRNA quantitation, 2.5 μl spike-in master mixes, containing five different types of RNA molecules at varying amount (2.5 × 10 −7 to 2.5 × 10 −14 mol), were added per 100 ng of mRNA [25]. The spike-in RNAs were synthesized by External RNA Control Consortium (ERCC) consortium by in vitro transcription of de novo DNA sequences or of DNA derived from the B. subtilis or the deep-sea vent microbe M. jannaschii genomes and were a generous gift of Mark Salit at the National Institute of Standards and Technology (NIST). These were used both to track the brain regions, species and to normalize expression levels across experiments. Each sample was tagged by adding a pair of spike-in RNAs unique to the region from which the sample was taken. Also, an additional three common spike-ins were added for controlling sequencing error rates, which is not influenced by SNP existence (Additional file 1: Table S7). Spike-in sequences are available at http://archive.gersteinlab.org/proj/brainseq/ spike_in/spike_in.fa. The mixture of mRNA and spike-in RNAs were subjected to fragmentation, reverse transcription, end repair, 3′-end adenylation, and adapter ligation to generate libraries of short cDNA molecules. The libraries were size selected at 200 -250 bp by gel excision, followed by PCR amplification and column purification. The final product was assessed for its size distribution and concentration using Bioanalyzer DNA 1000 Kit.
Sequencing
We used Illumina's Genome Analyzer IIx (GAIIx) for mRNA-sequencing by loading one sample per lane. For mRNA-sequencing, the library was diluted to 10 nM in EB buffer and then denatured using the Illumina protocol. The denatured libraries were diluted to 12 pM, followed by cluster generation on a single-end Genome Analyzer IIx (GAIIx) flow cell (v4) using an Illumina cBOT, according to the manufacturer's instructions. The Illumina GAIIx flow cell was run for 75 cycles using a single-read recipe (v4 sequencing kits) according to the manufacturer's instructions.
Mapping of mRNA-seq reads
We chose TopHat to map RNA-seq reads due to its ability to map junction reads without depending on annotation. The reference genomes used were the same as those for ortholog identification. Only uniquely mapped reads with at most 2 mismatches were included to calculate exon/gene read number and reads per kilobase per million (RPKM) [26].
Testing the effects of filters
To test the effects of each filtering step, we first compared the inter-species variation of genes remained with the ones filtered out in each filtering step. The interspecies log2-fold-change (log 2FC = log 2(RPKM sp1 + 1) − log 2(RPKM sp2 + 1)); sp1 and sp2 stand for Species 1 and Species 2, respectively) were calculated for each gene, using WGA annotation, WGA+LA annotation, and XSAnno annotation, respectively. To test the effects of local alignment, we compared the distribution of interspecies log2FC of genes remained in WGA+LA annotation from WGA annotation with that of genes excluded in WGA+LA annotation. Similarly, the distribution of interspecies log2FC of genes remained in XSAnno annotation was compared with the distribution of genes filtered out in XSAnno annotation from WGA+LA annotation. We conducted the F test for equality of variances as used in analyzing the published dataset.
To compare the inter-species variation of included exons with excluded exons from the same transcripts, we summarized the inter-species variation of in and out exons by calculating the mean inter-species log2FC. In other words, for a specific gene, exonFC in = mean (log2FC in ); exonFC out = mean (log2FC out ). For each gene, the difference between exons included and excluded was then calculated as In-Out = |exonFC in | -| exonFC out |. We then performed the paired Wilcoxon signed-rank test with alternative hypothesis |exonFC in | < |exonFC out | to test whether inter-species difference of in-exons are smaller than that of out-exons.
Differential expression analysis
Differential expression analysis were performed between human and chimpanzee and between human and macaque, respectively, with DESeq [13] package for R. Genes were identified as DEX, if FDR < 0.01.
The list of human-chimpanzee DEX genes were then intersected with the list of human-macaque DEX genes. Genes with the same direction of change (up or down) in human comparing with other two species were selected as human DEX genes.
Validation by droplet digital PCR
Thirty genes in the human DEX gene list were selected for validation, including 10 most significant human DEX genes only in WGA annotation, 10 most significant human DEX genes in WGA+LA annotation but not in XSAnno annotation, and 10 most significant human DEX genes in XSAnno annotation (Table S4).
We employed droplet digital PCR (ddPCR) to reliably quantify gene expression. An aliquot of the total RNA that was previously extracted from 3 randomly selected brains per species was used for secondary validation through ddPCR analysis. One μg of total RNA was used for cDNA synthesis using SuperScript III First-strand synthesis Supermix (Invitrogen) and subsequently diluted with nucleasefree water. Custom gene-specific primers and probe for each gene of interest were designed using NCBI/Primer-BLAST (http://www.ncbi.nlm.nih.gov/tools/primer-blast/) and PrimerQuest tool (IDT). In detail, primer pairs were designed in genomic regions that are orthologous (or identical, if the gene is conserved highly across three species), as well as to be separated by at least one intron on the corresponding genomics DNA with a targeted amplicon size at 70 bp to 200 bp. We also allowed primers to amplify mRNA splice variants that are annotated in RefSeq, while did not allow them to contain known SNPs. The probe was designed by PrimerQuest tool (IDT) by applying the above pre-designed PCR primers. We opted to design identical probe sequence for each species, but if the target region is less conserved across three species, we had to design slightly different probes for each species. IDT's proprietary ZEN internal quencher was applied on top of a 3′ quencher (IBFQ) and a 5′ fluorophore (FAM or HEX) probe labeling. ddPCR was carried out using the Bio-Rad QX100 system. After each PCR reaction mixture, consisting of ddPCR master mix and custom primers/ probe set, was partitioned into 15,000-20,000 droplets, parallel PCR amplification was carried out. Endpoint PCR signals were quantified and Poisson statistics was applied to yield target copy number quantification of the sample. Two color PCR reaction was utilized for the normalization of gene expression by the housekeeping gene TBP. Table S8 in Additional file 1 provides sequences of primers and probes used for the validation.
Gene expression was calculated as the ratio of target genes to the housekeeping gene TBP. Wilcoxon signedrank tests were performed to identify differentially expressed genes between human and chimpanzee and between human and macaque, separately. Genes were considered as DEX if p ≤ 0.1.
Additional files
Additional file 1: Table S1. Sample information of published data. Table S2. Gene number in different annotations. Table S3. Sample Information of our RNA-seq data. Table S4. List of genes for validation. Table S5. RNA-seq and ddPCR results of genes for validation. Additional file 2: Methods: Determination of liftOver parameters and Determination of BLAT parameters. Figure S1. Distribution of gene length. Figure S2. Determination of liftOver parameters. Figure S3. Determination of BLAT parameters. Figure S4. Distribution of inter-species difference in mappability. Figure S5 Percentage of reads covered by different annotations. Figure S6. Percentage of junction reads covered by different annotations. Figure S7. The performance of filters on estimating inter-species differences of genes. Figure S8. The performance of filters on estimating inter-species differences of exons. Figure S9. The number of differentially expressed genes. | 7,471.8 | 2014-05-07T00:00:00.000 | [
"Computer Science",
"Biology"
] |
The dust-to-gas ratio, size distribution, and dust fall-back fraction of comet 67P/Churyumov-Gerasimenko: Inferences from linking the optical and dynamical properties of the inner comae
In this work, we present results that simultaneously constrain the dust size distribution, dust-to-gas ratio, fraction of dust re-deposition, and total mass production rates for comet 67P/Churyumov-Gerasimenko. We use a 3D Direct Simulation Monte Carlo (DSMC) gas dynamics code to simulate the inner gas coma of the comet for the duration of the Rosetta mission. The gas model is constrained by ROSINA/COPS data. Further, we simulate for different epochs the inner dust coma using a 3D dust dynamics code including gas drag and the nucleus' gravity. Using advanced dust scattering properties these results are used to produce synthetic images that can be compared to the OSIRIS data set. These simulations allow us to constrain the properties of the dust coma and the total gas and dust production rates. We determined a total volatile mass loss of $(6.1 \pm 1.5) \cdot 10^9$~kg during the 2015 apparition. Further, we found that power-laws with $q=3.7^{+0.57}_{-0.078}$ are consistent with the data. This results in a total of $5.1^{+6.0}_{-4.9}\cdot10^9$~kg of dust being ejected from the nucleus surface, of which $4.4^{+4.9}_{-4.2}\cdot10^9$~kg escape to space and $6.8^{+11}_{-6.8}\cdot10^8$~kg (or an equivalent of $14^{+22}_{-14}$~cm over the smooth regions) is re-deposited on the surface. This leads to a dust-to-gas ratio of $0.73^{+1.3}_{-0.70}$ for the escaping material and $0.84^{+1.6}_{-0.81}$ for the ejected material. We have further found that the smallest dust size must be strictly smaller than $\sim30\mu$m and nominally even smaller than $\sim12\mu$m.
INTRODUCTION
The European Space Agency's (ESA) Rosetta mission escorted comet 67P/Churyumov-Gerasimenko (hereafter 67P) from August 2014 to September 2016 along its orbit through the inner Solar System. It watched as the comet's activity started to develop at large heliocentric distances, come to its culmination at perihelion, and decline as the comet travelled out towards Jupiter's orbit. This long-term continuous monitoring of the comet's activity has provided an unprecedented wealth of data on this comet and its activity.
The observations revealed a complex bi-lobate shape (Sierks et al., 2015;Preusker et al., 2017) and diverse morphology (Thomas et al., 2015b). As a comet approaches the Sun it is heated and the ices start sublimating and ripping with them dust particles. Thus one of the important questions to be answered was what the bulk of the comet was made of i.e. what the bulk refractory-to-volatile ratio is. In the simplified view where any ejected material is lost to space two measurements are sufficient to determine this ratio. First, the total mass loss during one apparition measured by the Radio Science Investigation (RSI) (Pätzold et al., 2019). Second, the total volatile mass loss which can be indirectly determined by the in-situ measurements of the gas density (e.g. Fougere et al., 2016;Läuter et al., 2018;Combi et al., 2020) or remote sensing data (e.g. Migliorini, A. et al., 2016;Bockelée-Morvan et al., 2016;Marshall et al., 2017;Biver et al., 2019). In this simple case, the refractory-to-volatile ratio can be immediately inferred from those two measurements. But the complex surface morphology has revealed large dust deposits ) that indicate that possibly a large fraction of the ejected dust is re-deposited (Thomas et al., 2015a). If that is indeed the case, then the two above mentioned quantities cannot constrain the total dust mass ejected but rather only the dust mass escaping the nucleus gravity. Further, the process of dust fall-back obscures the emitted dust-to-gas ratio.
One way of constraining the amount of fall-back material would be to attempt to measure the actual change in elevation of the surface as a function of time from local or global digital terrain models (DTM). We cannot assess at this point if that is indeed feasible with the Optical, Spectroscopic and Infrared Remote Imaging System (OSIRIS, Keller et al., 2007) data set. Another way is to couple the scattering properties of the dust with a dynamical model of the dust coma constrained by the brightness of the dust coma. In this work, we have adopted the latter approach and modelled the inner gas and dust comae for the entire Rosetta mission. We use Rosetta Orbiter Spectrometer for Ion and Neutral Analysis (ROSINA, Balsiger et al., 2007) data to constrain the gas production rate and OSIRIS data for our dust models. To constrain the dust models we compare the dust coma brightness as measured by OSIRIS to synthetic model images. This process links several dust parameters that are otherwise not easily combined. In particular, we will show how the dust size distribution, the dust-to-gas ratio, the fraction of fall-back and the optical properties are inter-dependant and thus cannot be determined independently.
In Sec. 2 we will describe the method used and lay out the assumptions we have made. Furthermore, we will point out the free parameters of the models, that need constraining through Rosetta data. Some theoretical considerations are presented in Sec. 3. We will discuss the results of our work in Sec. 4 and summarise and conclude our work in Sec. 5.
METHOD
In this work, we have used the modelling approach (and in particular our DRAG3D model for the dust coma) described in detail in Marschall et al. (2016). This approach has been successfully applied for the analysis and interpretation of multiple Rosetta instruments, in particular ROSINA, MIRO (Microwave Instrument for the Rosetta Orbiter), VIRTIS (Visible and Infrared Thermal Imaging Spectrometer), and OSIRIS (Marschall et al., 2016(Marschall et al., , 2017Gerig et al., 2018;Marschall et al., 2019b). While in previous work we have applied this approach to specific epochs of the Rosetta mission, we have employed it here to cover the entire mission period to study longer-term processes. In the following, we will briefly repeat some of the most important parts of the modelling elements and refer to Marschall et al. (2016) for a detailed description.
General assumptions
The calculation of the 3D gas flow field using the Direct Simulation Monte Carlo (DSMC) method is very computationally expensive and it is therefore currently not feasible to cover the entire escort phase of Rosetta (from August 2014 to September 2016) with a high temporal resolution. It is thus necessary to split the comet's orbit into a number of epochs that are computationally feasible and then interpolate between the results using a linear scaling between epochs. To ensure that the calculated results are representative of the respective epoch we make sure that during each of the epochs neither the total solar energy reaching the surface nor where the energy strikes the surface changes substantially. The amount of energy deposited is driven primarily by the heliocentric distance, R h , while the location of deposition apart from the rotation of the comet is controlled by the sub-solar latitude, LAT . We thus chose that the inverse square of the heliocentric distance of the comet's location at the start and end time of each epoch shall be within 15% of the location at the centre date of each epoch. Furthermore that the difference in sub-solar latitude be less than 5 • from the centre time of epoch to the start and end of the epoch, respectively. This leads to the twenty epochs listed in Tab. 1 and illustrated in Fig. 1. Simulations were run for the centre time of each epoch. This choice also ensures that we cover the exact dates of the in-and outbound equinox (epochs 6 and 18) as well as perihelion (epoch 11) and summer solstice (epoch 12). The basis of all simulations is the 3D shape model by Preusker et al. (2017). We use a decimated model with ∼ 440 000 facets due to our computational constraints. To fully define the illumination condition we need to select the sub-solar longitude in addition to the heliocentric distance and sub-solar latitude which are set by the choice of epoch. For each illumination condition, we calculate the incidence angle (angle between the surface normal and the direction of the Sun) of each facet taking into account self-shadowing. This allows calculating the solar energy entering the surface neglecting re-radiation from other facets. By means of a simple energy balance of the incoming solar energy, thermal re-radiation and sublimation we can calculate the sublimation temperature and the sublimation rate of each facet assuming pure water ice.
We do not take into account any emission from shadowed facets, be it due to local night or mutual shadowing by other parts of the nucleus. The calculated pure ice sublimation rate of each facet needs to be scaled to match observed sublimation rates at 67P. Here we assume a pure H 2 O ice surface that is areally mixed with inert refractory surface akin to a chequerboard pattern. This surface fraction of the facet covered by ice, which is a priori not known, is a free parameter of the model. We refer to this scaling factor as the effective active fraction (EAF). This factor only has a physical interpretation for a pure ice surface where it would represents the fraction of pure ice of an areally mixed surface needed for a specific sublimation flux. In general though it is not a physical parameter and should not be interpreted as such.
In the next steps, we calculate the gas and dust flow fields in three dimensions. We then perform a column integration along the line-of-sight through the dust coma for a specific viewing geometry of the OSIRIS NAC (narrow-angle) and WAC (wide-angle) cameras (Keller et al., 2007) and convolve the dust column densities with the optical properties of the dust to arrive at absolute radiance values that can be compared with the OSIRIS images. One major assumption that goes into this approach is that there is no significant back-coupling from the dust to the gas allowing a sequential treatment of the two flows. For low dust-to-gas mass ratios, this is certainly justified (Marschall et al., 2016) but will break down when a lot of dust is released. We will further discuss this limitation later on.
Gas kinetic simulations
The gas flow-field is calculated using the DSMC technique. The code used is called UltraSPARTS 1 and is a commercialized derivative of the PDSC++ code (Su, 2013) used in previous papers (e.g Marschall et al., 2016Marschall et al., , 2017. PDSC++ is a C++ based, parallel DSMC code which is capable of simulating 2D, 2D-axisymmetric, and 3D flow fields. The code has been developed over the past 15 years (Wu and Lian, 2003;Wu et al., 2004;Wu and Tseng, 2005) and contains several important features including the implementation of 2D and 3D hybrid unstructured grids, a transient adaptive sub-cell method (TAS) for denser flows, and a variable time-step scheme (VTS). In the parallel version, computational tasks are distributed using the Message Passing Interface (MPI) protocol. The improved UltraSPARTS (Ultra-fast Statistical PARTicle Simulation Package) has been applied to 67P Gerig et al. (2018); Marschall et al. Here we simulate the full 3D gas flow up to a distance of 10 km from the nucleus centre.
The sublimation temperature and flux -calculated as described above -for each facet are set as initial conditions of the simulation. This includes implicitly the assumption of the appropriate EAF. We assume here that the EAF of all facets are the same (i.e. homogeneous surface properties) but can change from epoch to epoch. This results in one value for the global EAF per epoch. Though we know from previous works (e.g Bieler et al., 2015;Marschall et al., 2016;Fougere et al., 2016;Zakharov et al., 2018a) that there are regional inhomogeneities that can be encoded in EAF it is not the focus of this work to constrain these inhomogeneities. Rather we seek a global estimate of the fluxes and dynamical behaviours. Because the EAF is a free parameter it needs to be constrained by data. In our case, we determine the EAF by comparing modelled densities extrapolated to the Rosetta position and actual COmet Pressure Sensor (COPS; Balsiger et al. (2007)) measurements during each epoch. Within each epoch where we match the sub-solar longitude of a measurement, we extract from the respective simulation the gas number density at the position of the spacecraft. If the spacecraft distance is larger than 10 km we extrapolate the value from the 10 km surface to the spacecraft distance assuming free radial outflow. This assumption is well justified as shown in Marschall et al. (2016). Though this does not capture the detailed structure of the ROSINA/COPS data it does account accurately for the average activity level at each epoch. Tab. 2 shows the EAF used and the resulting average global H 2 O production rate for one comet day.
The global gas production rate as a function of time is shown in Fig. 2 (purple band in top panel). Because we have used the total ROSINA/COPS data -which also contains the other gas species other than waterto constrain our emission, these values should be understood as a proxy for the entire emission. We have interpolated between the epochs using a local second-order polynomial. The fit for each epoch, i, includes three epochs i-1, i, i+1. The fitting parameters to calculate the mean gas production rate as a function of ephemeris time (ET) is shown in Tab. 5. The resulting integrated mass loss over the shown period adds up to (6.1 ± 1.5) · 10 9 kg. This is well in line with values published in other works as e.g. (6.3 ± 2.0) · 10 9 kg (Combi et al., 2020) or (5.8 ± 1.8) · 10 9 kg (Läuter et al., 2018). The error arises from the uncertainty of the data (up to 15%; Tzou (2017) although the relative errors are probably smaller (M. Rubin, pers. comm.)) and our model (5-10%; Finklenburg et al. (2014)) as well as from the scatter from the comparison of the data and our model. As it was not the goal of this work to constrain as precisely as possible the surface-emission distribution it is nevertheless noteworthy that our estimates come so close to the other published values. This illustrates that it is not necessary to know the surface-emission distribution well to estimate the total global volatile loss. Rather simple assumptions of the surface response is sufficient for such an estimate. Though it is not that surprising, because as pointed out in Marschall et al. (2019a) the global gas production rate can be fairly well estimated by even simplified models. Our peak production rate is reached at the summer solstice (epoch 12) and not perihelion (epoch 11) and therefore roughly 22 days post-perihelion. This is in line with dust coma measurements by OSIRIS. Gerig et al. (2018) reported peak dust coma brightness 20 days post-perihelion. This also hints at the fact that the obliquity plays an important role in the activity of comets. Though the heliocentric distance still is the main driver of the gas and dust activity (O(1)) it is the obliquity/season that controls the second order. The coincidence of the peak gas activity with the peak dust activity also indicates that the dust activity is mainly driven by H 2 O or at least near-surface volatiles without a significant thermal lag. Figure 2. The top panel shows the global production rate for the gas (purple) and dust (green) as a function of days to perihelion. The bands indicate the range due to the diurnal variation. The gas production rates have been constrained by ROSINA/COPS measurements while the dust production rates are from combined constraints of OSIRIS and gas fluxes. For the dust a minimum size of r min = 0.1 µm and power-law exponent of q = 3.75 are assumed. The bottom panel shows the fraction of dust fall-back (purple) and dust-to-gas ratio (green). Table 3. List of OSIRIS images used in each of the epochs as well as their filter, central wavelength (λ c ), phase angle (α), and cometo-centric distance (D cc
Dust dynamic simulations
After the gas flow field has been evaluated, we calculate the dust flow field by injecting dust test particles into the flow. We use a typical approach for computing the dust motion in a gas flow-field taking into account gas drag and the comet gravity using our DRAG3D dust coma model detailed in Marschall et al. (2016) and the references therein. We assume that the dust mass production rate is proportional to the gas mass production rate and that the dust size distribution does not vary across the surface except in cases where certain dust sizes are no longer lifted because the gas pressure is too low to surpass the local gravity. The dust size distribution is thus only naturally modified by the dynamics and lifting process. It is assumed that the dust particles are at rest on the surface (i.e. the ejection velocity is 0). The dust-to-gas mass ratio as well as the dust size distribution at the surface are free parameters of the model and will be constrained by the data as described below. Due to the presence of gravity, large dust particles may not reach escape speed and eventually return to the surface. The flux of back-fall particles is thus a further output of the model. It is important to note that we assume that the dust particles are desiccated, i.e. contain no significant amounts of volatiles that evaporate while airborne. They may still be wet but do not outgas significantly. This is a consequence of our assumption that there is no significant back-coupling of the dust flow onto the gas flow.
For each epoch (except for two) we have selected one OSIRIS image where the illumination conditions of the image match one of the gas simulations (see Tab. 1). The images used in this work, as well as some camera and geometric properties, are shown in Tab. 3. Two main criteria were used to select these images. First, the images needed a large enough field of view such that projected distance (impact parameter, b) in the image plane from the centre of the comet to the edge of the image at each side was at least 9 km. Why this is an important constraint will be described in the next paragraph. Second, images need a sufficient signal to noise such that the dust coma brightness could be measured well. These two constraints unfortunately, eliminated all images for epoch 2 and 20. Epoch 2 included the 10 km orbit phase and thus did not provide large enough fields-of-view while the signal-to-noise was bad in epoch 20 due to the very low activity of the comet. Most images we have used were taken by the wide-angle camera (WAC) and filter 18 (central wavelength, λ c = 612 nm) and at cometocentric distances between 87 and 635 km and phase angles between 37 • and 108 • .
The dust field is calculated for each image using 41 different dust sizes from 10 nm to 1 m. The dust sizes are logarithmically spaced with five dust sizes per decade. The particles are assumed to be spherical and have a density of 533 kg m −3 matching roughly the bulk density of the nucleus (Preusker et al., 2017). Even though all dust sizes are simulated, not all of them contribute to the dust brightness in the coma. This is because the particles larger than a certain size might not all be lifted because the gas pressure cannot overcome gravity. Thus the number of dust sizes present in the coma depends on the heliocentric distance (epoch). The upper size limit (largest liftable size) is thus naturally determined and thus an outcome of the simulation. What the smallest dust size should be is unless. The smallest diameter of particle sub-units measured by MIDAS (Mannel et al., 2019) is 100 nm. Whether these could also be the smallest dust particles in the coma or if these measurements have an in-situ collection bias at the spacecraft is not clear. One could imagine that very small particles might not have been collected because of spacecraft and dust charging. Della Corte et al. (2019) showed that particles, for which the ratio of the particle charge to its kinetic energy entering the electrostatic field of the space craft q/E k > 0.24CJ −1 , will not reach the spacecraft. We will therefore leave this issue open for the moment and examine the impact of the smallest size on the results in Sec. 4.
Once the 3D dust field is simulated we calculate the dust column densities of each size for the specific viewing geometry of the respective OSIRIS image. The final image is composed by weighting the different dust sizes according to a specific dust size distribution and convolving the column densities with the scattering properties described in Sec. 2.4.
For each of the images we compare the integrated radiance of the dust coma along an aperture with impact parameter b = 11 km and compare it to that of the synthetic images. Again it is not our goal in this work to match the structure of the inner dust coma but rather the overall global behaviour. Gerig et al. (2018) showed from OSIRIS data that the dust flow goes over to free radial outflow at an average impact parameter of b ∼ 11 km. This is in line with theoretical considerations of dusty flows (Zakharov et al., 2018b). Beyond that point, the dust brightness falls off with 1/b as expected for a freely expanding radial flow. For that reason, we have chosen b = 11 km to be within the free-flow regime. If the field-of-view was not large enough we used the maximum available impact parameter.
Scattering model
Previously, we have used a spherical particle model and a Mie scattering code in our modelling pipeline. Here we use a much more sophisticated approach based on the recently introduced radiative transfer with reciprocal transactions framework (Muinonen et al., 2018;Markkanen et al., 2018b). The approach allows for scattering analysis of large irregularly shaped particles with wavelength-sized details. Here, the dust particles are considered to be irregular aggregates composed of sub-micrometre-sized organic grains and micrometre-sized silicate grains. Such a particle model has been found to be in good agreement with OSIRIS (Markkanen et al., 2018a) and VIRTIS (Markkanen and Agarwal, 2019) phase function measurements. The refractive index for silicate grains is assumed to be m = 1.6048692 + i0.0015341 corresponding to magnesium iron pyroxine (Dorschner et al., 1995) and for organic grains m = 1.55950 + i0.42964 corresponding to amorphous carbon (Jäger et al., 1998). At 612 nm (WAC filter 18) the resulting scattering phase functions for different particle sizes normalized to the geometric albedo are shown in Fig. 3. The figure shows good agreement of the phase function of large particles (> 1 cm) with the nucleus phase function as measured by OSIRIS (Fornasier et al., 2015;Feller et al., 2016;Masoumzadeh et al., 2017). This should indeed be the case because larger particles should behave more and more like "small comets" themselves and thus be representative of the nucleus scattering properties. For small particles, the best agreement of a single dust size with the coma phases function (Bertini et al., 2017) is between 10 and 100 µm. The numerical method of Markkanen et al. (2018a) is not applicable to particles smaller than 1µm. Thus for the particles smaller than 1µm we use a Mie scattering code to determine the scattering properties (see Marschall et al., 2016) matching the single scattering albedo of the Mie result with the approach of Markkanen et al. (2018a) for 1µm particles. This gives us a smooth transition from the large particle region to the Rayleigh scattering region where particle's shape has a negligible effect on its scattering properties. This is a state of the art model and we have thus used its results throughout this work. But because the scattering model does have an effect on the results a re-evaluation of the results can be done if and when a better model arises.
THEORETICAL CONSIDERATION
To put some of our results in the next section (Sec. 4) into context, we present first some general theoretical considerations of what we can expect, in particular with regards to the relationship between the dust-to-gas ratio and the dust size distribution. We thus consider first a simple model where the comet is represented as a sonic (i.e. the gas velocity near the surface is equal to the local sound velocity and defined by the thermodynamic properties of the gas and the surface temperature i.e. R h ) spherical source of ideal perfect gas (with specific heat ratio γ=1.33) accelerating spherical solid grains. The source shall have radius R N , nucleus mass M N , total gas production rate Q g (kg/s). The motion of a spherical grain in a flow from such a source was studied in Zakharov et al. (2018b) for a wide range of conditions. They defined and which are dimensionless parameters, where ρ d is the specific density of the dust particles, v g0 the gas velocity near the surface, v max g the theoretical maximal velocity of gas expansion (defined by the thermodynamic properties of the gas and the surface temperature i.e. R h ), and G the gravitational constant. Iv characterises the ability of a dust particle to adjust to the gas velocity while F u quantifies the importance of gravity. Zakharov et al. (2018b)) found that for Iv < 0.1 (which is the case of 67P, and dust sizes > 1 nm) the dust particles reach 90% of their terminal velocity at about 6 · R N . The terminal velocity of particles with radius, r, varies as v d (r) ∝ r −0.5 for small F u (i.e. if gravity plays a minor role). The asymptotic dust velocities are given by: where r * and v d (r * ) are some referential size and corresponding terminal velocity, and C Iv is a constant.
For a dust size distribution given by a power-law, r −q , the normalised mass distribution, f md , of particles ejected from the surface is where r min and r max are the smallest and largest dust sizes ejected from the surface. In the following we will not considered specially the case of q = 4. The dust production rate, Q d , of each dust size is where χ = Q d /Q g is the total dust-to-gas mass loss rate. Therefore, the number density of dust particles with radius, r, at the radial distance, R, from the centre of the nucleus is: The column density at the distance from the centre of the nucleus in the image plane is: The total number of dust particles in a column within a circular observing aperture of radius is: The brightness is proportional to the flux F (W/m 2 ) gathered by an instrument which for an optically thin coma is: where F is the incident flux, ∆ is observational distance, q sca is scattering efficiency and ϕ av is the phase function averaged over phase angle. Substituting Eqs. (3), (4) and (8) in (9) we get: For fixed F, Q g , R N , ρ d , v g0 , r * , v d (r * ), ∆ and F (r, ) = C 4 − q r 4−q max − r 4−q min χr 5 2 −q q sca (r)ϕ av (r)dr (11) where C = 3 32 FQg C Iv ρ d ∆ 2 is a constant (for the given observational conditions). For the optical properties, we make some simplifying assumption. First, we approximate the scattering efficiency q sca (r) to be: q sca (r) = 0.233 · 10 24 · r 7/2 , 10 −8 ≤ r < 2 · 10 −7 4.993 · 10 −5 · r −2/3 , 2 · 10 −7 ≤ r < 2 · 10 −4 0.02, 2 · 10 −4 ≤ r ≤ 1.0 (12) Figure 4 shows the computed q sca from Sec. 2.4, the fitted q f it scattering efficiency and the relative difference. In this fit, we used "round numbers" (i.e. this is a very rough fit). This simplification results in differences of < 50%. For the phase function ϕ av we assume it to be constant for all sizes. We estimate an error of the order of a factor of 2 from this simplification.
Under the assumption we made the integration of Eq. (11) becomes trivial. Figure 5. Dust-to-gas mass production rate ratio vs. power-law exponent for constant dust brightness.
Frontiers
For a given gas production rate Q g the maximum dust size a max is also constant. Fig. 5 shows how the dust-to-gas mass loss rate Q d /Q g varies as a function or the power-law exponent of the dust size distribution for the same brightness. With increasing power-law exponent q from minimal value to ≈ 3 the Q d /Q g is slowly decreasing (since in this case practically all dust mass is concentrating in a narrow range of largest sizes), but with increasing q from 3 to 4 the ratio Q d /Q g is strongly decreasing. For 4.5 < q < 6 Q d /Q g is increasing (within one order of magnitude). This inflection point of Q d /Q g occurs at the transition from dust grains distribution with most mass being in the large dust sizes to where most mass is in the small dust sizes.
The growth of Q d /Q g for q > 4.5 is a consequence of the strong decrease of q sca for small sizes, therefore, in order to maintain the same brightness, it is necessary to eject more dust.
We should remember that this analytical result (Fig. 5) assumed several important simplifications: 1. we assumed that the dust expansion is strictly radial; 2. for evaluation of the dust brightness we used simplified optical properties (e.g. isotropic phase function); 3. we assumed that gravity plays only a minor role; 4. we assumed that the dust does not affect the gas flow.
We will discuss in the next section how these assumptions (in particular (1) and (3)) change the result.
RESULTS AND DISCUSSION
To convolve the results of the dust dynamics model with the scattering properties to arrive at synthetic OSIRIS images we need to assume a dust size distribution. As is commonly done we presume that the number of particles, n, of a certain radius, r, follows a power-law: where q is the differential power-law exponent. Fig. 6 illustrates an example of an OSIRIS and synthetic image for epoch 12 (solstice). As described in Sec. 2.3, we extract the integrated brightness along a circle with a constant impact parameter of b = 11 km where possible (illustrated in the figure with the red circles). We should stress here again that it was not the aim of this work to match the emission distribution on the surface and thus all the structures in the coma. For a given gas production rate, the three major factors controlling the brightness (see Eq. (11) for more detail) of the dust coma are: 1. the dust-to-gas mass production rate ratio, Q d /Q g , at the surface; 2. the dust size distribution (i.e. the power-law exponent, q) at the surface; 3. the scattering properties of the dust particles.
We should note that although we assume a uniform surface (i.e. globally constant Q d /Q g and q) the actual values at each facet vary depending on the local gas flux. If a particular facets' local flux is too low to lift a certain particle size the resulting dust flux and size distribution from that surface facet will differ locally from the nominal values. The three input parameters above are not known a priori and are thus initially free parameters and in need of constraints. We have fixed the scattering properties by using published results that fit OSIRIS data (see Sec. 2.4 and Markkanen et al., 2018a). This reduces the above parameters from three to two.
There are three further quantities that influence the coma brightness, but as we will show below their influence is small compared to the ones mentioned above. These are: 1. the smallest dust size, r min ; 2. the largest dust size, r max ; 3. the bulk density of the dust, ρ d .
Of these three we will explore the influence of r min and ρ d on our results. We will not be artificially truncate the size range at large sizes by varying r max . On the contrary, r max will be naturally regulated due to the balance of forces at the surface. If a given local gas flux is not sufficient for lifting a certain size, that will determine the largest dust size from that surface element.
Apart from the parameters that directly influence the brightness, several indirect factors further constrain the curves Q d /Q g and q. We will discuss these constraints at the end of this section. Figure 7. The dust-to-gas mass production rate ratio, Q d /Q g as a function of the power-law exponent, q, is shown for each of the 18 OSIRIS images of this study. Each line represents an equal brightness curve where the respective q and Q d /Q g result in a synthetic image that matches the OSIRIS brightness. The colours of the curves indicate the global gas production rate of the respective epoch.
As has already been shown in Fig. 12 of Marschall et al. (2016) Q d /Q g and q are not independent. Knowing the brightness of the coma these two parameters constrain each other to a limiting set of parameter pairs. Fig. 7 shows Q d /Q g as a function of q for each of the 18 OSIRIS images of this study. Each line represents an equal brightness curve where the respective q and Q d /Q g result in a synthetic image that matches the OSIRIS brightness. Several things are noteworthy. First, all curves show minima between q = 4 and q = 4.5 and thus illustrate the inherent degeneracy between Q d /Q g and q. Second, all cases with shallow power-laws (q < 3) require very large Q d /Q g of at least 10 but in most cases around 100. Third, steep power-laws (4 < q < 6) in all but one case require much less dust mass, i.e. Q d /Q g ≤ 1 to match the brightness of OSIRIS. Fourth, there is a clear trend in the gas production rate. As the gas production rate increases the slope in Q d /Q g for shallow power-laws (q < 3) becomes shallow, too. Or conversely for low gas production rates very high Q d /Q g are needed to match the OSIRIS brightness when the power-law is shallow. This has to do with the amount of dust that can be lifted and escape the nucleus' gravity.
Comparing Fig. 7 to the analytical solution presented in Fig. 5 of Sec. 3 we see that for high gas production rates the model follows the analytical solution rather well. The places where we deviate from the analytical solution illustrate the effect of different physical processes. For the analytical solution we have assumed a minor (but not negligible) role of gravity. The effect of gravity can be seen in the low gas production rate cases with shallow power-laws. There, in contrast to the analytical model which levels off at smaller power-law exponents, the dust coma model results in ever higher Q d /Q g . This is caused by the inability to lift large particles from the entire surface and therefore a higher Q d /Q g is required to maintain the brightness. Thus the deviations at low gas production rates and shallow power-laws exhibit the non-minor role of the nucleus' gravity. As in the analytical model for steeper size distributions most mass is in the smallest particles, which are weakly scattering and thus hardly contribute to the brightness. This is compensated by an increase of Q d /Q g at these steep power-laws.
Compared to previous work presented in Fig. 12 of Marschall et al. (2016) the Q d /Q g values we find here (in particular for q < 3.5) are much higher while the behaviour of the curves for steeper power-laws is within the expected range. The two main reasons we find larger values at shallow slopes are: 1) Marschall et al. (2016) assumed the scattering properties of astronomical silicate (Laor and Draine, 1993) which is much brighter than we now know; 2) we consider here considerably larger dust sizes as our upper limit. This extension of the size domain increases the Q d /Q g by orders of magnitude because of high fall back fractions of dust that is gravitationally bound and weakly scattering.
Two assumptions going into Fig. 7 are worth discussing. First, we have assumed that all dust particles have a bulk density equal to the nucleus density (533 kg m −3 ). It is likely that the density of small particles is significantly larger than that and that the density then decreases with size. Because the exact relationship of the density as a function of dust size is currently unknown we have not tested a varying density as a function of size. But we have varied the bulk density for the entire range of dust sizes between 250 kg m −3 and 1000 kg m −3 . The two left panels of Fig. 8 show the results for a moderate activity environment (epoch 6 -inbound equinox, Q g = 35 kg s −1 ) and a high activity environment (epoch 12 -solstice, Q g = 800 kg s −1 ). For 3 < q < 3.75 the differences between the different dust densities is minimal. For q > 3.75 the differences are larger, in particular in the high activity case. How the bulk dust density impacts the total dust mass loss will be explored later in this section.
Second, we have currently assumed that the smallest dust size is 0.01µm. This might not be the preferred choice and a much larger smallest size should be considered. The MIDAS instrument detected 1µm particles (e.g Mannel et al., 2019) and there is indirect evidence of sub-micron particles observed by VIRTIS during outbursts . We have thus explored the range of the smallest sizes between 0.01µm and 1µm. The two right panels of Fig. 8 explore the effect of the smallest size on the dust-to-gas ratio by varying the smallest size. Compared to the differences seen for different bulk dust density the effect of the smallest size is quite substantial. As we would expect the smallest size does not affect the result for q < 3 as in these cases most of the mass is in the large particles. As q increases from 3 the curves for different smallest sizes start diverging. Two trends can be observed. As the smallest size increases from 0.01µm to ∼ 0.1µm the dust-to-gas ratio starts to flatten out beyond q = 4. This is caused by the fact that the size distribution is no longer dominated by very inefficiently scattering particles. As the smallest size continues to increase to 1µm the overall dust-to-gas ratio increases. This is because the most efficient scatterers (see Fig. 4) are being removed from the size distribution and must be compensated by more mass of all other sizes. For very steep power-laws the difference in the dust-to-gas ratio can be up to 1.5 orders of magnitudes. How the smallest size impacts the total dust mass loss will be explored later in this section.
How the fraction of gravitationally bound dust mass, which falls back to the nucleus, varies as a function of global gas production rate is shown in Fig. 9 for different power-law exponents. This illustrates that for very low gas production rates and very shallow power-laws (q < 2.5) almost the entire dust mass emitted from the surface will be redeposited. This explains the large increase seen in Q d /Q g of Fig. 7. Conversely, in the case of steep power-laws (q ≥ 4.5) almost all of the dust escapes the nucleus' gravity field irrespective of the gas production rate. In all cases, the fraction of fall back decreases as the gas production rate increases. Therefore, the fraction of fall back material decreases as the comet approaches the Sun. At large heliocentric distances, large fractions of dust emitted will return to the surface (i.e. > 50% for q < 3.5). But the gas and dust production rates are highest at perihelion/solstice, thus the total amount of fall back during one apparition is dominated by the fraction of fall back during that period. Figure 9. The ratio of dust mass falling back, Q D f b to total dust mass, Q D is shown as a function of global gas production rate for different power-law exponents.
The fraction of fall back is also tightly bound to the maximum liftable dust size. Fig. 10 shows as a function of global gas production rate the largest dust size that can still be lifted from the surface of the nucleus. The figure also shows the largest dust size that can escape the gravity field of the comet. As the gas production rate increases so do the largest liftable and escaping dust sizes. For Q g > 300 kg s −1 the largest liftable dust size is larger or equal to 1 m, which is the largest size in our model. Though these sizes, or larger, can be lifted they will not be able to escape the gravity field of the comet and will be redeposited on the surface. The largest size that can escape the comet at peak gas production is roughly 0.6 m. We should note though that this calculation neglects surface cohesion, solar radiation pressure, and heat transport to the subsurface that is needed to eject such large particles. Here we only consider the balance of gas drag and gravity to determine these largest sizes.
The discussion of the previous paragraphs illustrates that multiple properties of the dynamical simulation of the dust coma (size distribution, dust-to-gas ratio, and the fraction of fallback) as well as the optical properties of the dust are not independent but mutually constraining. E.g. a given fraction of fallback implies a certain size distribution which in turn constrains the possible dust-to-gas ratios for a particular set of scattering properties. Though for a particular single OSIRIS image these parameters can be constrained there still remains a rather large set of parameters that are consistent with the data as presented to this point (including dust coma brightness in the OSIRIS images and local gas densities of ROSINA/COPS).
While we have only considered constraints within each epoch there is one strong constraint covering the entire mission. That is the measurement of the total mass loss during the Rosetta apparition. During Figure 10. The largest liftable dust size (red curve) and the largest escaping dust size (blue curve) are shown as a function of the gas production rate.
the 2 year mission comet 67P had lost (10.5 ± 3.4) · 10 9 kg (Pätzold et al., 2019). The total mass loss, M tot = (10.5 ± 3.4) · 10 9 kg, is: where M g is the total volatile mass loss, and M esc d is the total escaping dust mass. For the dust masses, we can further specify that where M d is the total dust mass ejected from the nucleus, and M f b d is the dust mass that falls back to the surface. We have determined the total volatile mass loss to be (6.1 ± 1.5) · 10 9 kg. Combined with the total mass loss of the nucleus it follows that M esc d = (4.4 +4.9 −4.4 ) · 10 9 kg. Note that within this interval exists the possibility that M esc d = 0 kg. Though we know that dust escaped from the nucleus the simple mass balance would not exclude this possibility. We can now integrate the total dust mass loss over the orbit of the comet for different power-law exponents. For the integration, we assume a linear interpolation of the results between epochs. Figure 11 shows the M esc d as a function of the power-law exponent, q. Cases, where M esc d exceeds the nominal dust mass loss of 4.4 · 10 9 kg (horizontal dashed green line) or the maximum dust mass loss of 9.3 · 10 9 kg (horizontal dashed red line), can be discarded. Furthermore, where the mass loss curve intersects the mass loss indicates the corresponding power-law that fits the data. Figure 11 also illustrates the effect of the smallest size -discussed earlier in more detail for an individual OSIRIS imageon the total mass loss. The effect of the smallest size is rather limited for 0.01µm < r min < 1µm because the dust mass curves cross between 3.5 < q < 4. This also implies that the effect of the bulk dust density is even smaller than the effect from the choice of the smallest size (see discussion about Fig. 8 above). We can also see that for r min >∼ 12µm there will no longer be a nominal solution to the constraints. Further, for r min >∼ 30µm there is no solution at all because the curve will stay above the maximum escaping mass for all power-law exponents studied here. This means that the minimum dust size must be strictly small than ∼ 30µm and nominally even smaller than ∼ 12µm. Fig. 11 illustrates how we can determine the power-law exponent for the nominal and maximum dust mass loss, which in turn determines the dust-to-gas ratio, dust production rates, fraction of dust fallback. As the minimum size grows larger than 1µm the required power-law exponent increases and becomes rather large. There remains the issue of the minimum escaping mass. As discussed above the lower limit according to the total and volatile mass loss is zero. But for our models, the minimum escaping dust mass is never zero. We have thus chosen the smallest possible mass loss of each model as the minimum mass loss. The resulting power-law exponents, dust mass losses, dust-to-gas ratios, and fall back fraction are summarised in Tab. 4. We have also determined the deposition height, H, that results if the fallback material is spread equally on the smooth deposits (9.43 km 2 ) identified by Thomas et al. (2018). Figure 11. The total escaping dust mass, M esc d , is shown as a function of the power-law index for five different minimum dust radii, r min . The horizontal dashed lines show the nominal ejected dust mass (green) and the maximum ejected dust mass (red).
The results in Tab. 4 show that the integrated quantities are rather insensitive to the choice of the smallest dust size if r min ≤ 1µm. For minimum sizes larger than 1µm the power-law becomes steeper and thus the amount of dust fall-back goes down. The dust-to-gas ratio is rather stable for all cases and is of the order of 0.8 with an error of the order of 100%. This means that while the nominal case reflects a comet that contains more volatiles than dust the case of a dusty comet lies within the error. Table 4. Power-law exponents, dust mass loss, dust-to-gas ratio, and fall back as a function of the smallest dust size (see Fig. 11) . Dashed entries mean that no solution is possible for this size.
This analysis assumes that the dust size distribution does not change along the orbit. There is an indication (e.g. Merouane et al., 2017) that this is not the case and that the slope is varying with heliocentric distance. Our model cannot resolve/constrain this. All the quantities here are heavily dominated by the period around perihelion and summer solstice when the emission was the highest. Therefore, the power indexes found here reflect the values for this period.
The power-law we find to be compatible with the data is an independent result based only on the brightness of the dust coma and the total mass loss balance. Because most mass is ejected around perihelion, this power-law mainly reflects this period and deviations of it at larger heliocentric distances would not influence the result. The value we find is in line with other measurements around perihelion e.g. the in-situ measurement of q = 3.7 by GIADA , q = 3.8 by COSIMA (Merouane et al., 2017), as well as ground-based estimates for the dust tail of 3.6 < q < 4.3 for sizes smaller than 1 mm and q = 3.6 for sizes larger than 1 mm .
A check of our dust dynamics model is the comparison of our model dust speeds with the ones measured by GIADA. For the period between 2.2 AU inbound to 2.0 AU outbound Della Corte et al. (2016) have reported 141 dust particle detection for which a dust speed and mass could be determined. Of these, the smallest particle had a mass of 2.8 · 10 −9 kg, which corresponds to a radius of 108 µm assuming a spherical particle with our nominal dust density. The measured dust speeds varied between 0.3 and 34.8 m s −1 . A further constraint is the fact that Rosetta spent ∼ 65% of the time at phase angles of ∼ 90 • and an additional ∼ 25% of the time at phase angles of ∼ 60 • which implies that the particles were mainly collected in those locations (see also Fig. 5 in Della Corte et al., 2016). At a phase angle of 90 • our model dust particles with radius 100 µm have speeds of (3.5 ± 1.0) m s −1 at the inbound equinox (epoch 6) and (18 ± 5.6) m s −1 at the summer solstice (epoch 12). For phase angles of 60 • the model dust particles have speeds of (7.0 ± 1.2) m s −1 at the inbound equinox and (32 ± 5.2) m s −1 at the summer solstice. Our dust speeds are thus well in line with the measured speeds by GIADA given that larger particles will have lower speeds than the ones listed above.
We should highlight that our peak dust production rate (∼ 530 kg s −1 ) is roughly an order of magnitude lower than those reported by e.g. Moreno et al. (2017) (∼ 3000 kg s −1 ) or Ott et al. (2017) (∼ 8300 kg s −1 ). Furthermore, Moreno et al. (2017) report a total dust mass loss of 1.4 · 0 10 kg. As neither Moreno et al. (2017) nor Ott et al. (2017) report any error bars on their results, we cannot asses if they are plausible. If taken at face value both results are inconsistent with the RSI measurement of the total mass loss of the comet (Pätzold et al., 2019) taking into account the estimates of the volatile mass loss in this work and others (Combi et al., 2020;Läuter et al., 2018).
Finally, the determination of the power-law exponent allows us to determine the dust production rate (Fig. 2, top panel, green band), dust-to-gas ratio (Fig. 2, bottom panel, green line), and fraction of fallback (Fig. 2, bottom panel, purple line) as a function of time. The dust production rates are linearly interpolated between the epochs. Unfortunately, our model is rather noisy but the overall trends are robust enough that we feel comfortable making further conclusions. The fraction of dust fallback is highest at large heliocentric distances and then decreases towards perihelion and reaches its minimum at summer solstice where the activity peaked. Though the faction of fallback is smallest at the peak of the activity (solstice), most mass that is falling back will still be from the period of summer solstice because of the high activity. The behaviour of the fraction of dust fallback is symmetric for the inbound and outbound part of the comets' orbit. Contrary to that the dust-to-gas ratio is highest (∼ 1.5) at large heliocentric distances inbound and keeps decreasing along the entire orbit and does not significantly increase on the outbound leg but rather flattens out at ∼ 0.1. This might be indicative of the comet shedding its dust mantle, in particular in the northern hemisphere. This trend of decreasing dust-to-gas ratio along the orbit manifests itself also in the asymmetry of the global dust production. To first order, the dust production rate follows the gas production rate during the inbound leg but the dust production rate drops faster than the gas production rate post solstice. This is also observed in ground-based measurements . There is also an intriguing spike in the dust-to-gas ratio after the inbound equinox coinciding with an increase in the total dust production rate. Future in-depth work will be needed to confirm the nature of this feature which does not seem to be present in the observations of the outer coma from ground-based measurements. But if it is truly there it can be understood as the comet shedding its southern dust mantle because the feature coincides with the period when the southern hemisphere receives increasing insolation.
SUMMARY AND CONCLUSIONS
In this work, we have simulated the inner gas and dust coma of comet 67P covering the entire Rosetta mission by splitting it into 20 epochs. The gas production rates of each epoch were constrained by in-situ measurements of the gas density by ROSINA/COPS. From that, the total gas mass loss is estimated at (6.1 ± 1.5) · 10 9 kg. This is in line with values published in other works as e.g. (6.3 ± 2.0) · 10 9 kg (Combi et al., 2020) or (5.8 ± 1.8) · 10 9 kg (Läuter et al., 2018). It also illustrates that it is not necessary to know the surface-emission distribution well to estimate the total global volatile loss.
By simulating synthetic OSIRIS images of the dust coma we showed how the dynamical and optical properties of the dust can be constrained. In particular, we showed how the dust-to-gas mass production rate ratio, Q d /Q g , the power-law exponent, q, the fraction of dust fall back, Q f b d , and the scattering properties are inter-related and constrain each other. Because these parameters are not independent they need to be fit simultaneously. E.g. the lowest mass needed to match the brightness of the dust coma as observed by OSIRIS is achieved with power-law distributions with exponents between 4 and 4.5. Using the constraint of the total mass loss of the comet during the 2015 apparition we were able to show that only a narrow parameter set fits all observations. We determined that power-laws with q = 3.7 +0.57 −0.078 are consistent with the data. This results in a total of 5.1 +6.0 −4.9 · 10 9 kg of dust being ejected from the nucleus surface, of which 4.4 +4.9 −4.2 · 10 9 kg escape to space and 6.8 +11 −6.8 · 10 8 kg (or an equivalent of 14 +22 −14 cm over the smooth regions) is re-deposited on the surface. This leads to a dust-to-gas ratio of 0.73 +1.3 −0.70 for the escaping material and 0.84 +1.6 −0.81 for the ejected material. Further, the minimum dust size must be strictly smaller than ∼ 30µm and nominally even smaller than ∼ 12µm. We have found that these results are robust with respect to varying the smallest dust size between 0.01 − 1µm and variations in the bulk density of the dust between 250 − 1000 kg m −3 .
It remains an open question as to how dust particles are lifted/ejected from cometary surfaces (see e.g. Vincent et al., 2019). Furthermore, a more detailed study of the change in the dust size distribution with heliocentric distance would be of great interest and could refine the work presented here. Finally, comprehensive work on estimating the amount of dust deposition through e.g. local digital terrain modelling (e.g. method by Jorda et al., 2016) would provide valuable additional constraints.
AUTHOR CONTRIBUTIONS
RM performed the modelling of the gas and dust coma as well as the comparisons with ROSINA/COPS and OSIRIS and the analysis related to that. JM performed the calculations of the scattering properties of the dust particles. SBG implemented new features that optimise DRAG3D. OPR produced the unstructured simulation grid within which all UltraSPARTS and DRAG3D were run. NT wrote the IDL programs for reading and analysis of the OSIRIS images. JW provided support for running and optimisation of UltraSPARTS.
FUNDING
Raphael Marschall acknowledges the support from the Swiss National Science Foundation grant 184482. Johannes Markkanen acknowledges the support from ERC Grant No. 757390. The team from the University of Bern is supported through the Swiss National Science Foundation, and through the NCCR PlanetS. Table 5. The mean gas production rate,q g [kg s −1 ] as a function of ephemeris time (ET): q g (ET ) = a · ET 2 + b · ET + c epoch a b c | 13,328 | 2020-05-27T00:00:00.000 | [
"Physics",
"Environmental Science"
] |
A general mathematical method for predicting spatio-temporal correlations emerging from agent-based models
Agent-based models are used to study complex phenomena in many fields of science. While simulating agent-based models is often straightforward, predicting their behaviour mathematically has remained a key challenge. Recently developed mathematical methods allow the prediction of the emerging spatial patterns for a general class of agent-based models, whereas the prediction of spatio-temporal pattern has been thus far achieved only for special cases. We present a general and mathematically rigorous methodology that allows deriving the spatio-temporal correlation structure for a general class of individual-based models. To do so, we define an auxiliary model, in which each agent type of the primary model expands to three types, called the original, the past and the new agents. In this way, the auxiliary model keeps track of both the initial and current state of the primary model, and hence the spatio-temporal correlations of the primary model can be derived from the spatial correlations of the auxiliary model. We illustrate the agreement between analytical predictions and agent-based simulations using two example models from theoretical ecology. In particular, we show that the methodology is able to correctly predict the dynamical behaviour of a host–parasite model that shows spatially localized oscillations.
Generator L R,C,P describes the following random event. Let, at a moment of time t ≥ 0 the system is given by a configuration γ t . The event is that, within a small time-interval [t, t + δt], a group of reactants {x i 1 1 , . . . , x iR R } disappears from the configuration and a group of products {z l 1 1 , . . . , z lP P } will become a part of the configuration, so that z 1 ∈ Λ 1 , . . . , z P ∈ Λ P for some disjoint bounded subsets Λ 1 , . . . , Λ P of R d . Thus, γ t+δt = γ t \ {x i 1 1 , . . . , x iR R } ∪ {z l 1 1 , . . . , z lP P }. The probability of this event is then δt · δt = 0. The influence on catalysts y j 1 1 , . . . , y jC C reflects the interaction between agents. The catalysts remain unchanged within the event, however, they influence the probability of the event.
We include also the case when, for some m, n, a reactant x m im and a product z n ln are such that x m = z n , whereas i m = l n , i.e. when an agent keeps its position with changing its type only. In this the corresponding integral w.r.t. dz n is omitted. We can also formally treat this as like the function r includes the factor δ(x m − z n ); henceforth δ(x) is the Dirac delta-function.
The dynamics of γ t if defined then through the differential equation: (1.5) which should be satisfied for a large class of functions F .
Spatial correlation functions and cumulants
Definition 1.1. For each i ∈ I N , a function k i t (x) ≥ 0 is said to be the first order spatial correlation function of type i (for the distribution of γ t ), if for any function g 1 (x) ≥ 0, Henceforth, E[·] denotes the expected value of a random quantity (w.r.t. the distribution of γ t ).
The function k i t (x) is also called the density of agents of type i, since, taking g 1 (x) = 1 1 Λ (x) for some bounded subset Λ of R d , where we get from (1.6) that Henceforth, |η| denotes number of points in a finite subset η of R d .
Definition 1.2. For each i, j ∈ I N , a function k i,j t (x 1 , x 2 ) = k j,i t (x 2 , x 1 ) ≥ 0 is said to be the second-order spatial correlation function (between agents of the types i and j), if, for any symmetric function g 2 (x 1 , x 2 ) ≥ 0, (1.7) Remark 1.3. Recall, we assume that agents cannot occupy the same position, hence, for i = j, γ i t and γ j t are disjoint, and thus the restriction x 1 = x 2 in (1.7) is redundant then.
Combining (1.7) with (1.6), we can also write, for all i, j ∈ I N , Henceforth, 1 1 i=j denotes the Kronecker delta (that is 1 if i = j and 0 otherwise). Substituting to (1.8) the symmetric function where Λ 1 , Λ 2 are bounded subsets of R d , we get (1.10) One can also consider the centralized spatial moment that is the expectation of the product of centralized random quantities |γ i t ∩ Λ 1 | − E[|γ i t ∩ Λ 1 |], i ∈ I N (called so because the expectation of each such quantity is 0): Definition 1.4. The function (1.11) is called the second order spatial cumulant between types i and j.
We have hence (1.12) We going to define now a general spatial correlation function.
Remark 1.7. If N = 1, so that i 1 = . . . = i n = s 1 , then we will normally use the notation: k In particular, k (1) t (x) := k s 1 t (x). We can also rewrite then (1.13) as follows, t (x 1 , . . . , x n ); dx 1 . . . dx n . and the spatial correlation function k (n) t is also called the n-th order spatial factorial moment. Note that k (n) t is a symmetric function.
To define n-th order spatial cumulants, we note that [i 1 , . . . , i n ] is called a multiset, i.e. a collection of n (possibly repeating) elements from I N .
Definition 1.8. We set u i t (x) := k i t (x), i ∈ I N , and define spatial cumulants through the equality Remark 1.9. To see that (1.14) indeed defines spatial cumulant u t for given spatial correlation functions k t , note that the right hand side (r.h.s. henceforth) of (1.14) contains the term with m = 1 which is just u i 1 ,...,in Differential equations for spatial correlation functions can be obtained from (1.5) by using the definition (1.13). Namely, we take as F in (1.5) the integrand in the left hand side (l.h.s. henceforth) of (1.13), i.e. F = F n , where F (γ t ) = F n (γ i 1 t , . . . , γ in t ) = where g n is a symmetric function such that, for some bounded subset Λ of R d , g n (x 1 , . . . , x n ) = 0 if only x m / ∈ Λ for some 1 ≤ m ≤ n. Differentiating both part of (1.13), we will get then from (1.5) that where, recall, F = F (g n ).
The next step is to represent where g m are also symmetric functions depending on g n , and types j 1 , . . . , j m ∈ I N ; they all depend on the particular form of the operator L; in the case of an RCPgenerator, g m and types depend on the rate (1.2). Note that then the summation in m is finite. We will get then, by (1.13), Since F n depends on g n linearly and LF depends on F linearly, we have that L m,n g n := g m depend on g n linearly as well. By considering a dual operator L n,m := ( L m,n ) * , we will get that Since g n was arbitrary, we get then Considering an infinite vector k t of all functions k i 1 ,...,in t indexed by n ≥ 1 and by different multisets [i 1 , . . . , i n ] of types, we can treat the r.h.s. of (1.15) as the action of an infinite matrix L , whose entries are operators L n,m .
Stress that, typically, m can take values larger than n, so that the system of linear differential equations (1.15) is not closed and cannot be solved analytically nor numerically.
The explicit form for the action of L in case of the RCP-generator L, given by (1.3), can be found in [1,Supplementary Note 1].
The differential equations for spatial cumulants can be obtained by substituting (1.14) into (1.15). The equations will have a similar form with, however, nonlinear operators Q n,m . For their explicit form, in the case of L given by (1.4), we also refer to [1, Supplementary Note 1].
Beyond mean-field expansion for spatial dynamics
Equation (1.15) has initial conditions at, say, time t = 0: k i 1 ,...,in 0 (x 1 , . . . , x n ). The important class of such initial conditions are product functions where q i 1 0 , . . . , q in 0 are nonnegative functions on R d . Spatial correlation function (1.16) corresponds to the Poisson distribution of configurations. The characteristic feature of the Poisson distribution is that random numbers are independent for all disjoint bounded subsets Λ 1 , . . . , Λ n of R d ; in particular, all corresponding spatial cumulants of an order more than 1 are equal to 0, cf. (1.12). The Poisson distribution is also called chaotic because of the mentioned independence.
In most cases, however, the solution to (1.15) with the initial condition (1.16) does not have a product structure. The idea of the mean-field approximation (with a small parameter ε > 0) is to find a modification L ε of the Markov operator L in (1.5), such that the solution k i 1 ,...,in would be approximately (up to certain order of ε) equal to a product function. Hence the distribution of γ ε,t would be approximately chaotic, in a certain sense. This is called the propagation of chaos in statistical physics. The realization of the scaling procedure for the RCP-generator is as follows. We assume that r in (1.2) is given through combinations of various kernels of the form (1.18) where v, w ∈ R d , k, m ∈ I N , a k,m ≥ 0 is a function on R d . Here v k , w m are some agents among reactants x i 1 1 , . . . , x iR R , catalysts y j 1 1 , . . . , y jC C or products z l 1 1 , . . . , z lP P . We consider L ε given by (1.4) where r ε,R,C,P has the same structure as r R,C,P , however, the kernels a(v k , w m ), given previously by (1.18), are replaced now by i.e. the scaled kernels have the same full integral but a scaled (expanded) shape.
Next, we consider the initial condition to the corresponding equation (1.17), as follows (1), (1.20) where lim ε→0 o(1) = 0 (in particular, one can consider the initial condition without that o(1) at all). The statement is that then the solution to (1.17) has the property where q i t , i ∈ I N , solve a system of (nonlinear) differential equations where q t is the vector of all q s 1 t , . . . , q s N t ; with certain (nonlinear) mappings H s 1 q , . . . , H s N q . For the exact form of H i q , i ∈ I N , we refer to [1,Supplementary Note 1]. By (1.21), the cumulants of all orders bigger than 1 corresponding to the function k i 1 ,...,in ε,t (x 1 , . . . , x n ), n ≥ 2, through expansion (1.14) are equal to o(1). In particular, cf. (1.11), The term o(1) in (1.21) depends in a non-trivial way on both time t, variables x 1 , . . . , x n and types i 1 , . . . , i n . To partially reveal this dependence, one needs the next term of the expansion. It was shown in [1,Supplementary Note 1], that Here q i t satisfies (1.22) and p i t , g i,j t satisfy certain linear differential equations • p t is a vector of all p i t , i ∈ I N ; and g t is the vector of all g i,j t , i, j ∈ I N ; • mappings H i p [q t ] and H i,j g [q t ] depends on q i t in a nonlinear (in general) way.
One can also get then from (1.23) the following enhancement of (1.21) for n = 2: Space-homogeneous case Consider the special case, where, initially, the density does not depend on space and the pair-correlation is translation invariant, namely: (1.28) Then if the operator L ε has the form (1.4) with r R,C,P in (1.3) replaced by r ε,R,C,P which is a combination of pair-interaction kernels as above, then, for all t ≥ 0, where q i t , i ∈ I N , satisfy the system (1.22) of ordinary differential equation, and (see [1,Supplementary Note 1,formula (241)]) the equation (1.25) can be rewritten in terms of the Fourier transform of functions g i,j t (x), defined by where x · ξ denotes the standard dot-product in R d and i 2 = −1. Namely, g i,j t (ξ) satisfies the following differential equation, for each ξ ∈ R d , Here, similarly to above, the result is a function of ξ; i ∈ I N , in general, nonlinearly. When i, j run over I N , the system of equations (1.30) can be read as a linear nonhomogeneous system of (ordinary) differential equation (considered independently for each value of ξ). Since all q i t , i ∈ I N , are known, one can solve (1.30) explicitly.
Spatiotemporal characteristics 2.1 Spatiotemporal correlations
By (1.13), spatial correlation function k i 1 ,...,in t (x 1 , . . . , x n ) characterizes the probability to find n agents of types i 1 , . . . , i n of the configuration γ t in vicinities of positions x 1 , . . . , x n ∈ R d , respectively. It is naturally also important to characterize the similar probability when agents appear in those vicinities at different moments of time.
We restrict ourselves to two moments of time only: t ≥ 0 and t + ∆t for some ∆t ≥ 0. Moreover, we consider the second order spatiotemporal correlations only. Namely, we are interested to find, for each i, j ∈ I N , a function k i,j t,∆t (x 1 , x 2 ) ≥ 0, such that, for each symmetric It it worth noting that, as we will see below, To obtain k i,j t,∆t , we proceed as follows. Recall, we consider dynamics of For each i ∈ I N , we consider auxiliary dynamics of three configurations γ iO ∆t , γ i+ ∆t , γ i− ∆t , which will be created at the moment t and will have 'own local time' ∆t ≥ 0. Namely • γ iO ∆t contains all agents of the considered system which were present in the system at time t having type i; didn't change their positions nor types within the time interval [t, t+∆t], and hence they are still present in the system at time t + ∆t having type i; • γ i+ ∆t contains all agents of the considered system which appeared in the system within the time interval [t, t + ∆t] having type i; didn't change their positions nor types after that, and hence they are still present at the system at time t + ∆t having type i; • γ i− ∆t contains all agents of the considered system which were present in the system at time t having type i; do not present in the system at time t + ∆t: namely, each of such agent, within the time interval [t, t + ∆t], either disappeared from the system or changed its position and/or type.
We have hence Therefore, our full auxiliary dynamics is i.e. it contains agents of 3N types (recall that a type is just a label). We set (2.6) Recall also that there are two notations to represent configurations, see (1.1), hence, we can also write where, for A ∈ {O, +, −}, Next, by (2.4), we can rewrite the l.h.s. of (2.1) as follows and using (1.7) and Remark 1.3 for (2.5), one can continue Therefore, by (2.1), however, by (2.8), in general, (2.2) holds.
Dynamics of the auxiliary model
To study the dynamics of γ ∆t , we need to consider a modification of (1.5): with an appropriate modification L of L given by (1.4). Namely, we need that • a reactant x iO does not just disappear from γ O ∆t , but changes its type becoming • a reactant x i+ just disappears from γ + ∆t (since then this agent did not exist at time t and will not exist at time t + ∆t); • products may be of the type '+' only; a product z i+ just appears in γ i+ ∆t ; • the event should happen with the same rate as for L, but applied to the union of O-catalysts and +-catalysts (as they all present at the system on the time interval [t, t + ∆t]); • agents of the type '−' do not perform own dynamics (hence they appear because of the transformation from O-reactants only).
Let R, C, P be fixed and L R,C,P be given by (1.3). It means that there are still R reactants, some of them are O-reactants (denote their number by r, so that 0 ≤ r ≤ R), the rest are +-reactants, namely, there are R − r ≥ 0 of +-reactants. Next, there are P products, all are +-products by the above. Finally, C catalysts should be chosen from γ O ∆t ∪ γ + ∆t ; let, similarly to reactants, there be c O-catalysts (0 ≤ c ≤ C) and hence C − c ≥ 0 +-catalysts.
As a result, we will get Naturally, we also set Remark 2.2. It may be also convenient to use another style of writing. Namely, we will interpret now γ ∆t as the union: rather than as the the tuple (2.7). Then, for
Beyond mean-field expansion for spatiotemporal dynamics
Let L ε be given by (1.4) with r R,C,P in (1.3) replaced by (1.19) as it is described in Subsection 1.3. Let, initially, γ ε,0 be distributed so that the corresponding correlation functions has the form (1.20) for certain fixed collection of functions q i 0 , i ∈ I N . Let γ ε,t and γ ε,t+∆t be the corresponding random configurations at times t and t + ∆t, respectively.
We consider the corresponding auxiliary dynamics distributed according to the generator L ε obtained from L ε by an analogy to that done in Subsection 2.2, in particular, by (2.3), . , x n ), ı 1 , . . . , ı n ∈ I N , be the corresponding system of correlation functions.
Recall that, cf. Remark 2.1, for i, j ∈ I N , Space-homogeneous case Consider again the special case where (1.28) holds. By (2.3), the auxiliary (and scaled by ε) dynamics will inherit that property as well: for all ı, ∈ I N , k ı ε,∆t will not depend on a space coordinate, and k ı, ε,∆t (x) (and hence u ı, ε,∆t (x), g ı, ∆t (x)) will depend on one space coordinate only. Rewriting the formulas above, one gets and where, initially, (2.35) By using (1.30) with i, j ∈ I N replaced by ı, ∈ I N , we get differential equations for all g ı, ∆t (ξ) = g iA,jB ∆t (ξ), A, B ∈ {O, +, −}, with coefficients dependent on q ı t . Solving the obtained system of differential equations, one can find g i,j t,∆t (ξ) by (2.32). However, we are interested to simplify the computations by finding a differential equation on g i,j t,∆t (ξ). We are going to formulate now a conjecture which can be verified for various models (in particular, for the considered below). We are going to prove it in a forthcoming paper.
To formulate the conjecture, we consider auxiliary functions on R d : By (1.30) and (1.22), we get that the vector h t = (h i,j t ) i,j∈I N satisfies a nonhomogeneous system of linear differential equations: where, similarly to above, A i,j [q t ](·) is a multilinear mapping, calculated here at the vector h t , and B i,j [q t ] is a function; both depend on q i t , i ∈ I N , nonlinearly (in general).
Conjecture. Consider another auxiliary functions on
recall that q iO ∆t depends on t. Then the vector h t = (h i,j t,∆t ) i,j∈I N satisfies a homogeneous system of linear differential equations: The system of linear equations (2.39), can be solved in matrix form (or, rather, tensor form, as vector h t,∆t is two-dimensional). Note that the initial condition to (2.39), when ∆t = 0, can be obtained, by (2.38), (2.33), (2.35), (2.32), as follows: Next, if i = j, one has to find q iO ∆t (that can be often done explicitly), and get g i,j t,∆t (ξ) from (2.38). Finally, one has to take the inverse Fourier transform, to obtain g i,j t,∆t (x); the latter, of course, can be done only numerically. As a result, one gets an approximate value of u i,j ε,t,∆t (x) from (2.31).
3 Case study 1: Spatial and stochastic logistic model
Spatial characteristics
We consider agents of one type, i.e. N = 1. Let L be given through some of three operators, cf. 1.4: Here m > 0 is a constant, and a ± (x) ≥ 0 are kernels such that We denote also We will always assume that A ± > 0, i.e. it is not the case that a ± (x) = 0 for almost all (a.a. henceforth) x ∈ R d . Operator L 1 describes that any catalyst at x ∈ γ may create a product at y ∈ R d (send an off-spring to y) according to the dispersion kernel a + ; L 2 describes that any reactant at x ∈ γ may disappear with an density independent mortality m; L 3 describes that any reactant at x ∈ γ may also disappear because of competition with catalysts at y ∈ γ \ {x} given through the competition kernel a − .
Following the scheme above, we consider L ε with a ± (x − y) above replaced by ε d a ± (εx − εy); next, we consider the dynamics of γ ε,t defined by (1.5) ε,t (x 1 ) and k (2) ε,t (x 1 , x 2 ) be the corresponding first-and second-order correlation functions, and let u be the corresponding first-and second-order cumulants. Consider the space homogeneous case. Then, by e.g. [5], Function q t , cf. (1.22), satisfies the mean-field equation which can be solved explicitly: ( 3.4) If we assume, additionally, that we obtain, see [3], an equation for the Fourier transform of g t (x), namely Equation (3.3) has two stationary solutions q t ≡ 0 and q t ≡ q * , where We will always assume that i.e. that q * > 0; otherwise, by (3.4), lim t→∞ q t = 0, i.e. the population would extinct.
Under (SL 1 ), we have lim By (3.1), J t is integrable; as a result, (3.5) holds with g 0 replaced by g t . In particular, cf. (1.29), According to (2.36), we define also By (3.6) and (3.3), is just a multiplication operator given by, cf. (3.7), for a function f : R d → R.
We will consider below the stationary regime, when t → ∞. We define, for a.a.
We will assume, additionally to (SL 1 ), that there exists α > 0, such that Since, for an integrable function f ≥ 0, one has, by (3.15) and (SL 1 ), the following sufficient condition for (SL 2 ): It was shown in [3], that if (SL 1 ), (SL 2 ), (3.10) and (3.5) hold, then there exists Surely g * (ξ) is just the stationary solution to (3.6), i.e. it satisfies (3.6) with the left hand side replaced by 0. It was also shown in [3] that the inverse Fourier transform g * (x) of g * (ξ) is just the pointwise (and even uniform) limit of g t (x) as t → ∞.
Spatiotemporal characteristics
We consider the auxiliary dynamics of γ t = (γ O t , γ + t , γ − t ) described by the generator where L 1 , L 2 , L 3 are defined according to the rules postulated in Subsection 2.2.
i.e. both O-reactants and +-reactants may produce +-products. Next, in the counterparts of L 2 and L 3 , O-reactants become −-products, whereas +-reactants just disappear. Therefore, and since there are both O-and +-catalysts, we have Following the general scheme, we consider L ε with a ± (x − y) above replaced by ε d a ± (εx − εy); next, we consider the dynamics of γ ε,t defined by (2.18) ∆t , A, B ∈ {O, +, −} be the corresponding functions from the beyond mean-field expansion.
One can now solve, for each ξ ∈ R d , a linear ordinary differential equation (3.24) with the initial condition where h t (ξ) is given by (3.12). Then, one can get g t,∆t (ξ) from (3.21); to this end, one needs q O ∆t . The latter function satisfies the following differential equation (again, see Subsection 3.3 for details): where we used (3.23). As a result, we will get the following statement.
where q t and q t+∆t can be obtained from (3.4). If, additionally, (3.10) and (SL 2 ) hold, then g t,∆t (ξ) is an integrable function, and one can apply the inverse Fourier transform to it, to get g t,∆t (x) for a.a. x. Then, for all t ≥ 0 and a.a. x ∈ R d ,
28)
and g ∞,∆t (ξ) is an integrable function. Let g ∞,∆t (x) be its inverse Fourier transform. If, additionally, g 0 (x) and g 0 (ξ) are both integrable, then, for all ∆t ≥ 0, the following limit holds uniformly in a.a. x ∈ R d :
Derivation of equations
In this Subsection, we are going to derive equations (3.22) and (3.25). We will partially use the Model Constructor toolbox presented in [1]. Firstly, we express L 1 , L 2 , L 3 given above as sums of model components in the terminology of [1,Supplementary Note 2]: Here L 11 represents the Birth component: L 12 represents the BirthToAnotherType component: L 21 represents the DensityIndependentDeath component: L 22 represents the ChangeInType component: L 31 represents DeathByCompetition: L 32 represents DeathByExternalFactor: L 33 and L 34 require a new component called ChangeInTypeByFacilitation (which is defined below): The Model Constructor is written on Wolfram Language and requires Wolfram Mathematica R v10 or later. The Model Constructor packages are available at [2] and should be installed before running the following code. Next, we define the ChangeInTypeByFacilitation model component needed for L 33 and L 34 above. It describes the event when an agent at a position x 1 changes own type from s 2 to s 1 . The event happened because of interaction of the agent with each of other agents of a type s 3 placed at a position x 2 . The interaction is defined through a kernel a(x 1 − x 2 ). In particular, s 3 may be equal to s 1 as it is needed for L 33 .
In [5] We define now the AuxiliaryProcess which includes all model components corresponding to operators L ij above. Here the agent types 1, 2, 3 correspond to O, +, −, respectively. We sum up now the right hand sides of the differential equations for the needed g A,B ∆t (ξ), A, B ∈ {O, +, −}, and q O ∆t , cf. (3.20), (3.21). In the notations of the Model Constructor: We use the following code: We are going to verify now (3.22); to this end, we define the expression for h := h t,∆t (ξ), cf. (3.20), (3.21): In[19]:= (*Define h*) h=g [1,1,ξ]+g [1,2,ξ]+g [1,3,ξ]+g [2,3,ξ]+q [1]; Finally, we equate Ch with the obtained sum of the right hand sides of the equation, and find C, that is nothing but 1 2 Here q[2] = q + ∆t and also, by the very definition (1.29) of the Fourier transform: Therefore, the found expression for C coincides with the factor before h t,∆t (ξ) in the right hand side of (3.22). The second found alternative just means that h = 0, i.e. that h t,∆t (ξ) ≡ 0 also solves (3.22), that is trivial. Hence, (3.22
Numerics for the stationary regime on plane
We consider the 2-dimensional case: d = 2, and radially symmetric kernels with equal Gaussian shapes: Note that, indeed, R 2 β(|x|) dx = 1, and also, see Example 3.1, the assumption (3.17) holds, hence (SL 2 ) holds. We will need the following lemma.
where β is given by (3.30). Then Moreover, if f is a function such that the function g(ξ) := f ( c(ξ)), ξ ∈ R 2 is integrable, then the inverse Fourier transform g(x)of g(ξ) can be found by the formula
32)
where J 0 is the Bessel function of the first kind.
The latter integral can be calculated numerically. We use the following Wolfram Mathematica code (where dt = ∆t and r = |x|): The simulations were done with ε = 1 2 . The covariance between numbers of agents in two areas satisfies (2.25); note that we are actually interested in the covariance between 'small' areas (a local characteristic), so we may assume that they are disjoint, hence, the second summand in the right hand side of (2.25) is redundant. Next, the value of u ε,t,∆t (x) can be approximated by the formula (2.31), with d = 2 and ε = 1 2 , in our case. Therefore, we are interested in We plot now graphs for 1 4 g ∆t, r 2 with ∆t ∈ {0, 1, 2}, r ∈ [0, 10]:
Spatial characteristics
We consider now agents of two types, called hosts and parasites: Let L be given through some of three operators, cf. 1.4: Here L 1 describes an independent birth process of hosts: any H-catalyst sends an off-spring which is an H-product, according to a dispersion kernel a + ≥ 0: next, hosts may die because of the competition with other hosts (for resources), according to a competition kernel a − ≥ 0: next, parasites may die with a constant mortality rate m > 0: finally, any host may be transformed to a parasite (keeping the position) because of interaction with the existing parasites, according to a kernel b ≥ 0: We will assume that (3.1) holds for both a ± and for b, we define A ± through (3.2), and set, similarly, We consider L ε by replacing a ± (x − y) and b(x − y) by ε d a ± (εx − εy) and ε d b(εx − εy), respectively. We consider the space homogeneous case. Then, by the general scheme described in Section 1, (4.1) We define also, cf. (2.36), Differential equations for q A t and h AB t (ξ) = g BA t (ξ), A, B ∈ {H, P } are derived in Subsection 4.3 below. We will show that Next, we define and consider the matrix The second and third rows will correspond to h HP t (ξ) and h P H t (ξ) which are equal. Hence, we consider also the matrix with swapped second and third rows (4.6) Finally, we define the vector-function henceforth, the superscript T denotes the transpose vector. Note that Then, we will show in Subsection 4.3 that, for the vector we have, cf. (2.37), We consider now the stationary regime when t → ∞. The only pair of non-zero stationary solutions of (4.3) is Therefore, the condition ensures that (q H * , q P * ) is a the only pair of positive stationary solutions to (4.3). Proposition 4.1. Let (HP 1 ) hold. Then, for any q H 0 > 0, q P 0 > 0, then q H t and q P t oscillate around q H * and q P * , respectively, with a decreasing amplitude (damping oscillation).
We define also the following analogue of (3.14): for x, ξ ∈ R d , we set (4.14) We will assume that there exist α > 0, such that The following proposition provides simple sufficient conditions for (HP 1 )-(HP 3 ). 3. An example when (4.15) holds is the case (3.19) of an equal shape c of kernels a + = A + c and a − = A − c, provided that (HP 1 ) holds. Indeed, then
Proposition 4.2. Suppose that
In the Appendix below, we consider also how the condition (4.16) can be relaxed to still get (HP 3 ).
Spatiotemporal characteristics
Similarly to Subsection 3.2, we consider the auxiliary dynamics of described by the generator where L 1 , L 2 , L 3 , L 4 are defined according to Subsection 2.2. Namely, now we have, similarly to the corresponding operators in spatial logistic model The situation with L 4 is more complicated: when HO-reactant of the spatial dynamics becomes P +-product (keeping the position), it should be also transformed to H−-product, according to the general scheme.
Hence, formally, one could write: However, the first summand in the latter expression does not satisfy the basic requirement that different agents should have different positions: there are agents x H− and x P + simultaneously. 1 To overcome this, we consider a formal modification the host x HO transforms to the parasite z P + distributed in space according to the kernel given by the Dirac δ-function δ(x − z).
Therefore, we define Considering the first summand of the operator L 4 as such with a regular (integrable) kernel δ(x − z) one apply the technique described above and derive the corresponding differential equations for correlation functions, cumulants, and for the beyond mean-field expansion. We should then 'replace' the regular kernel by the real δ-function. This latter includes two steps. Firstly, in differential equations in terms of the Fourier transform, we replace δ(ξ) by 1.
Secondly, one has to distinguish the terms which, in real coordinates (before passing to the Fourier transform), contained the δ-function, i.e.
If such term contained also the point x H− , then, after the integration w.r.t. z P + = z, the corresponding integral would disappear, and z will be replaced by x. The latter is however the position of the H−-agent. We will get as a result the δ-function between the positions of H− and P + agents. This can be written heuristically as follows: for a (regular) function f , It means that the pair correlation between H− and P + will include now a δfunction. By (2.17) (considered in the case i, j = I 2 = {H, P }), pair cumulant u H−,P + ∆t = u P +,P − ∆t in the r.h.s. appears for u HP t,∆t in the l.h.s. only. Hence, in the space homogeneous case, u HP t,∆t (x) is (the only) non-integrable pair cumulant. This is the effect of using L 4 instead of L 4 . Since the dynamics we consider is linear, one has u HP t,∆t (x) = u HP t,∆t (x) + u HP t,∆t,sing δ(x), (4.23) so, to get the answer, that is the corresponding cumulant u HP t,∆t (x) for the model generated by L 4 , one has to get rid of the singular term. We will do this in the beyond mean-field approach below. 2 Following the general scheme, we consider L ε with a ± (x − y) and b(x − y) above replaced by ε d a ± (εx − εy) and ε d b(εx − εy), respectively; next, we consider the dynamics of γ ε,t defined by (2.18) with L replaced by L ε . Let q X ∆t , g X,Y ∆t , X, Y ∈ {HO, H+, H−, P O, P +, P −} be the corresponding functions from the beyond mean-field expansion. We consider, cf. (2.32), for all A, B ∈ {H, P }, (4.24) and, cf. (2.38), (4.25) Recall that, g HP t,∆t = g P H t,∆t and hence h HP t,∆t = h P H t,∆t . By (4.23), g HP t,∆t (x) is (the only) non-regular function which should include the Dirac δ function, as a result g HP t,∆t will be non-integrable at infinity. By (4.23), if we subtract from g HP t,∆t its limit at infinity, the result will be nothing but the Fourier transform of g HP t,∆t (x), so that, cf. (2.31), AB ∈ {HH, HP , P H, P P }. (4.26) We will get hence the values of the spatiotemporal cumulants for the initial model. In Subsection 4.3 below, we will show that d d∆t (4.28) where D t,∆t (ξ) is the following matrix: and hence, cf. (4.4), . (4.29) Therefore, by (4.5), we can represent A t+∆t (ξ) as a block matrix, namely, (4.30) where 0 denotes 2 × 2 matrix of zeros, and hence, denoting, cf. (4.9), we get, by (4.27), (4.28), (4.31) cf. also (4.10). Note that, by (4.29), cf. (4.8), A t+∆t (ξ) = A[q H t+∆t , q P t+∆t ](ξ). Comparing this with (4.10), we see that the conjecture holds.
An explicit formula for g HP t,∆t (∞) is provided in the Appendix below, see (A.33). As a result, for each AB ∈ {HH, HP , P H, P P }, one can apply the inverse Fourier transform to an integrable function g AB t,∆t (ξ), to get, for a.a. x ∈ R d , the needed for (4.26) function g AB t,∆t (x).
As a result, we obtained the desired leading terms g AB ∞,∆t (x) in the beyond meanfield expansion (4.26), for each AB ∈ {HH, HP , P H, P P }, of the spatiotemporal cumulant of the considered model in the stationary regime, i.e. when t in (4.26) is replaced by ∞.
Derivation of equations
In this Subsection, we are going to derive, in particular, equations (4.3), (4.10), and (4.31). Similarly to Subsection 4.3, we will partially use the Model Constructor toolbox from [1]. Firstly, we note that the operators L 1 , L 2 , L 3 , L 4 defined above represent Birth, DeathByCompetition, DensityIndependentDeath and Infection components, respectively.
Next, we express L 1 , L 2 , L 3 , L 4 given above as sums of model components in the terminology of [1,Supplementary Note 2]. Namely Here L 11 represents the Birth component: L 12 represents the BirthToAnotherType component: L 21 represents the DeathByCompetition component: L 22 represents the DeathByExternalFactor component: L 23 and L 24 both represent the ChangeInTypeByFacilitation component introduced in Subsection 4.3: L 31 represents the DensityIndependentDeath component: L 32 represents the ChangeInType component: L 41 also represents the ChangeInTypeByFacilitation component: L 42 represents the Infection component (which is, actually, a partial case of the ChangeInTypeByFacilitation component): Finally, L 43 and L 44 both represent the ChangeInTypeAndBirthByFacilitation component defined below: We are going to describe the Wolfram Mathematica code we used. First six lines (In [1][2][3][4][5][6]) are the same as in Subsection 3.3: we load libraries, set-up internal variables, define the ChangeInTypeByFacilitation and Relax components.
Next, we define the ChangeInTypeAndBirthByFacilitation model component needed for L 43 and L 44 above. It describes the event when an agent at a position x 2 changes own type from s 3 to s 2 and, simultaneously, it sends an off-spring of a type s 1 to a position x 1 . The off-spring is sent through a kernel d(x 1 − x 2 ) (which is the Dirac δ-function δ(x 1 − x 2 ) in operators L 43 and L 44 ). The event happened because of interaction of the agent with each of other agents of a type s 4 placed at a position x 3 . The interaction is given through a kernel b(x 2 − x 3 ). In particular, s 4 may be equal to s 1 as it is needed for L 44 .
In[7]:=
To simplify the representation of the calculations below, we introduce a replacement rule to replace values of the Fourier transform at the origin by the corresponding integral, i.e.
we include here also the replacement δ ≡ 1: In the Model Constructor toolbox, HQfALL and also HGfALL are the functions providing the r.h.s. of the differential equations for functions q and g, respectively.
Firstly, we create a collection rule: ,-q [4],-q [5], q [1],q [2],q [3],q [4],q [5]}; Next, we collect the terms in the r.h.s. of the equations obtained in In[14] according to the rule above; and then one can replace the sums of g by the corresponding notations for h AB t,∆t . Then we expand, and thereafter we collect again, now to distinguish the coefficients before functions h:
True
We are going now to define the functions in the stationary regime, using the replacement according to (4.12). Firstly, we consider the stationary version (the limit as t → ∞) of the matrix (4.5): Finally, we are going to verify the corrections obtained in (4.34)-(4.35) to get integrable functions. We were actually interested at the values of the obtained solutions h AB ∞,∆t (ξ) as |ξ| → ∞. By the Riemann-Lebesgue lemma, the Fourier transforms of a ± , b converge to zero at infinity.
Analysis and numerics for the stationary regime
By Theorem 4.7, the eigenvalues of the matrix E * (ξ) have negative real parts for each ξ ∈ R d . Then, by (4.36)-(4.37), functions h AB ∞,t,∆t (ξ), A, B ∈ {H, P } converge (for each ξ) to 0 as ∆t → ∞. Similarly to Proposition 4.1, this convergence to 0 can be monotone or oscillating with damping, depending on whether the eigenvalues of E * (ξ) are real negative or complex with negative real parts, respectively. By (4.34) and (4.35), functions g AB ∞,∆t (ξ), AB ∈ {HH, HP , P H, P P } have the same properties.
By the proof of Theorem 4.7, for a fixed ξ ∈ R d , the eigenvalues of E * (ξ) are real negative iff is non-negative; otherwise, they are complex with negative real parts. The character of convergence hence depends on an interplay between behavior of the Fourier transforms a + (ξ), a − (ξ) and b(ξ) in different zones of ξ ∈ R d , and is especially non-trivial if the Fourier transforms take negative values, that may be the case e.g. for the Gaussian-like kernels considered in (A.18) in the Appendix.
One can make, however, several general observations about the mentioned convergence.
Since
we conclude that the convergence is oscillating for ξ = 0 if and only if (4.13) holds. By continuity and the strict inequality in (4.13), the oscillations will take place for ξ at a neighbourhood of the origin.
2. Directly from (4.39), one gets that the convergence is monotone for all ξ ∈ R d such that b(ξ) ≤ 0. We assume now that this is not the case and (4.40) 3. To have oscillating convergence for all large enough |ξ|, one needs with necessity, by the Riemann-Lebesgue lemma, that As a result, to have oscillating in neighbourhoods of the origin and infinity, we require, with necessity that both (4.40), (4.41), and (4.13) hold. Note also that (4.13) under assumption (4.41) can be easily rewritten as follow: We assume now that both (4.40)-(4.42) hold; moreover, we also consider the case of equal shapes for all kernels: (4.43) Then, since, by (3.16), c(ξ) ≤ 1, one can easily rewrite (4.39) as follows: because of (4.42). Therefore, (4.40)-(4.42) imply that that all functions g AB ∞,∆t (ξ), AB ∈ {HH, HP , P H, P P }, converge to 0 as ∆t → ∞ with damping oscillations for all ξ ∈ R d .
Note that the opposite to (4.42) inequality does not imply that the convergence is monotone for all ξ ∈ R d . Moreover, one can not show analytically that the oscillations will be preserved for the inverse Fourier transforms g AB ∞,∆t (x), AB ∈ {HH, HP , P H, P P }.
The result of function gReal is the vector of g AB ∞,∆t (x), AB ∈ {HH, HP , P H, P P }; here valt = ∆t and valx = |x|. The result will be used to find the corresponding cumulants by (4.26): the simulations were done for ε = 1 2 , hence, the cumulants measured in simulations should be approximated as follows: AB ∈ {HH, HP , P H, P P }.
We are going to discuss now the results of the numerical calculations of the inverse Fourier transforms.
1. For a fixed space variable, e.g. for x = 0, the graphs of the g-functions as functions of ∆t ∈ [0, 20] are shown on Figure 2a. They demonstrate the damping oscillations. As we can see, values of g HH ∞,∆t (0) and g P P ∞,∆t (0) are pretty close, as well as values of g HP ∞,∆t,reg (0) and −g P H ∞,∆t (0). We observe also the initial negative correlation between finding a host at the current position of a parasite for some positive time interval.
2. Next, in the considered case of monotone kernels, cumulants converge to 0 in |x| monotonically, see Figure 2b for a fixed ∆t = 7. In other words, for each |x| ≥ r 0 (perhaps, staring with some r 0 > 0), we will see a picture similar to that on Figure 2a, however, the corresponding cumulants have smaller amplitudes.
3. We consider now the dependence of solutions on A + when A + = m. We keep other parameters in (4.48) and compare the graphs of Figure 2a with those for A + = 2 > m and A + = 1 2 < m. We present the comparison on Figure 3, for e.g. |x| = 5. We can observe that, with the growth of A + , the oscillation became more frequent (the period becomes smaller) and the amplitude becomes higher.
4. Finally, recall that the parameters in (4.48) satisfy (4.42), that is, for A + = m, nothing but (4.13). We consider the case when (4.42) fails. If we keep A + = B = m = 1, then (4.42) fails iff A − ≥ 2( √ 2 − 1) ≈ 0.83. We take A − = 0.85, and then, see Figure 4, the convergence of g-functions in ∆t to 0 becomes monotone, without visible damping oscillations. Note that, however, we can not prove this analytically, so the fluctuation may still happen for large values of ∆t and/or |x|. Appendix: Mathematical proofs and discussions Proof of Theorem 3.2 Step 1. By (2.40), h t,0 (ξ) = g t (ξ) + q t .
Then, the solution to (3.24) has the form By the flow property of solutions to (3.3), q t+τ = q τ , where We have then d dτ and integrating from τ = 0 to τ = ∆t, we get Replacing back q τ by q t+τ , we obtain Substituting into (A.1) and using that m + q * A − = A + , one gets Then, one can rewrite: To find g t,∆t (ξ) from (3.21), one has to solve (3.25). By (2.35), q O ∆t = q t . Therefore, by (A.2), As a result, (3.21) implies (3.26).
Next, we have and by (A.9), (A.5), Finally, rewriting back and using that we obtain from (A.8), that Hence, by the dominated convergence theorem, (A.11) holds with I 1 replaced by each of I 2 , I 3 , I 4 . Therefore, g t,∆t converges to g ∞,∆t in L 1 (R d ) as t → ∞. Since g t,∆t − g ∞,∆t is the inverse Fourier transform of g t,∆t − g ∞,∆t , we obtain from an analogue of (3.16) that g t,∆t converges to g ∞,∆t in L ∞ (R d ).
Proof of Lemma 3.3
Firstly, for the Fourier transform defined as in (1.29), formula (3.31) follows from e.g. [4,Example 2.2.9,Proposition 2.2.11]. Next, we note that the Fourier transform of a (radially) symmetric function is also (radially) symmetric, and it coincides with the inverse Fourier transform of that function. Therefore, by e.g. [4,Back Matters B.5], Making the substitution s = 2πr, one gets the desired formula (3.32).
Proof of Proposition 4.1
We set f (x, y) = x(A + − A − x − By), g(x, y) = y(Bx − m). Consider the Jacobian Then, it is straightforward to check that Since under (HP 1 ), we conclude that both eigenvalues of j(q H * , q P * ) have negative real parts, hence (4.12) holds.
The monotone convergence in (4.12) takes place when the eigenvalues of J are real (and hence negative), otherwise there will be damping oscillations. The eigenvalues of J are real iff tr(J) 2 ≥ 4 det(J), that is equivalent to 2 , and hence the statement is proved.
with small enough s > 0. Indeed, it is straightforward to check that b(ξ) < 0 for |ξ| > d(s) for certain continuous d(s) with d(0) = 0. Therefore, taking s > 0 small enough we ensure that b(ξ) < 0 for some ξ ∈ Λ given by (A.17). Note also that a small s here corresponds to a large length scale of the kernel b(x) describing the influence of parasites on hosts.
operators on X) and also provided that the operator (matrix) C * is invertible. We have that C * (ξ) is given by (4.18) and Th show that C * is invertible in X it is evidently enough to show that the function det C * (ξ) is separated from 0. We have By (HP 2 ) and (A.13), the proves the needed. As a result, by [3,Lemma 3.1], and moreover g AB t → g AB * in both L 1 (R d ) and L ∞ (X) as t → ∞, A, B ∈ {H, P }. The convergence in L 1 implies, by (SL 2 ), the convergence in L ∞ (R d ) for the inverse Fourier transforms, that fulfills the proof. | 12,082 | 2020-10-01T00:00:00.000 | [
"Mathematics",
"Computer Science"
] |
Structural Insight into Substrate Selection and Catalysis of Lipid Phosphate Phosphatase PgpB in the Cell Membrane*
PgpB belongs to the lipid phosphate phosphatase protein family and is one of three bacterial integral membrane phosphatases catalyzing dephosphorylation of phosphatidylglycerol phosphate (PGP) to generate phosphatidylglycerol. Although the structure of its apo form became recently available, the mechanisms of PgpB substrate binding and catalysis are still unclear. We found that PgpB was inhibited by phosphatidylethanolamine (PE) in a competitive mode in vitro. Here we report the crystal structure of the lipid-bound form of PgpB. The structure shows that a PE molecule is stabilized in a membrane-embedded tunnel formed by TM3 and the “PSGH” fingerprint peptide near the catalytic site, providing structural insight into PgpB substrate binding mechanism. Noteworthy, in silico docking of varied lipid phosphates exhibited similar substrate binding modes to that of PE, and the residues in the lipid tunnel appear to be important for PgpB catalysis. The catalytic triad in the active site is essential for dephosphorylating substrates lysophosphatidic acid, phosphatidic acid, or sphingosine-1-phosphate but surprisingly not for the native substrate PGP. Remarkably, residue His-207 alone is sufficient to hydrolyze PGP, indicating a specific catalytic mechanism for PgpB in PG biosynthesis. We also identified two novel sensor residues, Lys-93 and Lys-97, on TM3. Our data show that Lys-97 is essential for the recognition of lyso-form substrates. Modification at the Lys-93 position may alter substrate specificity of lipid phosphate phosphatase proteins in prokaryotes versus eukaryotes. These studies reveal new mechanisms of lipid substrate selection and catalysis by PgpB and suggest that the enzyme rests in a PE-stabilized state in the bilayer.
Phosphatidylglycerol (PG) 2 is one of the major phospholipids in the bacterial inner membrane, accounting for ϳ20% of total lipid composition. PG is generated by dephosphorylation of phosphatidylglycerol-phosphate (PGP) catalyzed by three membrane-associated phosphatidylglycerol phosphatases, PgpA, PgpB, and PgpC (1,2). These phosphatidylglycerol phosphatases exhibit no sequence homology with each other, and their active sites are predicted to face different sides of the cytoplasmic membrane. PgpB is the only phosphatidylglycerol phosphatase protein containing multiple (six) transmembrane helices (TM) (3). Raetz and coworkers (1) have shown that PgpB alone is sufficient to maintain PG at the wild type level in Escherichia coli, although the specific role of each phosphatidylglycerol phosphatase is still unclear. In addition to PGP, in vitro studies showed that PgpB was able to dephosphorylate other lipid phosphate substrates, including lysophosphatidic acid (LPA), phosphatidic acid (PA), diacylglycerol pyrophosphate (DGPP), and undecaprenyl phosphate (2)(3)(4). Any involvement of PgpB in these bacterial phospholipid catalyzes will require experimental verification in vivo, although substrate diversity has been reported in PgpB's eukaryotic homologs.
PgpB is a member of the lipid phosphate phosphatase protein family (LPP), which is universally found in all kingdoms of life (5). Numerous studies have illustrated their important roles in lipid signaling processes in attenuating a variety of lipid phosphate levels in eukaryotic cells (6). For instance, mammalian LPP1 hydrolyzes LPA to reduce cell proliferation and increase apoptosis (7). Both LPP3 and SPP, a sphingosine-1-phosphate (S1P) phosphatase, were found to be associated with embryonic development and cell death (8,9). In Arabidopsis, LPPs modulate the stress response via PA and DGPP-mediated lipid signaling (10). This substrate versatility may be advantageous for LPPs to participate in diverse signaling networks simultaneously. It has long been proposed that LPPs including PgpB utilize a common acid phosphatase mechanism mediated by three essential catalytic motifs (C1-C3) to catalyze dephosphorylation of structurally different lipid phosphate substrates (11).
Recently, the structure of the apo form of PgpB from E. coli has been reported. The structure showed that the three catalytic motifs form a catalytic site on the extracellular surface in a * This work was supported by National Institute of General Medical Sciences Grants R01GM098572 and R01GM097290 (to L. Z.). This work was also supported by American Heart Association postdoctoral fellowships (to S. T.) The authors declare that they have no conflicts of interest with the contents of this article. The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Institutes of Health. The atomic coordinates and structure factors ( To address these fundamental questions, here we report the crystal structure of the PE-bound state of PgpB. The PE binding conformation provides a structural basis to help understand the substrate binding mechanism of PgpB. Our data also reveal a novel PgpB dephosphorylation mechanism specific for PGP. We also identified a pair of lysine residues on TM3 that enable PgpB to distinguish the lyso form from diacyl-form substrates based on their acyl chain conformations. In addition, a novel regulatory effect of PE lipid on PgpB catalysis is discussed.
Results
Functional Characterization of PgpB in Vitro-The PgpB protein fused with a His 6 tag at its C terminus was expressed and purified using the detergent n-dodecyl -D-maltoside (DDM). The activity of the purified protein was measured using a standard colorimetric phosphatase assay in vitro. Although PGP is the only PgpB substrate that has been characterized in vivo (1), PGP catalysis has not yet been analyzed in vitro. To compare PGP with other LPP substrates, we also chose two lyso forms (LPA and S1P) and the diacyl form PA (Fig. 1A). Both PGP and PA have similar chemical structures except that PGP has an additional phosphoglycerol moiety on the phosphate group. PgpB apparently dephosphorylates all four substrates in vitro; however, the activity for LPA or PA was substantially (ϳ6ϫ) higher than for S1P or PGP (Fig. 1B).
All PgpB substrates tested above contain a long (ϾC 16 ) acyl chain(s) despite their different head group structures. To examine whether the acyl chain is involved in substrate binding, we tested PgpB using three LPA analogs with different acyl chain lengths: 18:1, 6:0, and acyl-less glycerol 3-phosphate. Michaelis-Menten kinetic analysis yielded a K m ϭ 108 Ϯ 17 M and V max ϭ 1471 Ϯ 73 M/g/min for 18:1 LPA (Fig. 1C). PgpB activity showed a strong dependence on substrate acyl chain length. As seen in Fig. 1D, the activity of 6:0 LPA was dramatically reduced, resulting in a K m ϭ 5052 Ϯ 802 M and V max ϭ 36 Ϯ 3 M/min/g for 6:0 LPA. No activity was detected with 30 mM glycerol 3-phosphate in the reaction (Fig. 1B). These data showed that PgpB exclusively catalyzes lipid substrates. The reduction (Ͼ40ϫ) in catalytic kinetics, in both K m and V max , indicated that a long acyl chain is important not only for substrate binding but also for enzyme catalysis.
PE Inhibition of PgpB in Vitro-Orthovanadate is the only identified inhibitor for the LPP proteins. Interestingly, we also found that the activity of PgpB was inhibited by 70% after adding 3 mM POPE (the concentration in the crystallization buffer; see below) in the reaction ( Fig. 2A). No apparent inhibition was observed in the presence of POPG or cardiolipin (CL) at the same concentration. Fig. 2B shows a time course for PgpB-catalyzed LPA hydrolysis in the presence of POPE. To further characterize this novel PE inhibition, we generated a Dixon plot by measuring PgpB activity at varied substrate concentrations as a function of inhibitor concentration. The Dixon plot in Fig. 2C is characteristic of competitive inhibition. The K i value was estimated to be 2.7 mM based on the intersection of linear regressions at varied LPA concentrations. The lack of inhibition by PG suggested the ethanolamine head group is required for PE inhibition. Phosphocholine shares a zwitterionic lipid conformation similar to PE but has an additional trimethyl group. To probe the role of inhibitor conformation, we tested DOPC. However, the addition of DOPC to the reaction had no noticeable effect ( Fig. 2A), indicating the specificity of PE inhibition.
To directly measure PE interaction, we also performed a ligand pulldown assay with the purified PgpB protein anchored on Ni 2ϩ -NTA resin. We generated 32 P-labeled PE from E. coli strain UE54 (13) (Fig. 2C). Based on radioactivity, the binding of PgpB with PE increased as a function of lipid concentration (Fig. 2D). In the presence of 4 mM PE, 7% (ϳ700 cpm) of the added [ 32 P]PE (total ϳ10,000 cpm) was associated with the ϪK i value of inhibition was estimated based on the intersection of linear regression. D, TLC analysis of 32 P-labeled total lipids from E. coli UE54 strain, visualized by a phosphorimaging system. E, [ 32 P]PE pulldown assay using the PgpB protein (circles) on a Ni-NTA resin as a function of POPE concentration. Empty resin (triangles) was used as control. The bound PE ligand was quantified by a scintillation counter.
PgpB protein compared with only 0.6% (ϳ60 cpm) bound to the control empty resin lacking PgpB, indicating specific interaction of PE with PgpB and also lending support to the evidence for PE as an in vitro PgpB inhibitor.
Structural Determination of the PgpB-PE Complex-Identification of PE as a specific in vitro inhibitor provided an opportunity to study the lipid substrate binding mechanism of PgpB. Attempts to crystallize PgpB in the presence of synthetic POPE were unsuccessful. We were able to crystallize the PgpB protein using the vapor diffusion method in the presence of 5 mM E. coli total lipid extract, which contained ϳ3 mM PE. The structure was determined at 3.2 Å resolution using the SAD (single wavelength anomalous dispersion) method (Table 1). Although the PgpB lipid complex was crystallized under different conditions from that used for the previous apo form (12), both structures exhibited nearly identical overall conformations with an root mean square deviation value of 0.9 Å. However, in the PgpB lipid complex, a strong and lipid-like electron density was observed in the central cavity assembled by six TM helices (see below) in the F o Ϫ F c difference map. A PE molecule (1,2dilauroyl-sn-glucero-3-phosphoethanolamine) fits well in the density region. We excluded other possibilities such as PG, cardiolipin, DDM or PEG6000, which were also present in the crystallization solution due to the following facts: 1) their headgroups did not fit in the density and 2) no noticeable inhibition by these additives was observed under their crystallization conditions ( Fig. 2A). The electron density shown in Fig. 3, A and B, represents the final PE conformation after structural refinement using Refmac. Both the PE headgroup and S n 2 tail exhibit similar thermal B values to those of their neighboring peptides (ϳ90), whereas the B value of the S n 1 tail is 20% higher, perhaps due to its localization on the protein surface (see Fig. 5A and also see below). The final structural model contains the fulllength sequence (amino acid residues 1-254) together with the C-terminal His 6 tag and a PE molecule.
Overall Conformation of PgpB-Monomeric PgpB contains a transmembrane domain, an extracellular domain, and an intracellular helix CH1 (Fig. 3A). Six TM helices (TMs 1-6) assemble the integral membrane domain with both N and C termini in the cytoplasm. The extracellular domain formed by four short helices (EHs 1-4) between TMs 3 and 4 of the PgpB molecule tilts by 65°in the bilayer based on the membrane boundaries determined by the positions of 10 tryptophan residues from different TMs (Fig. 3B).
The catalytic site is located in a positively charged cavity on the interface between the membrane domain and the periplasmic domain (Fig. 3B). Six conserved residues in the C1-C3 motifs essential for LPPs' activity are assembled together to form a catalytic site (Fig. 4A). Three conserved residues, Lys-97, Arg-104, and Arg-201, in a triangular orientation, create a phosphate binding site. His-163, His-207, and Asp-211 form the catalytic triad aligning across the phosphate binding site.
PE Binding Conformation-In both the apo and PE-bound forms, TM3 is angled away from the other five TM helices, creating a V-shaped groove beneath the active site and a membrane-embedded tunnel (referred to as the TM3 tunnel) ( Fig. 3B and 5A) (12). The tunnel is narrow, ϳ4 Å in diameter, estimated by MOLE and is mainly constrained by a loop consisting of four residues (PSGH) that comprise the LPP fingerprint sequence (Fig. 5B).
In the lipid-bound structure, PE was found in the tunnel, which was sandwiched between TM3 and TMs 4 and 6 (Figs. 3B and 5A). The ethanolamine headgroup was stabilized in a threewalled cage formed by His-163, Gln-50, and Phe-166 in front of the catalytic site via cationinteractions (Fig. 5C). A similar PE interaction was previously reported in the structure of cytochrome c oxidase (14). The H-bond interaction between the amine group of PE and the side-chain oxygen atom of Gln-50 stabilized the whole Gln-50 residue, which was invisible in the apo form structure (an alanine was assigned at this position instead) (12). In the tunnel, the PE glycerol group is constrained by two glycine residues, Gly-89 from TM3 and Gly-162 from the PSGH loop (Fig. 5B). The PE S n 2 tail deeply inserts into a narrow pore (referred to as the acyl pore) with its tip reaching out of the front TM2-3 groove (Fig. 5D). The acyl pore is formed by several hydrophobic residues including Leu-82, Ile-86 from TM3, Phe-166 and Trp-170 from TM4, and Leu-222 from TM6 (Fig. 5E). It should be noted that the PE molecule and its adjacent structural components are not involved in crystal packing.
Docked Substrate Conformations-The PE conformation provides insight into the PgpB substrate binding mechanism. As a further test, we examined substrate docking using the Aut-oDock program (15). As seen in Fig. 6, LPA, S1P, and PA are stabilized in the TM3 tunnel in a conformation strikingly similar to that of PE observed in the structure. Interestingly, in all three docking models, one fatty acyl chain, either the S n 1 tail of LPA or S1P or the S n 2 tail of PA, was found in the acyl pore, suggesting that the pore is energetically favorable for fatty acyl chain binding. This finding also explained results from the PgpB kinetic study showing that a long fatty acyl chain is important for substrate binding (Fig. 1, C and D). In contrast to PE, these lipid phosphates positioned their phosphor headgroups toward the catalytic center in proximity to the predicted phosphate binding position. The TM3 Tunnel Is Important for PgpB Catalysis-To gain further insight into the substrate binding mechanism in the TM3 tunnel, we first tested the effect of blocking substrate tunnel access by placing bulky residues, either valine or phenylalanine, at the Gly-89 or Gly-162 positions in the tunnel neck. As expected, all four mutations (G89V, G89F, G162V and G162F) completely abrogated PgpB activity. In addition, acyl chain binding in the acyl pore appeared to be important for substrate binding. We tested this by mutating two aromatic pore-lining residues. Phe-166 interacted with the C 1 -C 6 atoms, whereas Trp-170 reached the C 10 -C 12 atoms at the front exit (Fig. 5E). Both alanine substitutions at these two positions resulted in a dramatic reduction (Ͼ90%) of C 18 -LPA catalysis (Fig. 4F), supporting our hypothesis.
In addition to the TM3 tunnel, the structure suggested that the active site may be accessed from the front V-shaped groove (Fig. 3A), although the tilting orientation of PgpB would argue against substrate lateral diffusion from the membrane (Fig. 3B). Previously, Fan et al. (12) showed that mutations on the groove surface largely preserved PgpB activity. To carefully exclude this access possibility, we mutated two glutamine residues, Gln-50 from TM2 and Gln-90 from TM3, at the entrance of the groove (Fig. 5C). Q50A was as fully active as the wild type, and Q90A maintained Ͼ30% activity (Fig. 4F). Taken together, these results do not support this alternative substrate accessing route.
The Catalytic Triad Is Not Required for PGP Activity-PgpB was thought to use a common acidic phosphatase mechanism requiring all six residues in the active site for hydrolysis of different lipid substrates. This hypothesis was tested using substrates LPA, PA, and DGPP (12). To study the PGP catalytic mechanism and substrate specificity, we generated six single alanine mutants in the active site and tested them with a new set of four lipid phosphates including LPA, S1P, PA, and PGP (Fig. 4C). Our results using LPA, S1P, and PA are consistent findings from the previous study by Fan et al. (12) that the entire catalytictriad(His-163,His-207,andAsp-211)arecrucialfordephosphorylation of these substrates. Surprisingly, this was not the case for PGP. Results shown in Fig. 4C show that His-207 appears to be the only residue essential for hydrolysis of PGP. In fact, mutation H163A increased PGP hydrolysis by 50%, and mutant D211A retained 50% activity. Therefore, PgpB may utilize a unique catalytic mechanism for PGP dephosphorylation.
In many histidine phosphatases, the dephosphorylation reaction is mediated by a catalytic dyad composed of a histidine as an H ϩ acceptor and another carboxylate residue as an H ϩ donor (16). On the periplasmic EH4 helix, the carboxylate group of Glu-154 is closed (4.5 Å) to the imidazole ring of His- FIGURE 5. PE conformation in the TM3 tunnel. A, electrostatic surface representation of the TM3 tunnel with PE (sticks). B, TM3 tunnel is constructed by TM3 (green) and PSGH sequence (yellow). The tunnel neck is drawn as dashed lines. C, the headgroup conformation of bound PE in the front of the catalytic site. D, a cut-through view of the electrostatic surface shows the S n 2 tail of PE inside the acyl chain pore. E, the conformation of the pore-lining residues stabilizes the PE S n 2 tail (gray). F, characterization of PgpB mutations in the TM3 tunnel or the front V-shaped cavity using 18:1 LPA as substrate. All activities were normalized to that of wild type.
163. However, mutation of Glu-154 to alanine retained ϳ80% activity for both LPA and PGP, excluding it as an alternative H ϩ donor in the PGP reaction.
Selectivity for Lyso Versus Diacyl Substrates-Substrate discrimination was also observed among the conserved triple Lys/ Arg residues in the active site. Mutation of R104A or R201A inside the active site was lethal for all four substrates. But Lys-97 located at the cavity entry was only required for the lyso forms LPA and S1P. In fact, K97A enhanced the activity for diacyl PA (instead of the complete activity loss observed in the Fan et al. (12) study) and for PGP by Ͼ70%, indicating its distinctive role in the catalysis of lyso versus diacyl substrates.
The novel acyl chain selectivity of K97A drew our further attention to the TM3 helix. Adjacent to Lys-97, another lysine residue, Lys-93, is also located near the active site (Fig. 7A). Interestingly, similar to K97A, the mutant K93A also showed complete activity loss for LPA and S1P, whereas it retained full activity for PA and gained 40% more activity toward PGP compared with wild type (Fig. 7C). To probe any functional crosstalk between these two adjacent lysine residues, we generated a double mutant, K93A/K97A. The double mutant exhibited a similar selective activity change as seen with single mutants K93A and K97A. Furthermore, the double alanine mutant further enhanced PGP catalysis by nearly 3-fold (Fig. 7C). Those results indicated that both lysine residues are absolutely required for lyso form substrates, whereas they do not appear to be involved in catalysis of diacyl form substrates. Given that these substrate selectivity properties occur at two positions in TM3, these results further support our structural observation that TM3 is important for substrate binding.
Selectivity for Prokaryotic Versus Eukaryotic Substrates-Lys-97 is highly conserved in the LPP family, but evolutionary divergence clearly appears at the Lys-93 position (Fig. 7B). Lys-93 is conserved in prokaryotes, but a threonine residue was found at the analogous position in all eukaryotic LPPs. To further explore the specific role of Lys-93, we mutated Lys-93 to threonine (Fig. 7C). Strikingly, K93T significantly improved activity for LPA, S1P, and PA by 2.5-or 3.4-fold but not for PGP. LPA, S1P, and PA are the major substrates of eukaryotic LPPs. In eukaryotic cells, PGP dephosphorylation is actually catalyzed by a different phosphatase enzyme Gep4 localized in mitochondria (17). Because K93T boosted overall PgpB activity, we questioned if K93T alone is sufficient to maintain PgpB activity. The double mutant K93T/K97A lost all activity for LPA or S1P but retained 50% activity for PA or PGP. These results further con-firmed the critical role of Lys-97 for lyso substrates and suggested that the residue at Lys-93 serves as a tuner to adjust LPP activity for individual substrates.
Discussion
PgpB is an intramembrane lipid phosphatase protein promoting PG biosynthesis in bacteria. We identified a novel in vitro PE inhibition and determined the structure of the PgpB PE-bound form. The PE binding conformation together with substrate in silico docking and mutagenesis studies provides new insights into the mechanisms of lipid substrate recognition and catalysis of prokaryotic PgpB and other LPPs in eukaryotes.
Potential Role of PE on PgpB-The in vitro inhibitory effect of PE also raised a fundamental question about its function in vivo as PgpB is an integral membrane protein embedded in the inner membrane, which contains 70% PE. In the apo form structure, the hydrophobic TM3 tunnel is largely open toward the membrane bilayer. Whether PgpB rests as a lipid-occluded state in the membrane is unknown as all in vitro studies were carried out using detergent-delipidized protein.
Lipid is important for the stability of the PgpB protein. Fan et al. (12) has shown that adding lipid substrates with a long-chain (C 18 ) but not a short-chain (C 8 ) enhanced thermal stability of PgpB. In addition, PgpB could be stabilized substantially by adding MoO 4 2Ϫ in the protein solution (12). It was expected that MoO 4 2Ϫ binding at the active site draws TM3 to close the TM3 tunnel. These data collectively implied that a lipid-occluded TM3 tunnel is energetically unfavorable and may thus require lipid association in the bilayer. Zwitterionic PE usually increases the stability of the folded state of membrane proteins (18). Conversely, an excess of negatively charged lipids such as PG could severely destabilize a transmembrane helix bundle structure (19). Therefore, the PE-bound form demonstrated in this work may represent the resting state of PgpB stabilized in the cell membrane in vivo.
Several lines of evidences have suggested that accommodation of a defined lipid species within a membrane protein might allow the activity of the protein to be controlled by altering its stability (20,21). In the case of PgpB, the substrate binding affinity is significantly higher (ϳ20-fold) than the K i value for PE that shows only partial inhibition even at high PE concentrations (Figs. 1D and 2B). The modest inhibition is perhaps due to the fact that the bulky phosphoethanolamine headgroup cannot enter the phosphate binding site (Figs. 5C and 6). A resting conformation would allow efficient replacement of PE with lipid phosphate substrates in the active state. By balancing stability and activity, the optimal existence and functioning of PgpB may be reached in the lipid environment.
Although the physiological importance of the anionic lipids PG and CL has been recognized, the regulation of a key enzyme for their biosynthesis, the phosphatase that converts PGP to PG, remained obscure. PE regulation may allow PgpB activity to remain at a physiologically required threshold. PE can dissociate as soon as its concentration drops. The level of PE can be altered at different growth phases, and its accumulation could shift depending on the stage of the cell cycle (22). These events could contribute to regulation of anionic and zwitterionic glycerophospholipid synthesis during cell growth. The elevation of PE levels would lead to an increased level of PGP coincident with its use as a phosphorylated precursor in the synthesis of PG and CL (1). Thus, PE could be crucial for controlling the activity of PgpB via its dependence on the presence of an amount of PE required for stabilizing this protein. Changes in PE concentration can also be produced by the action and regulation of several lipid enzymes (phosphatidylserine synthase, phosphatidylserine decarboxylase, and phospholipase A) that are accordingly predicted to affect the activity of PgpB during different growth phases via the maintenance of appropriate PG, CL, and PE levels.
Substrate Binding Mechanism: Lyso Versus Diacyl Lipids-Our structural and functional analyses suggested that the TM3 tunnel is the major lipid substrate binding site. Lateral diffusion into the tunnel from the membrane entry between TMs 3 and 6 provides a convenient access to the catalytic site (Fig. 3B). Stabilizing a long acyl chain(s) in the tunnel is crucial not only for lipid substrate binding (K m ) but also for the catalytic rate (V max ) as seen in the kinetic analyses of 18:1 versus 6:0 LPA (Fig. 1, C and D). Based on the structure and docking model, 6:0 LPA might not be able to be stabilized in the tunnel due to its short length. Instead, phosphor binding in the active site would pull its short acyl chain out of the tunnel to a position in the front of the catalytic cavity. As expected, a flexible glycerol-acyl chain would unavoidably interfere with the His-163 side chain at the entry, affecting proton transfer by the catalytic triad evidenced by the dramatic drop in the rate. Most natural bacterial lipids have a C 16 -C 18 acyl chain. By stabilizing the long acyl chain in the tunnel, an optimal lipid catalysis can be achieved. Our data also revealed an important role of Lys-97 for lyso substrates (Fig. 7). In the LPP catalytic mechanism, Lys-97 was expected to stabilize the phosphor headgroup (5). As seen in many acid phosphatase and haloperoxidase structures (23)(24)(25), the analogous residues of Lys-97, Arg-104, and Arg-201 coordinate a phosphate/vanadate ion in the catalytic site (Fig. 4B). In contrast to other residues found in nearly identical positions, Lys-97 is 3.5 Å away from the ligand-bound state of its counterparts. To form proper phosphor coordination, Lys-97 may need to move toward the catalytic center. Phosphor binding would inevitably draw TM3 toward the PSGH loop to constrain the TM3 tunnel, in turn stabilizing the slim lyso substrate in the tunnel (Fig. 6, A and B). This conformational change may require a joint effort with Lys-93 by interacting with the glycerol backbone of LPA or the sphingoid base of S1P to enhance the stability of the lysolipid in the tunnel.
However, this motion may not be required or may even be unfeasible for diacyl substrates due to the fact that their two acyl chains simultaneously enter into the TM3 tunnel (Fig. 6C). In the PE complex structure, the glycerol backbone of PE actually blocked the tunnel neck (Fig. 4B). The full occupancy is probably sufficient to stabilize the substrate in the tunnel, as indicated by the dispensability of Lys-97 for diacyl substrates. Such a conformational adaptation induced by substrate binding allows both substrate diversity and optimal catalysis to be achieved. Determination of any protein motion with lyso versus diacyl lipids would provide a test for the induced-fit mechanism.
PGP-specific Catalytic Mechanism-Both Fan et al. (12) and our studies support a common LPP catalytic mechanism (11) for PgpB catalysis of LPA, S1P, PA, or DGPP. The catalytic triad Asp-211, His-207, and His-163 establishes a charge relay system; 1) D201 stabilizes His-207 for a nucleophilic attack to form a phosphohistidine intermediate with the substrate; 2) His-163 at the tunnel entry facilitates hydrolysis of the intermediate to release the phosphate ion to the periplasm and the dephosphorylated lipid back to the membrane layer.
However, this mechanism may be inapplicable to PGP as both Asp-211 and His-163 are not required for its dephosphorylation (Fig. 4C). But the essential role of His-207, which is located deeply inside the active site, indicates that the PGP reaction takes place in the same catalytic site. PGP has an additional phosphoglycerol moiety compared with PA (Fig. 1A). Attempts to dock PGP into the structure did not lead to any meaningful binding information, arguing that the protein may undergo a conformational change to accommodate the large PGP headgroup. Based on the structure, this could be achieved by moving the imidazole ring of His-163 away from the catalytic site entry (Fig. 4A). The fact that the H163A mutation improved PGP hydrolysis supports this idea (Fig. 4C). Depositioning the side chain of His-163 would probably disrupt the existing charge-relay wire. Therefore, an alternative mechanism has to be established for PGP hydrolysis.
The search for an alternative proton transfer route on the protein was not successful. Specific PGP binding conformations may allocate a water molecule as a H ϩ donor to initialize hydrophilic attack given the surface location of the active site. Whether PGP itself is involved in its own catalysis is unknown. In the mechanism of phosphoglycerate mutase, the phosphorisomerization reaction is mediated by a single histidine residue and the substrate itself (26). PGP is significantly different from other lipid phosphate substrates. A bulky phosphoglycerol moiety as a replacement for His-163 at the catalytic entry may serve as an alternative H ϩ donor to deliver a H ϩ to the terminal phosphor group given their adjacent positions (Fig. 1A). A selfcatalysis mechanism might explain the specificity of the PGP reaction due to its unique chemical structure.
Protein Expression and Purification-The E. coli pgpB gene was cloned into the pET22b vector (Novagen) to generate the C-terminal His 6 -tagged protein. Mutants were generated using standard site-directed mutagenesis. The PgpB wild type and mutant proteins were expressed in E. coli strain C41(DE3) grown in autoinduction medium (27) at 37°C for 2 h followed by a 20-h incubation at 25°C. To express the selenomethionine derivative, autoinduction minimal medium (28) was used. Harvested cells were suspended in lysis buffer containing 50 mM Tris-HCl, pH 7.5, 500 mM NaCl, and 10% glycerol and then ruptured using an EmulsiFlex-C3 homogenizer (Avestin) at 15,000 p.s.i. Cell debris was removed by centrifugation. The supernatant was ultracentrifuged at 150,000 ϫ g for 1 h. Membrane fractions were suspended in the lysis buffer and then incubated with 1% (w/v) DDM for 1.5 h at 4°C. After another ultracentrifugation at 150,000 ϫ g for 30 min, the supernatant was loaded on a Ni 2ϩ -NTA affinity column (GE Healthcare). The resin was washed with lysis buffer containing 40 mM imidazole. The protein was eluted with a buffer containing 50 mM Tris-HCl, pH 7.5, 500 mM NaCl, 400 mM imidazole, and 0.05% DDM. The protein was further purified using a size exclusion Superdex-200 GL column (GE Healthcare) equilibrated in a buffer of 20 mM Tris-HCl, pH 7.5, 200 mM NaCl, and 0.03% DDM. The peak fraction was directly used for in vitro assay or concentrated to 8 mg ml Ϫ1 for crystallization.
In Vitro Colorimetric Assay-Lipid phosphatase assay was carried out in vitro using a standard phosphate colorimetric approach (29). Briefly, the colorimetric reagent was prepared by mixing 34 mM ammonium molybdate in 5 M hydrochloric acid with 2.16 mM malachite green oxalate in a ratio of 1:3 (v/v) at room temperature and filtered before use. All substrates were dissolved in the reaction buffer containing 20 mM Tris-HCl, pH 7.5, 200 mM NaCl, 4% glycerol, and 0.5% DDM before use.
Each assay was carried out in a 100-l reaction mixture containing the appropriate amount of purified PgpB proteins at room temperature so that no more than 30% of the substrates was hydrolyzed during the reaction. The reaction was terminated by the addition of 200 l of the colorimetric reagent. 30 l of 1% polyvinyl alcohol was then added to the reaction to stabilize the phosphate complex. The reaction mixture was measured spectroscopically at 660 nm. The free phosphate concentration was calculated based on a standard curve measured with potassium phosphate.
Preparation of 32 P-Labeled PE-Radioactive PE was made biosynthetically in E. coli strain UE54 (MG1655 lpp-2⌬ara714 rcsF::mini-Tn10 cam pgsA::FRT-kan-FRT) in LB medium containing 5 Ci ml Ϫ1 [ 32 P]orthophosphate. This strain lacks the major anionic phospholipids PG and CL, accumulating PE to 95% of total phospholipids in deep stationary grown cells (13). The cells from 50 ml of culture were harvested, and the lipids were extracted as described. The purity of 32 P-labeled PE was verified by TLC on Silica Gel G thin-layer plates developed with chloroform/methanol/ammonia/H 2 O (60:37.5:1:3 v/v) and then visualized by a phosphorimaging system.
In Vitro PE Binding Assay-250 g of PgpB protein was incubated with 50 l of Ni 2ϩ -NTA affinity resin for 1 h. Unbound proteins were removed by washing with 20 mM Tris-HCl, pH 7.5, buffer containing 100 mM NaCl, 0.03% DDM, and 40 mM imidazole. 32 P-Labeled PE prepared above was dried, solubilized in 0.3% DDM, and then diluted 10ϫ as in binding assay. About 10,000 cpm of 32 P-labeled PE premixed with the indicated concentrations of POPE was incubated with the resin for 10 min. The resulting resin was washed with 500 l of the washing buffer 3 times and then eluted with a buffer supplemented with 400 mM imidazole. Radioactivity of the eluate was measured by liquid scintillation spectrometry to assess lipid-protein interaction. A resin without the PgpB protein was used as the control.
Crystallization of the PgpB-Lipid Complex-An E. coli total lipid extract (Avanti Polar Lipids) in chloroform was dried in an argon gas flow and resuspended in 1.25% DDM at a concentration of ϳ30 mM. The selenomethionine-substituted PgpB protein premixed with 5 mM (final concentration) of the lipid extract was crystallized using the sitting-drop vapor diffusion method at 20°C. The crystallization buffer contained 0.1 M N-carbamoylmethyl iminodiacetic acid, pH 6.5, and 10% polyethylene glycol 6000. Crystals were soaked in a cryo-protectant solution supplemented with 30% glycerol and then directly flash-frozen under liquid nitrogen. Note that crystallization and structural determination were done before the apo form structure was published; therefore, selenomethionine-derivative protein was used in the crystallization.
Structural Determination-Crystal diffraction data were collected at 100 K at the Swiss Light Source beamline X06SA (SLS, Villigen, Switzerland). Data processing was carried out using the programs XDS (30) and SCALA (31). The phases were obtained using the single wavelength anomalous dispersion (SAD) method by Autosol in the PHENIX software suite (32). The PgpB model was initially generated by the PHENIX Autosolution program and then completed manually in Coot (33). The PE ligand was carefully built based on the electron density map. The structure refinement was performed using Refmac (34,35). All residues fell into the favorable and allowable region of the Ramachandran plot. The statistics of data collection and refinement are shown in Table 1. The atomic coordinates of the PgpB-PE complex structure has been deposited in the Protein Data Bank (entry code 5JWY). All structural figures were prepared using graphic programs PyMOL (35). | 8,036 | 2016-07-12T00:00:00.000 | [
"Chemistry",
"Biology"
] |
Bombardment of Lunar Polar Crater Interiors by Out-of-ecliptic Ions: ARTEMIS Observations
Permanently shadowed regions (PSRs) inside lunar polar craters likely harbor volatiles which are of great interest for both science and resource utilization. The origin and evolution of this resource is in part driven by external space weathering, including the bombardment by space plasma ions. Previous work has investigated the flux of horizontal solar wind ions that are deflected into lunar polar craters by plasma wake electrostatic fields. Here, we constrain the flux of ions that travel northward or southward in the natural environment encountered by the Moon along its orbit. Using 9 years of in situ ion measurements gathered by the ARTEMIS mission, we find that all locations inside lunar craters are altered by a flux of out-of-ecliptic ions of 10−3 times the solar wind flux. In particular, the central floor of Shackleton’s crater is weathered by a non-null ion flux. The origin of northward and southward ions impacting the Moon is identified as (i) shocked thermalized solar wind ions in the terrestrial magnetosheath and (ii) the isotropic component of ion distributions in the terrestrial magnetotail. The energy spectrum of out-of-ecliptic ions is found to be flatter than the solar wind spectrum. Thus, sputtering of pure water ice irradiated by out-of-ecliptic ions would be created for more than 30% by >3 keV protons, unlike equatorial locations that are mostly sputtered by 1 keV protons. Future work may investigate the influence of the low, but nonzero flux of out-of-ecliptic ions reported here on the budget of volatiles in lunar PSRs.
Weathering of Permanently Shadowed Regions Inside Lunar Polar Craters
The obliquity of the Moon is only 6.7°, so that craters located near the lunar poles may harbor Permanently Shadowed Regions (PSRs). The cold environments of PSRs may accumulate and retain volatiles and are therefore of great interest for science and resource utilization (e.g., Arnold 1979;Nozette et al. 2001;Prem et al. 2020). As the Moon does not have an atmosphere or present-day global magnetic field, lunar polar crater PSRs are altered by external processes such as micrometeoroid bombardment, large impactors and possibly by space plasma electrons and ions. The role of impactors and space plasma particles on the volatile budget in PSRs is ambivalent: they act as both a source of elementary bricks required to create volatiles (including hydroxyl and water) (e.g., Füri et al. 2012), but they also vaporize, sputter, displace, and bury volatiles (e.g., Farrell et al. 2013Farrell et al. , 2015Szalay et al. 2019). A first step toward understanding the origin and evolution of volatiles in PSRs is the characterization of the influx of micrometeoroids and space plasma particles at each location inside lunar polar craters. Crater walls do not seem to protect PSRs from interplanetary dust, as their flux inside lunar craters may be as strong as anywhere else on the lunar surface, mostly because of the north and south toroidal source of dust originating from long-period comets (Pokorný et al. 2020). In this article, we further constrain the flux of space plasma ions weathering the interiors of lunar polar craters.
Space Plasma Ions which Bombard Lunar Polar Crater Interiors
To zeroth order, the majority of space plasma ions impacting the Moon originate in the solar wind, which consists of a beam of ∼1 keV/nucleon ions flowing parallel to the ecliptic plane, and therefore does not weather lunar polar crater interiors at all. However, we introduce hereafter the three known mechanisms by which ions access inside lunar polar craters: (1) the horizontal solar wind ion beam can be locally deflected into craters by ambipolar electric fields; (2) there are, in the natural environment encountered by the Moon along its orbit, ions traveling out of the ecliptic plane, northward or southward, which therefore directly enter into lunar polar craters; and (3) there are ions coming from the Moon itself.
(1) Plasma wakes are created inside lunar polar craters as the solar wind flows horizontally over them. The subsequent refilling of plasma wakes by electrons leads to the generation of ambipolar electric fields that deflect horizontal ions inside polar craters (Farrell et al. 2010(Farrell et al. , 2019Zimmerman et al. 2011Zimmerman et al. , 2012Zimmerman et al. , 2013Rhodes & Farrell 2020). Rhodes & Farrell (2020) have computed the flux of solar wind ions that impact this way at all locations inside four craters near the lunar South Pole: Shackleton, Haworth, Shoemaker, and Faustini. The previous authors found that the flux of deflected solar wind ions impacting most locations inside these craters is on the order of 10 −3 to 10 −1 times the horizontal solar wind flux. The topography inside craters appears to shield pocket valleys against deflected ions, where their flux may be zero. In addition, the width-to-depth ratio of Shackleton makes it different from the three other craters, as Rhodes & Farrell (2020) point out that the flux of electrostatically deflected ions is zero in a large region of Shackleton's central floor.
(2) In the solar wind, the ion bulk velocity can be deflected out of the ecliptic plane during transient events. For instance, Gosling et al. (1997) reported north and south ion flow deflections of more than 8°above and below the ecliptic plane during the passage of a Corotating Interaction Region. In addition, the natural environment of the Moon comprises ion populations not encountered by asteroids simply bathed in the solar wind, because of the presence of the terrestrial magnetosphere. When the Moon is upstream of the Earth bow shock, it is bombarded by energetic foreshock ions (with kinetic energies typically >1 keV) traveling away from the bow shock (Eastwood et al. 2005;Nishino et al. 2017;Xu et al. 2018). In the magnetosheath region, shocked thermalized solar wind ions may be deflected enough to access lunar polar crater interiors.
Finally, ions traveling northward or southward may exist in the terrestrial magnetotail which is crossed by the Moon for ∼5 days per lunar orbit. Three dynamic plasma environments are encountered by Earth's satellite in the geomagnetic tail, namely the plasma sheet, the plasma sheet boundary layer and the tenuous lobes. Positively charged particles there may consist of both solar wind ions (H + , He ++ ) and terrestrial ionospheric ions (H + , He + , O + , N 2 Poppe et al. 2016;Terada et al. 2017).
The flux of "lunar" ions that impact the interiors of lunar polar craters is unknown, but we note that backscattered and reflected solar wind ions may have gyroradii smaller than the lunar radius (Harada & Halekas 2016), so that they may enter inside lunar polar craters. Heavy ions sputtered from the lunar surface have such large gyroradii that they may not re-impact the Moon. Exospheric ions can be created anywhere around the Moon, so that an unknown fraction of them should directly weather lunar PSRs.
Previously, Poppe et al. (2018) compiled omnidirectional (averaged over all look directions) ion observations collected from 2012 to 2018 by the Acceleration, Reconnection, Turbulence, and Electrodynamics of the Moon's Interaction with the Sun (ARTEMIS) mission. They determined the longterm averaged omnidirectional flux of ions in the natural environment encountered by the Moon as a function of ion kinetic energy and position of the Moon around Earth (i.e., upstream of the bow shock, in the terrestrial magnetosheath and in the magnetotail). Here, we constrain northward and southward ion fluxes that directly enter inside lunar polar craters (population 2 above) by analyzing directionally resolved ion flux observations gathered by ARTEMIS from 2012 to 2021.
The analyzed data set and the methods used to process it are introduced in Section 2. Section 3 then presents the characteristics of the long-term flux of out-of-ecliptic ions, which are compared with the flux of electrostatically deflected ions computed by Rhodes & Farrell (2020) (population 1 above). Our findings are summarized and discussed in Section 4, where future areas of research are also highlighted. In particular, the contribution of lunar ions to "self-weathering" effects in lunar polar crater interiors deserves future investigation (population 3 above). This study relies on in situ ion measurements collected by the two probes of the ARTEMIS mission (Angelopoulos 2010). As highlighted by Poppe et al. (2018), the ARTEMIS ion data set is the best to date to estimate the long-term averaged ion environment seen by the Moon, thanks to the mission's 9 yr longevity, ion instruments put on board the satellites and the fact that the probes, in orbit around the Moon, co-orbit around Earth with the natural satellite in the different plasma regions it encounters: upstream of the bow shock, in the terrestrial magnetosheath and in the magnetotail. The two ARTEMIS probes, named ARTEMIS P1 and P2, are in highly elliptical near-equatorial orbits with periselene altitudes varying between 10 and ∼1000 km and aposelenes located between 10 and 12 R L from the center of the Moon (R L is the lunar radius, 1 R L = 1737 km).
As introduced in Section 1.2, observations in the "ion foremoon" region may contain lunar ions. However, the traveling direction of a lunar ion observed locally by an ARTEMIS probe does not necessarily determine whether this ion subsequently impacts lunar polar crater interiors. For instance, a reflected proton observed close to the equator by an ARTEMIS probe and seen traveling northward could be misinterpreted as having access to South Pole craters, whereas it may in fact not impact the Moon at all.
Thus, to exclude this potential "contamination" from the study of northward and southward ion streams encountered in the natural environment crossed by the Moon, we only use measurements collected far upstream of the Moon, at X SSE > 3 R L (SSE is the Selenocentric Solar Ecliptic system). When the Moon is upstream of the terrestrial bow shock, the solar wind convects lunar ions downstream of the Moon. This is confirmed by the statistical study of lunar ions by Harada et al. (2015) which shows that the data selection criterion that we use, X SSE > 3 R L , ensures that we do not capture lunar ions when upstream of the terrestrial bow shock. In addition, all lunar ion detections reported when the Moon is in the magnetosheath or magnetotail regions happened at distances to the lunar center lower than 2 R L (e.g., Tanaka et al. 2009;Poppe et al. 2012;Halekas et al. 2015;Cao et al. 2020). Lunar ions generated in the tail lobes, where the convection velocity is reduced compared with the solar wind, may access the X SSE > 3 R L equatorial region that we study here. However, this happens for very specific and unlikely convection velocity and magnetic field configurations (Poppe et al. 2013a).
We average data collected from January 2012 to January 2021. The ARTEMIS P1 and P2 probes spent during this time period a total time of respectively 1065 days and 1129 days in the studied X SSE > 3 R L region. Figure 1(a) shows the time spent by each ARTEMIS probe in the X SSE > 3 R L region each day of the 2012-2021 period. It can be seen that the rotation of the Earth-Moon system around the Sun repeatedly brought the ARTEMIS probe line-of-apsides close to the Sun-Earth direction, when the spacecraft can sample the X SSE > 3 R L region. It can also be seen that the ARTEMIS probes' orbital period of around 26 hours make them spend, on some days, entire days in the X SSE > 3 R L region. The data set used here frequently sampled the conditions seen by the Moon from 2012 to 2021, and using data from the two probes together further improves the time coverage (Figure 1(a)). We can therefore average together these measurements to construct a long-term averaged picture of the ion environment seen by the Moon, as done at Phobos around Mars by Nénon et al. (2019Nénon et al. ( , 2021. Figure 1(b) shows the time spent by each of the two ARTEMIS probes in the region of interest in 1°-wide GSE longitude bins, i.e., as a function of the position of the Moon around Earth (GSE is the Geocentric Solar Ecliptic system). The total observing times of 1065 days and 1129 days for ARTEMIS P1 and P2 are distributed so that each probe spent a total of 2.5-3.5 days in each 1°GSE longitude bin.
Averaging Ion Observations Collected from 2012 to 2021 by the ARTEMIS ESA Experiment
The ARTEMIS probes each carry two experiments designed to observe space plasma ions: the ElectroStatic Analyzer (ESA; McFadden et al. 2008aMcFadden et al. , 2008b which observes ions with kinetic energy per charge lower than 30 keV/q, and the Solid State Telescope (SST) experiment which observes 30 keV to several MeV ions. The angular resolution of SST data products is too coarse to constrain northward and southward ion fluxes, so that we only report on observations by ARTEMIS ESA.
ESA anodes observe 180°in a plane that contains the spin axis of the satellites, so that a 4π steradian coverage is achieved each 3.25 s satellite spin period. Ion data are collected according to different modes and packed into various data products with different resolutions in time, kinetic energy per charge and solid angle. We use here the "Full" data product collected in the two modes "Magnetospheric Fast Survey" and "Magnetospheric Slow Survey." In these data products, ion observations are organized in 32 energy bins and 88 angular sectors. Each observation is a 1-spin 4 s snapshot obtained either every 32 spacecraft spins ("Fast Survey" mode) or 128 spacecraft spins ("Slow Survey" mode). We find that we average together 539,559 independent data points (each consisting of a 32 energy bins by 88 angular sectors table) collected in the X SSE > 3 R L region by the two ARTEMIS probes from January 2012 to January 2021.
The ARTEMIS P1 and P2 data sets are combined and we average the two-probe data set in 1°wide GSE longitude bins that represent the position of the Moon around Earth. Background ion counts are created by particles penetrating the instrument housing and by natural radioactivity in the ESA microchannel plate detectors (McFadden et al. 2008a(McFadden et al. , 2008bHalekas et al. 2014). Background count rates were estimated and removed from observed count rates before conversion to ion flux in each GSE longitude bin independently. To compute the background, we have averaged, in each GSE longitude bin, count rates observed over the entire time period by the lowest energy bin of the instrument (i.e., the one most likely to show only background counts). This method accounts for time variation of the background linked to solar wind events, to the long-term variability of galactic cosmic ray particle fluxes and to possible energetic electrons in the terrestrial current sheet. Finally, recorded ion kinetic energies are corrected for the spacecraft surface potential, as measured by the Electric Field Instrument (EFI; Bonnell et al. 2009).
The 88 angular bins of the ESA data products analyzed here are defined in the ARTEMIS Despun, Sun-pointing, L-vector (DSL) coordinate system. Z DSL is aligned with the spin axis of the spacecraft, the X DSL -Z DSL plane contains the Sun direction (with X positive toward the Sun) and Y completes the orthogonal system (Angelopoulos 2009). From 2012 to 2021, Z DSL made an angle with Z GSE between 164°and 172°for the two ARTEMIS probes. Ions traveling anti-sunward along −X GSE are therefore observed with a traveling DSL longitude, noted j DSL , that changed only very slightly over time between 179°.8 and 180°. 2 and DSL latitudes, noted θ DSL , varying between −15°and +12°. We present in Section 3 anisotropy maps of ion fluxes in DSL coordinates to not distort angular sectors by converting them to another coordinate frame. In addition, working with the DSL coordinate system eases the integration of ion fluxes over look directions, as in particular the orientation of DSL with respect to GSE changes over time. However, the 8°-16°angular offset between the DSL and GSE coordinate systems needs to be properly considered when interpreting ion fluxes integrated over look directions in the DSL system (see Section 3.2).
We finally note that the ARTEMIS ESA experiment cannot identify either the charge or mass of observed ions. We can therefore report hereafter only on ion kinetic energy per charge, and not ion kinetic energy, and cannot use ion mass or mass per charge information to further identify the origin of observed ions (e.g., He ++ of the solar wind or O + ions from the terrestrial ionosphere).
3. Long-term Averaged Fluxes of Ions Impacting the Moon on its Subsolar and Antisubsolar Points, and Inside Polar Craters 3.1. Long-term Averaged Anisotropy of Ion Fluxes Figure 2 gives for selected positions of the Moon around Earth (GSE longitude) the long-term averaged flux of 700 eV/q and 9000 eV/q ions as a function of ion traveling direction in DSL coordinates (see Section 2.2). Upstream of the terrestrial bow shock in either the dawn sector (Figure 2(a)) or dusk sector (Figure 2(g)), 700 eV/q solar wind ions mostly travel anti-sunward. Suspicious high latitude fluxes are seen in the j DSL = 180°-225°angular sectors. This appears to be an instrument artifact that has not been removed by the background correction method (see Section 2.2). We later show in Section 3.2 that it does not impact the conclusions of this study. At 9 keV/q, two ion populations are observed upstream of the bow shock (Figures 2(b), (h)): (1) energetic ions traveling antisunward and (2) terrestrial foreshock ions that travel away from Earth, likely along magnetic field lines connecting the spacecraft to the bow shock (noting, for instance, that a j DSL of 270°c orresponds to a GSE direction longitude near 90°). The highlatitude noise reported at 700 eV/q is not seen at 9 keV/q (Figures 2(b), (h)). We note that foreshock ion signatures seem broader in panel (h) than in panel (b). However, this may be linked to instrument background rather than to characteristics of these ions. Indeed, averaged foreshock ion fluxes are lower in panel (b) than in panel (h), so ion fluxes in angular sectors surrounding the peak sector in panel (b) may be below the instrument background level.
In the magnetosheath region downstream of the Earth bow shock (Figures 2(c)-(d)), some shocked heated ions are seen to travel away from Earth, while others have been deflected enough to reach elevation angles larger than 45°in absolute value. As we show in later sections, these high-elevation ions may directly enter inside lunar polar craters.
Deep in the terrestrial magnetotail (Figures 2(e)-(f)), both 700 eV/q and 9000 eV/q ions show an isotropic component that leads to the existence of ions traveling northward and southward, which can therefore directly enter South Pole and North Pole craters, respectively. Isotropic distributions in the magnetotail for 100 s of eV to 10 s of keV ions were already reported at distances of 20 Earth radii (R E ) from the center of Earth by Walsh et al. (2011) using Cluster observations and Wang et al. (2013) using THEMIS observations. The physical processes that act to isotropize ion distributions in the tail are not fully understood or conclusively identified (Walsh et al. 2011). We report here that similar isotropic distributions are observed at lunar distances of ∼60 Re downtail. For 9000 eV/q ions, an additional population of earthward and tailward ions is observed (Figure 2(f)), likely because of reconnection events at the near X-line (generating tailward ions at the Moon) and distant X-line (earthward ions). One can see that the Moon is exposed to as much earthward energetic ion flux as tailward ion flux, as already reported by Kiehas et al. (2018) based on ARTEMIS ESA ion measurements.
Origin of Ion Fluxes Impacting the Subsolar, Antisubsolar, and Polar Points on the Moon
Ion fluxes determined from the ARTEMIS observations are then integrated over appropriate angular sectors to compute the flux of ions that impact the Moon at four points: (1) subsolar point, (2) antisubsolar point, and the flux of ions directly weathering the interior of lunar craters located near (3), the North Pole, and (4) the South Pole. At each of these four points on the Moon, we performed two integrations over look directions in DSL coordinates (Section 2.2). The first integration is obtained by taking into account all ions coming from within a cone around the local zenith with a half-opening angle of 45°. The second integration is performed within a cone with a halfopening angle of 22.5°. The choice of these two opening angles is driven by the 22.5°elevation width of the ESA angular sectors. Using a cone with a half-opening angle of 45°, we can compute the flux of ions that directly weather the center of Shackleton crater. Indeed, this point is exposed to all ion velocities making an angle with the local normal lower than 57°( see Figure 1 of Rhodes & Farrell 2020), and averaging ion observations over 45°in DSL coordinates may show ions coming from a direction inclined with the local normal of at maximum 60°(see Section 2.2). Using an integration cone with a half-opening angle of 22.5°enables to extract the most vertical ions. Figure 3 shows the long-term averaged flux of ions that impact the subsolar, antisubsolar, and polar points as a function of GSE longitude of the Moon around Earth and ion kinetic energy per charge. Boundaries between the region upstream of the bow shock, the magnetosheath, and the magnetotail are identified with red vertical dashed lines, based on the results of Poppe et al. (2018). As expected, ions impacting the subsolar point have a lower flux and a broader kinetic energy range when the Moon crosses the magnetotail (Figures 3(a), (b)).
When the Moon is upstream of the terrestrial bow shock in the undisturbed solar wind, the flux of ions reaching lunar polar crater interiors (Figures 3(e)-(h)) is mostly below the ARTEMIS ESA background level. One can see at kinetic energies from 300 eV/q to 2000 eV/q the high latitude noise identified in Section 3.1, that is likely an instrument artifact. A real signal of out-of-ecliptic ions impacting lunar polar crater interiors is found at GSE longitudes between 240°and 280°w ith kinetic energies as high as 10 s of keV. The location and kinetic energies of these ions make them likely to be terrestrial foreshock ions. Foreshock ions may slightly access the antisubsolar point of the Moon (Figures 3(c)-(d)).
In the terrestrial magnetosheath, some shocked ions are thermalized enough to access lunar polar crater interiors (Figures 3(e)-(h)) but cannot access the antisubsolar point (Figures 3(c)-(d)). Finally, most of the ion flux impacting the polar and antisubsolar points is encountered when the Moon is in the magnetotail region, where ion fluxes are quasi-isotropic. Figures 4(a) and (b) give the ion flux impacting respectively the subsolar point and polar points, averaged within a 45°4 (<400 eV/q) kinetic energies (Figure 4(c)) are mostly encountered when the Moon is in the magnetosheath and magnetotail regions.
The fluence of out-of-ecliptic ions entering lunar polar craters while the Moon is upstream of the bow shock (red curve on Figure 4(d)) is negligible compared with fluences in the magnetosheath and magnetotail regions (green and blue curves on Figure 4(d)). We therefore find that the noise reported in Section 2.2, which is clearly visible as the ∼700 eV/q bump (red curve), does not impact the conclusions of our study, as its contribution is negligible over magnetosheath and magnetotail ion fluences. Above a few keV/q, ions that directly weather polar crater interiors mostly come from crossings of the Moon in the terrestrial magnetotail (blue curve on Figure 4
Intensity of Out-of-ecliptic Ion Fluxes Entering Lunar Polar Craters
Figure 4(e) gives, as a function of ion kinetic energy per charge, the ratio of ion fluxes impacting the subsolar point to those directly entering lunar polar craters (averaged within an ion direction cone of 45°, see Section 3.2). At solar wind kinetic energies ∼700 eV/q, the lunation-averaged ion flux on the subsolar point is more than three orders of magnitude stronger than the flux of polar ions. However, the ratio of subsolar to polar ion fluxes is of only a factor of 3 at kinetic energies greater than 10 keV/q. This relatively low ratio comes from the isotropic component of 10 s of keV/q ions in the magnetotail (Figure 2(f)). The fact that ion fluxes on the subsolar point are a factor of 3 more intense than on polar regions at these kinetic energies comes from energetic tailward ions associated to reconnection events.
The flux of ions that directly enter lunar polar craters is, integrated over all ion kinetic energies, of 1.7 × 10 5 cm −2 s −1 , which is around one-thousandth of the solar wind flux (2 × 10 8 cm −2 s −1 ). One can compare the flux of out-of-ecliptic ions computed here (10 −3 the solar wind flux) with the flux of horizontal ions electrostatically deflected inside craters, shown on top crater maps by Figure 3 of Rhodes & Farrell (2020).
Some localized pocket valleys inside the craters Haworth, Shoemaker, and Faustini were found by the previous authors to be completely sheltered from deflected horizontal ions due to local topography. In addition, a large region around the central floor of Shackleton was proposed to be completely unaltered by space plasma ions (see Figure 3 of Rhodes & Farrell 2020). We find that these locations are in fact weathered by a flux of ions that is not zero but that is of at least 10 −3 times the solar wind flux. However, most locations inside the South Pole craters studied by Rhodes & Farrell (2020) are exposed to a flux of electrostatically deflected ions of 10 −2 -10 −1 the solar wind flux, where electrostatic deflection is therefore the dominant source of bombarding ion flux over out-of-ecliptic ions.
Out-of-ecliptic Ion Energy Spectrum and Surface Sputtering
As out-of-ecliptic ions are mostly encountered when the Moon crosses the terrestrial magnetosheath and magnetotail (Figure 3), their energy spectrum is flatter than the solar wind spectrum (Figure 4(d)). We study here the influence of ion energy spectra on sputtering of neutral particles from the surface, which is a fundamental process at airless bodies throughout the solar system. In particular, we investigate which ion kinetic energies contribute to sputtering due to ions impacting the subsolar point and polar regions, respectively. To do so, we have computed the flux of neutral atoms sputtered from a surface made of either Fe50 olivine (MgFeSiO 4 ) or pure water ice. We note that water ice on the Moon is likely mixed with regolith (Li et al. 2018); however, we use pure water ice as an end-member test case. All observed ions are assumed to be protons and we use the energy-dependent sputtering yields published by Nénon & Poppe (2020) for Fe50 olivine with a density of 3.8 g/cc and those given by Cassidy et al. (2013) for pure water ice. Figures 5(a) and (b) give the cumulative distribution of neutral sputtered flux as a function of proton kinetic energy, i.e., the sputtered flux created by protons with kinetic energies going from E k = 0 to the abscissa kinetic energy, normalized by the neutral flux sputtered by all kinetic energies together. Sputtering of olivine and water ice at the lunar subsolar point is, as expected, generated by a narrow range of kinetic energies around 600 eV, as 80% (between 0.1 and 0.9 on the y-axis of Figure 5) of the total sputtered flux is Figure 5. Flux of neutral particles sputtered from a surface by protons with kinetic energies between 0 and the abscissa kinetic energy, normalized by the flux sputtered by all proton kinetic energies together. Panel (a): for Fe50 olivine with a density of 3.8 g/cc using sputtering yields from Nénon & Poppe (2020). Panel (b): for pure water ice, using sputtering yields from Cassidy et al. (2013). created by 400-1500 eV protons. Pure water ice exposed to only the flux of out-of-ecliptic ions would be sputtered a thousand times slower than at regions exposed to the solar wind. However, we reveal on Figure 5(b) that this process would be the result of the bombardment by ions with greater kinetic energies than the solar wind, as 50% of water ice sputtering would be due to >1.5 keV protons and 20% due to >5 keV protons ( Figure 5(b)). This comes from the combination of (1) the relatively flat energy spectrum of out-of-ecliptic ions with (2) the energy dependence of the pure water ice sputtering yield, which increases with increasing proton kinetic energy.
Summary and Discussion
Since 2012, the ElectroStatic Analyzer experiment (ESA) on board the two ARTEMIS probes has been collecting directionally resolved ion flux measurements in the environment encountered by the Moon along its orbit (upstream of the Earth bow shock, in the terrestrial magnetosheath and in the terrestrial magnetotail). This data set reveals the long-term averaged flux of ions which, in the natural environment that is not disturbed by the Moon itself, travel northward or southward and therefore directly enter lunar polar craters. The lunationaveraged flux of out-of-ecliptic ions is dominated by thermalized ions in the magnetosheath and by the isotropic component of ion distributions encountered in the terrestrial magnetotail (Figures 3 and 4).
As a result of the out-of-ecliptic ion population that bombards the Moon, we find that all locations inside lunar polar craters and PSRs are weathered by a long-term averaged flux of ions that is of at least 10 −3 times the solar wind flux. In particular, these ions bombard regions that are otherwise protected by topography from horizontal solar wind ions deflected by wake electric fields (Rhodes & Farrell 2020), including the central floor of Shackleton's crater. The influence of out-of-ecliptic ions encountered in the terrestrial magnetosheath and tail on the life cycle and budget of volatiles on Shackleton's central floor could be investigated in the future (e.g., Tucker et al. 2020) using the energy spectra reported on Figures 3 and 4.
The energy spectrum of out-of-ecliptic ions is broader than the solar wind spectrum. One consequence of this is that sputtering of pure water ice which would be irradiated only by out-of-ecliptic protons would be generated by protons more energetic than the typical 1 keV solar wind energy, as 50% of sputtering would be due to >1.5 keV protons and 30% to >3 keV protons.
Future work can be conducted along three lines of research to further identify the characteristics of ions that bombard and alter lunar PSRs. First, Rhodes & Farrell (2020) considered a perfectly horizontal ion beam while studying the deflection of ions inside lunar craters. Future efforts may consider the deflection of ions with non-null elevation angles. The coarse angular resolution of the ARTEMIS ESA data products does not enable a study of ion populations with low elevation angles, for instance ions traveling with an elevation angle of 8°above or below the ecliptic plane during the passage of a CIR (Gosling et al. 1997). However, observations of the solar wind with fine angular resolutions by the ACE and Wind spacecraft can be analyzed to study the influence of the distribution of solar wind elevation angles over time on the flux of electrostatically deflected ions inside lunar polar craters.
A second future line of work could investigate the flux of "lunar" ions impacting lunar polar crater interiors. In particular, solar wind protons reflected over magnetic anomalies have been reported to have densities as high as 10 −2 the solar wind density in the lunar wake (Xu et al. 2020). For conditions where these reflected protons had relatively smaller gyroradii (e.g., during periods of higher IMF strength), it may be possible that reflected protons gyrate directly into lunar polar regions as opposed to gyrating farther downstream and into the wake.
Finally, the specie of out-of-ecliptic ions that enter lunar polar craters is not measured by the ARTEMIS ESA ion experiment. Ion measurements with mass (or mass per charge) and directional resolution conducted in the terrestrial magnetotail at lunar distances would for instance enable us to constrain the flux of terrestrial O + ions that may supply oxygen in lunar PSRs. | 7,505.4 | 2021-06-01T00:00:00.000 | [
"Physics"
] |
Clinical Implications of Noncoding Indels in the Surfactant-Encoding Genes in Lung Cancer
Lung cancer arises from the accumulation of genetic mutations, usually in exons. A recent study identified indel mutations in the noncoding region of surfactant-encoding genes in lung adenocarcinoma cases. In this study, we recruited 94 patients with 113 lung cancers (88 adenocarcinomas, 16 squamous cell carcinomas, and nine other histologies) who had undergone surgery in our department. A cancer panel was designed in-house for analyzing the noncoding regions, and targeted sequencing was performed. Indels in the noncoding region of surfactant-encoding genes were identified in 29/113 (25.7%) cases and represent the precise cell of origin for the lung cancer, irrespective of histological type and/or disease stage. In clinical practice, these indels may be used as clonal markers in patients with multiple cancers and to determine the origin of cancer of unknown primary site.
Introduction
Large-scale sequencing of human tumor samples has implicated unexpected pathways and mutational processes in carcinogenesis [1,2]. The growing power of whole-genome sequencing now enables the discovery of significantly altered loci in noncoding sequences. The 98% of the genome that does not code for proteins includes transcribed but untranslated exons of genes, introns, and noncoding regulatory genetic elements, some of which may harbor clinically important and targetable DNA alterations [3,4]. In 2017, Imielinski et al. reported the presence of noncoding insertions/deletions (indels) in certain cancer types, which is reportedly a prevalent and hitherto unrecognized mutational process linking cellular lineage and cancer [5].
In that study, Imielinski et al. analyzed whole-genome sequences of lung adenocarcinoma using a somatic burden test based on Gamma-Poisson regression for the analysis of both indel and single nucleotide variant somatic mutations [5]. They found recurrent somatic indel mutations in noncoding regions of surfactant protein genes, the major transcriptional product of type II pneumocytes in the lung [5]. Using statistical analysis of whole-genome sequences across a diverse collection of cancers, they determined that other tumor types harbor similarly prevalent hotspots of noncoding somatic indel mutations, targeting lineage-defining genes (i.e., ALB, TG, and LIPF) [5]. These highly expressed genes define cell types that play essential biosynthetic roles in the physiology of their respective organs and constitute the precise cell of origin for the respective cancers.
The frequent indel mutation of this gene class is a previously undescribed feature of cancer genomes and quite surprising; however, it has yet to be elucidated whether these indels are a hallmark of carcinomas arising from secretory epithelial cell types or a more general phenomenon, and whether these indels are harbored by lung cancers other than adenocarcinoma. Furthermore, it remains to be determined at which stage of tumor phylogeny these noncoding indel mutations occur, how they are involved in oncogenesis, what effects they have on biological behavior, and what their clinical implications are.
As a rule, in whole-genome sequencing analysis the identification of spurious hotspots is quite broad, while the number of samples is limited compared with whole-exome capture data. Accordingly, based on the results of the above-mentioned study [5], we designed a custom panel for targeting the noncoding regions of six genes (SFTPA, SFTPB, SFTPC, ALB, TG, and LIPF). In our method, samples from surgical cases could be examined in our own laboratory, and the abundant clinical data in our facility could be analyzed for correlation. Namely, we investigated the correlation between these indels and the clinical, pathological and/or genomic findings, and attempted to characterize the cancers harboring these indels. In addition, we explored the possibility of a clinical application of these indels from the viewpoint of their clinical value as clonal markers and in the identification of the primary focus in cancers of unknown origin.
Patient Characteristics
Ninety-four patients with lung cancer who had undergone surgery between July 2014 and March 2018 in our department were enrolled in this study in an unbiased manner. These subjects comprised 64 men and 30 women ranging in age from 49 to 90 years (mean 70.7 ± 12.5 years). Nineteen patients had double primary. Therefore, 113 cancers in total were analyzed. Histologically, they included 88 cases of adenocarcinoma, 16 cases of squamous cell carcinoma, four cases of pleomorphic carcinoma, four cases of small-cell carcinoma, and one case of large-cell carcinoma.
Detection of Noncoding Indels
A cancer panel was designed in-house based on data published previously to analyze the noncoding regions of six genes-surfactant protein A1, B, and C, as well as albumin, lipase, and thyroglobulin. Indels in the noncoding region of surfactant-encoding genes were identified in 29/113 (25.7%) cases (Table S1). The detection rate of the indels in the three-surfactant protein (SFTP) genes was 6/113 (5.3%) in SFTPA1, 23/113 (20.4%) in SFTPB, and 2/113 (1.8%) in SFTPC. The co-occurrence of noncoding indels in SFTPA and SFTPB was found in 2 patients (Case 1 and 25 in Table S1). These results were similar to those previously reported by Imielinski et al. (i.e., 6.0% in SFTPA1, 12.7% in SFTPB, and 5.1% in SFTPC) [5]. Allele fraction of detected noncoding indels was on average 34.4 ± 17.6%, relatively higher than that of the frequent mutations detected in the coding regions in lung cancer. In lung cancer specimens, no noncoding indels were detected in the albumin, lipase, or thyroglobulin genes, which indicated that the noncoding indels among the six genes are organ-specific, as demonstrated by a previous study [5].
As a confirmatory experiment, some of the detected noncoding indels, which exhibited high allele frequency, were validated through Sanger sequencing ( Figure S1).
Patient Characteristics with or without Noncoding Indels
Lung cancers with and without noncoding indels were compared in terms of patient and tumor characteristics (Table 1). There were no significant differences in age, sex, performance status, smoking status, tumor size and location, CT findings, surgical procedure, pathological vessel and lymphatic invasion, or pathological stage. Peripheral, central, and middle lung cancers were defined as cancers with primary lesions located in the outer, inner, or middle third of the lung field, respectively. GGN, ground-glass neoplasm.
Surgical Outcome with or without Noncoding Indels
There was no significant difference in either postoperative disease-free survival or overall survival between patients with lung cancers harboring noncoding indels and those not harboring noncoding indels (Figure 1).
Somatic Driver Mutations with or without Noncoding Indels
Targeted sequencing was performed using the cancer panel designed in-house to analyze the exon regions of 53 lung cancer-related genes [6,7]. When the frequencies of the affected pathways were compared between adenocarcinomas and squamous cell carcinomas, RAS (rat sarcoma viral oncogene homolog) pathway was found to be affected significantly more frequently in adenocarcinomas, while the chromatin remodeling, epigenetic, transcription, and TP53 pathways were affected significantly more frequently in squamous cell carcinomas ( Figure S2). Meanwhile, there was no significant difference in the frequency of major driver mutations such as those of KRAS, TP53 and EGFR in relation to the presence or absence of noncoding indels (p = 0.93, 0.92, and 0.43, respectively) ( Figure 2).
Somatic Driver Mutations with or without Noncoding Indels
Targeted sequencing was performed using the cancer panel designed in-house to analyze the exon regions of 53 lung cancer-related genes [6,7]. When the frequencies of the affected pathways were compared between adenocarcinomas and squamous cell carcinomas, RAS (rat sarcoma viral oncogene homolog) pathway was found to be affected significantly more frequently in adenocarcinomas, while the chromatin remodeling, epigenetic, transcription, and TP53 pathways were affected significantly more frequently in squamous cell carcinomas ( Figure S2). Meanwhile, there was no significant difference in the frequency of major driver mutations such as those of KRAS, TP53 and EGFR in relation to the presence or absence of noncoding indels (p = 0.93, 0.92, and 0.43, respectively) ( Figure 2). Peripheral, central, and middle lung cancers were defined as cancers with primary lesions located in the outer, inner, or middle third of the lung field, respectively. GGN, ground-glass neoplasm.
Surgical Outcome with or without Noncoding Indels
There was no significant difference in either postoperative disease-free survival or overall survival between patients with lung cancers harboring noncoding indels and those not harboring noncoding indels (Figure 1).
Somatic Driver Mutations with or without Noncoding Indels
Targeted sequencing was performed using the cancer panel designed in-house to analyze the exon regions of 53 lung cancer-related genes [6,7]. When the frequencies of the affected pathways were compared between adenocarcinomas and squamous cell carcinomas, RAS (rat sarcoma viral oncogene homolog) pathway was found to be affected significantly more frequently in adenocarcinomas, while the chromatin remodeling, epigenetic, transcription, and TP53 pathways were affected significantly more frequently in squamous cell carcinomas ( Figure S2). Meanwhile, there was no significant difference in the frequency of major driver mutations such as those of KRAS, TP53 and EGFR in relation to the presence or absence of noncoding indels (p = 0.93, 0.92, and 0.43, respectively) ( Figure 2). small-cell carcinomas harbored noncoding indel mutations ( Figure 3). Interestingly, noncoding indel mutations were detected in poorly differentiated carcinomas such as squamous cell and pleomorphic carcinomas at frequencies similar to those in adenocarcinomas. Figure 3). Interestingly, noncoding indel mutations were detected in poorly differentiated carcinomas such as squamous cell and pleomorphic carcinomas at frequencies similar to those in adenocarcinomas.
Noncoding Indels Arising in Various Histological Cancer Types
Case I A 72-year-old man underwent left upper division segmentectomy because a ground-glass neoplasm was found in the left upper lobe ( Figure 4A). The lesion was pathologically diagnosed as adenocarcinoma in situ (AIS), TisN0M0, stage 0 ( Figure 4B). AIS is a well-differentiated adenocarcinoma, and the survival rate after resection is reportedly 100% [8]. Three indels in the noncoding region of the SFTPB gene were detected ( Table 2). The detection of noncoding indels in a case of such early, well-differentiated lung cancer suggested that noncoding indel mutations occur in the early phase of tumor evolution.
Noncoding Indels Arising in Various Histological Cancer Types
Case I A 72-year-old man underwent left upper division segmentectomy because a ground-glass neoplasm was found in the left upper lobe ( Figure 4A). The lesion was pathologically diagnosed as adenocarcinoma in situ (AIS), TisN0M0, stage 0 ( Figure 4B). AIS is a well-differentiated adenocarcinoma, and the survival rate after resection is reportedly 100% [8]. Three indels in the noncoding region of the SFTPB gene were detected ( Table 2). The detection of noncoding indels in a case of such early, well-differentiated lung cancer suggested that noncoding indel mutations occur in the early phase of tumor evolution.
The Presence of Noncoding Indels According to Histology
Based on the histological classification, 23 (26.1%) of 88 adenocarcinomas, four (25.0%) of 16 squamous cell carcinomas, one (25.0%) of four pleomorphic carcinomas, and one (25.0%) of four small-cell carcinomas harbored noncoding indel mutations ( Figure 3). Interestingly, noncoding indel mutations were detected in poorly differentiated carcinomas such as squamous cell and pleomorphic carcinomas at frequencies similar to those in adenocarcinomas.
Noncoding Indels Arising in Various Histological Cancer Types
Case I A 72-year-old man underwent left upper division segmentectomy because a ground-glass neoplasm was found in the left upper lobe ( Figure 4A). The lesion was pathologically diagnosed as adenocarcinoma in situ (AIS), TisN0M0, stage 0 ( Figure 4B). AIS is a well-differentiated adenocarcinoma, and the survival rate after resection is reportedly 100% [8]. Three indels in the noncoding region of the SFTPB gene were detected ( Table 2). The detection of noncoding indels in a case of such early, well-differentiated lung cancer suggested that noncoding indel mutations occur in the early phase of tumor evolution. Case II A 79-year-old woman was found to have a massive tumor measuring 90 mm in diameter in the left lower lobe and underwent left lower lobectomy combined with resection of the thoracic wall and diaphragm ( Figure 4C). Histologically, the lesion was diagnosed as squamous cell carcinoma, pT4N0M0, stage IIIB ( Figure 4D). An indel in the noncoding region of the SFTPB gene was detected (Table 2).
Thus, noncoding indels were detected in lesions ranging from early-stage lung cancer, as in case I, to massive and poorly differentiated cancer, as in this case.
Case III
A 78-year-old woman was found to have a massive tumor measuring 78 mm in diameter in the left upper lobe and underwent left upper lobectomy and chest wall resection. In this case, with pleomorphic carcinoma, histopathologically, the cancer was composed of papillary adenocarcinoma and sarcomatoid cancer, pT3N0M0, stage IIB ( Figure 5A-C). Case III A 78-year-old woman was found to have a massive tumor measuring 78 mm in diameter in the left upper lobe and underwent left upper lobectomy and chest wall resection. In this case, with pleomorphic carcinoma, histopathologically, the cancer was composed of papillary adenocarcinoma and sarcomatoid cancer, pT3N0M0, stage IIB ( Figure 5A-C).
Whole-exome sequencing analysis of each component was performed, and phylogenetic analysis showed that the separate components shared several common mutations and that the sarcomatous component ramified from the carcinomatous component in the early phase of the evolutionary process and accumulated several mutations that were different from those of the carcinomatous component ( Figure 5D). In terms of the noncoding indel mutations, the same noncoding indel was detected in both the adenocarcinoma and sarcomatoid cancer components ( Table 2), and phylogenetic analysis revealed that this indel mutation occurred in the common trunk in the early phase of tumor evolution ( Figure 5E).
Noncoding Indels as a Clonal Markers for Multiple Lung Cancers
There are no specific clinical or radiological features that can be used to dependably distinguish multiple primary cancers from intrapulmonary metastases, and the differential diagnosis is at times perplexing in the clinical setting. As both a more precise and clinically applicable method for the diagnosis of multiple lung cancers, we performed mutation analysis of noncoding indels and evaluated the possibility of identifying the clonality of individual lung cancers using their mutations as a diagnostic marker. Whole-exome sequencing analysis of each component was performed, and phylogenetic analysis showed that the separate components shared several common mutations and that the sarcomatous component ramified from the carcinomatous component in the early phase of the evolutionary process and accumulated several mutations that were different from those of the carcinomatous component ( Figure 5D). In terms of the noncoding indel mutations, the same noncoding indel was detected in both the adenocarcinoma and sarcomatoid cancer components (Table 2), and phylogenetic analysis revealed that this indel mutation occurred in the common trunk in the early phase of tumor evolution ( Figure 5E).
Noncoding Indels as a Clonal Markers for Multiple Lung Cancers
There are no specific clinical or radiological features that can be used to dependably distinguish multiple primary cancers from intrapulmonary metastases, and the differential diagnosis is at times perplexing in the clinical setting. As both a more precise and clinically applicable method for the diagnosis of multiple lung cancers, we performed mutation analysis of noncoding indels and evaluated the possibility of identifying the clonality of individual lung cancers using their mutations as a diagnostic marker.
Importantly, detection of noncoding indels in the SFTP gene was helpful in determining whether either of the tumors were primary or metastatic in nature, as shown in Cases IV-XIV.
Cases IV-XII
In cases IV-X, one of the two tumors harbored noncoding indels, whereas the other did not ( Figure 6A-G). In cases XI and XII, SFTPB mutations were identified in both tumors, but they differed in nucleotide position and variance ( Figure 6H,I). Thus, individual tumor in these patients did not share the same noncoding indel. In addition, the mutation profiles in the coding region also differed completely between the two tumors ( Figure 6L-T). Such clear differences in mutation patterns supported the judgment of double primary cancer. Importantly, detection of noncoding indels in the SFTP gene was helpful in determining whether either of the tumors were primary or metastatic in nature, as shown in Cases IV-XIV.
Cases IV-XII
In cases IV-X, one of the two tumors harbored noncoding indels, whereas the other did not ( Figure 6A-G). In cases XI and XII, SFTPB mutations were identified in both tumors, but they differed in nucleotide position and variance ( Figure 6H,I). Thus, individual tumor in these patients did not share the same noncoding indel. In addition, the mutation profiles in the coding region also differed completely between the two tumors ( Figure 6L-T). Such clear differences in mutation patterns supported the judgment of double primary cancer.
Cases XIII and XIV
Targeted deep sequencing revealed that the noncoding indel mutation in 2 tumors in each patient involved SFTP ( Figure 6J,K). Furthermore, the nucleotide position and variance in the mutation were entirely consistent (Table 2). Likewise, two lung cancers in each patient were characterized by identical gene mutations in the coding region ( Figure 6U,V)
Cases XIII and XIV
Targeted deep sequencing revealed that the noncoding indel mutation in 2 tumors in each patient involved SFTP ( Figure 6J,K). Furthermore, the nucleotide position and variance in the mutation were entirely consistent (Table 2). Likewise, two lung cancers in each patient were characterized by identical gene mutations in the coding region ( Figure 6U,V). Thus, a diagnosis of solitary, intrapulmonary metastasis was made in these cases.
Estimation of the Primary Focus in Cases of Carcinoma of Unknown Origin
Noncoding indels in the SFTP gene may indicate the precise cell of origin in lung cancer. Application of this finding to the clinical setting may provide an answer to the important clinical question as to whether mediastinal lymph node cancer is a form of lung cancer.
In addition to one surgical case, four cases of mediastinal lymph node cancer, although non-surgical cases, were also examined (Table S2). Among five mediastinal lymph node cancers, noncoding indels were detected in two cases (Cases XV and XVI, Figure 7).
Estimation of the Primary Focus in Cases of Carcinoma of Unknown Origin
Noncoding indels in the SFTP gene may indicate the precise cell of origin in lung cancer. Application of this finding to the clinical setting may provide an answer to the important clinical question as to whether mediastinal lymph node cancer is a form of lung cancer.
In addition to one surgical case, four cases of mediastinal lymph node cancer, although nonsurgical cases, were also examined (Table S2). Among five mediastinal lymph node cancers, noncoding indels were detected in two cases (Cases XV and XVI, Figure 7). Case XV Surgical resection of the lymph node revealed squamous cell carcinoma ( Figure 7A,B). Immunohistochemically, tumor cells were negative for thyroid transcription factor-1 (TTF-1). Targeted sequencing was performed using a surgical specimen and it showed that the cancer harbored noncoding indels in the SFTPA1 and SFTPB genes ( Table 2). These indels represent an origin in the lung.
Case XVI
Endobronchial ultrasound-guided transbronchial needle aspiration (EBUS-TBNA) revealed that the tumor was adenocarcinoma ( Figure 7C,D), but immunohistochemical stain for TTF-1 was negative. Using the EBUS specimen, targeted sequencing was performed and revealed that the cancer harbored noncoding indels in the SFTPB gene, leading to a diagnosis of mediastinal lung cancer ( Table 2).
In summary, SFTP noncoding indels were detected in two (Cases XV and XVI) of five cases of mediastinal lymph node cancer, and it was validated genomically that these mediastinal cancers originated from the lung (lung cancer).
Case XV
Surgical resection of the lymph node revealed squamous cell carcinoma ( Figure 7A,B). Immunohistochemically, tumor cells were negative for thyroid transcription factor-1 (TTF-1). Targeted sequencing was performed using a surgical specimen and it showed that the cancer harbored noncoding indels in the SFTPA1 and SFTPB genes ( Table 2). These indels represent an origin in the lung.
Case XVI
Endobronchial ultrasound-guided transbronchial needle aspiration (EBUS-TBNA) revealed that the tumor was adenocarcinoma ( Figure 7C,D), but immunohistochemical stain for TTF-1 was negative. Using the EBUS specimen, targeted sequencing was performed and revealed that the cancer harbored noncoding indels in the SFTPB gene, leading to a diagnosis of mediastinal lung cancer (Table 2).
In summary, SFTP noncoding indels were detected in two (Cases XV and XVI) of five cases of mediastinal lymph node cancer, and it was validated genomically that these mediastinal cancers originated from the lung (lung cancer).
SFTP Indels Near A or G Repeat Motifs
The indel sites in our analysis were shown in Figure 8A. Furthermore, we examined the sequence features in 50-base neighborhood of highly expressed indels to identify the sequence contexts that might be associated with SFTP indel hotspots. Applying the Multiple Em for Motif Elicitation (MEME) algorithm (http://meme-suite.org/), we discovered significant enrichment of either an A repeat (E = 5.9 × 10 −10 ) or G repeat (E = 5.9 × 10 −10 ) motif in the vicinity of SFTP indels ( Figure 8B).
SFTP Indels Near A or G Repeat Motifs
The indel sites in our analysis were shown in Figure 8A. Furthermore, we examined the sequence features in 50-base neighborhood of highly expressed indels to identify the sequence contexts that might be associated with SFTP indel hotspots. Applying the Multiple Em for Motif Elicitation (MEME) algorithm (http://meme-suite.org/), we discovered significant enrichment of either an A repeat (E = 5.9 × 10 −10 ) or G repeat (E = 5.9 × 10 −10 ) motif in the vicinity of SFTP indels ( Figure 8B).
Discussion
In 2017, Imielinski et al., using advanced analytical techniques, revealed that some lung adenocarcinomas harbor noncoding indel hotspots in surfactant protein genes (SFTPA1, SFTPB, and SFTPC) [5]. They obtained whole-genome sequencing reads mainly from the TCGA database and
Discussion
In 2017, Imielinski et al., using advanced analytical techniques, revealed that some lung adenocarcinomas harbor noncoding indel hotspots in surfactant protein genes (SFTPA1, SFTPB, and SFTPC) [5]. They obtained whole-genome sequencing reads mainly from the TCGA database and analyzed whole-genome sequences from 613 tumors representing 13 tumor types (79 lung adenocarcinomas, 50 lung squamous cell carcinomas, 64 cutaneous melanomas, 50 papillary thyroid carcinomas, 23 bladder cancers, 105 breast cancers, 32 glioblastomas, 16 head and neck squamous carcinomas, 54 hepatocellular carcinomas, 5 kidney cancers, 19 low-grade gliomas, 40 gastric cancers, and 76 prostate cancers), thus demonstrating a 25-fold enrichment of noncoding indels in SFTP gene (95% CI: (13.2, 47.4)) in lung adenocarcinoma versus other tumor types, even after correcting for sample-specific variations in indel density (p = 5.6 × 10 −23 , Wald test, logistic regression) [9][10][11]. In general, whole-genome sequencing leads to the enormous number of candidate regions; in addition, measurement is often difficult, and the number of cases with available data is limited. In our study, we intensively and efficiently searched for and analyzed the previously reported noncoding indels in our cases of surgically treated lung cancer, using a cancer panel designed in-house. The method with use of this cancer panel was advantageous in that it allowed comparison with abundant clinical data available in our facility, without limitation in the number of cases.
The indel hotspots are reported to target a special class of loci, encoding protein products that are manufactured in large quantities by a single cell type within a specific organ [5]. Moreover, the secretion of these lineage-defining proteins is a primary function of that cell type and vital to healthy organ and systems physiology. Surfactant proteins are surface-active agents produced and secreted by type II alveolar epithelial cells, representing major secretory proteins in the lung. SFTP is a lineage-defining gene in lung, and thus the noncoding indels in SFTP gene link cellular lineage and lung cancer [5].
Imielinski et al demonstrated that noncoding indels in the SFTP gene were detected exclusively in lung adenocarcinoma [5]. However, our study revealed that not only adenocarcinoma but also other types of poorly differentiated carcinomas such as squamous cell carcinoma and pleomorphic carcinoma in the lung, harbored noncoding indels. The frequency of noncoding indels in lung cancer had no association with the clinical findings such as stage and histology; indels therefore appear to be a general phenomenon that can occur at random in all lung cancers. Our study represents a follow-up experiment of the whole-genome sequencing study [5]; the following differences may exist between the two studies: (i) characteristics of the patients enrolled, (ii) depth of sequencing coverage, and (iii) DNA extraction methods. While Imielinski et al. used the data of whole-genome sequencing, we performed targeted deep sequencing; the mean sequencing coverage across targeted bases in our study was 1119X compared to 69X-121X in their study. Moreover, in our study, tumor cells were collected from formalin-fixed, paraffin-embedded (FFPE) tissues using a laser-capture microdissection system, and DNA was extracted after tumor cell collection and removal of normal tissues; this may have led to an increased allele fraction i.e., increased chance of detection of the targeted bases.
We previously reported that pleomorphic carcinoma composed of carcinomatous and sarcomatous components evolves from a common ancestral clone [12,13]. The phylogenetic analysis also showed that the sarcomatous component had ramified from the carcinomatous component in the early phase of the evolutionary process and accumulated several mutations that were different from those of the carcinomatous component [12]. In this study, noncoding indels were detected in both the carcinomatous and sarcomatous components in the pleomorphic carcinoma in case III. This finding indicated that this mutation occurs in the stage involving the common ancestral clone, i.e., in the early phase of tumor evolution [14]. This is also supported by the detection of noncoding indels in the early cancer lesion in case I with AIS.
In cases of multiple lung cancers, the clinical distinction between primary and metastatic tumors is sometimes difficult, making treatment selection challenging. Thus, we previously conducted lung cancer mutation analysis by targeted deep sequencing and found that mutations in individual lung cancers can serve as clonal markers, allowing identification of the clonality of individual tumors [15]. In this study, on the assumption that mutations in the noncoding region would also serve as clonal markers, we compared different tumors regarding the mutation pattern and found that noncoding indels in the SFTP gene can serve as clonal markers. In our experience, it is sometimes difficult to determine whether the tumor is primary or metastatic even when the data on mutations in the exon region is available; therefore, in such cases, noncoding indel data plays a supplementary role in diagnosis. Comparative approaches to the mutation patterns in the coding and noncoding regions, when combined, may help resolve the current dilemma of misdiagnosis in the clinical setting.
In general, cancers are composed of cell populations with distinct molecular and phenotypic features, a phenomenon termed intratumor heterogeneity [16,17]. Intratumor heterogeneity, associated with heterogeneous protein function, may foster tumor adaptation, phenotypic aggravation, and/or therapeutic failure through Darwinian selection [18,19]. In contrast, a pivotal driver mutation serves as the trigger of clonal expansion and is estimated to be retained homogenously within tumors of the same clone [20][21][22]. These events can be explained by "trunk and branch" mutation models, i.e., mutational events in early clonal progenitors are represented within the "trunk" of the tumor [16,17]. Such trunk somatic aberrations, present at the early stages of tumor development, are likely to occur ubiquitously at all sites of the disease. In contrast, later somatic events that occur following branched separation of subclones represent heterogeneous events. Such subclonal heterogeneity may be spatially separated between regions of the same tumor or its metastatic sites [16][17][18][19]. In this context, clonally dominant "trunk" aberrations are important clonal markers, and noncoding indels, with their allele fraction always being high at 11-92%, are considered "trunk" mutations. The detection of the same noncoding indel in different sites within the tumor in cases III also suggested that these indels are "trunk" mutations. Primary and metastatic tumors can be discriminated by determining whether such ubiquitous mutations are identical.
Cancer of unknown primary site (CUP) is the collective term for a group of cancers in which the anatomical site of origin remains unidentified after a metastatic focus had been found [23]. CUP is characterized by clinically unconfirmed primary malignancy, early occurrence of dissemination, rapid progression, and difficult prediction of the metastatic pattern [23,24]. The incidence of CUP is reported to be approximately 0.5-6.7% [25][26][27][28]. It occurs more frequently in men than in women and most frequently involves the lymph nodes and bones [28]. Histologically, most cases are adenocarcinomas [28]. CUP rarely occurs in mediastinal lymph nodes, accounting for only 1.0-1.5% of all CUP cases [27,28].
The lung is highly likely to be the primary site of metastatic mediastinal lymph node cancer. In approximately 40% of reported cancers of the hilar, mediastinal, and cervical lymph nodes, the site of primary malignancy was estimated to be the lung [28]. Taking into account the pathway of regional lymph flow in the lung, occult microcarcinoma can be considered to be present in the lung in cases of mediastinal lymph node CUP [29,30]. However, it is not rare for cancer of a distant organ, such as colorectal cancer or breast cancer, to metastasize to mediastinal lymph nodes [31][32][33][34][35], so identification of the primary focus has important implications for treatment selection. In particular, lung cancer is a prototype of precision oncology, and once a diagnosis of lung cancer is made, it is easier to develop effective treatment strategies using EGFR-TKI or anti-PD-1 antibodies as indicated by the tumor biomarkers. In fact, in cases XV and XVI in this study, immune checkpoint therapy using anti-PD-1 antibody achieved favorable control of the disease (Table S2). Histopathological and immunohistochemical examinations are often helpful for the estimation of the primary origin, but almost never definitive. For instance, TTF-1 immunostaining has been conventionally used as an important marker in patients with unknown primary cancer. In the present study, TTF-1 immunostaining was negative in Cases XV and XVI, whereas the presence of noncoding indels revealed their origin in lung. Thus, it is assumed that noncoding indel may be a more accurate marker than TTF-1 immunostaining. Because SFTP is a lineage-defining gene for the lung, analysis of its noncoding indels can genomically and definitively demonstrate that CUP is derived from the lung. One limitation in terms of clinical application is that there is still a significant number of CUP of unknown origin owing to the low detection rate of SFTP noncoding indels in lung cancer.
Much remains to be elucidated regarding the pathogenetic implications of noncoding indels. These mutations may be neutral and hence not affected by strong selection pressure. One possibility is that these mutations are not causally tied to the associated genetic lesions, but rather tag a particular evolutionary trajectory in tumorigenesis that is reflected in the transcriptional signature. The limitations of our study lie in the fact that it is based on data from a single institution and was performed retrospectively. Further molecular and translational studies, ideally on a multi-institutional basis, will be needed in the future to improve our understanding of the mutational processes and molecular pathogenesis of cancers and to make these findings more applicable to the clinical setting.
Study Population
The survey included 94 patients who had undergone surgery for lung cancer in our department between July 2014 and March 2018 and four patients not subjected to surgery but diagnosed with mediastinal lymph node cancer. All participants provided written informed consent prior to participation in the genetic research. The research was conducted in accordance with the Declaration of Helsinki, and the study was approved by the Institutional Review Board Committee of Yamanashi Central Hospital (Yamanashi, Japan). In total, 117 cancers were subjected to the mutation analysis, which included 75 patients with a single primary cancer, 19 patients with double primary lung cancer, and four patients with mediastinal lymph node cancer (non-surgical cases).
The medical records of the 94 consecutive patients with primary lung cancer who had undergone surgery at our hospital between July 2014 and March 2018 were retrospectively reviewed. The patients' data were obtained from the cancer registry database of our institution. The information collected from the patients' medical records included the preoperative characteristics, CT findings (tumor size and location), histopathological diagnosis, operative procedure, and follow-up data.
Histological typing was performed according to the World Health Organization's classification (third edition) [36], and clinical staging was performed according to the International Union Against Cancer tumor-node-metastasis classification (eighth edition) [37,38].
Sample Preparation
Serial sections of FFPE tissues were stained with hematoxylin and eosin. Tumor cells were collected from FFPE tissues using an ArcturusXT laser-capture microdissection system (Thermo Fisher Scientific, Waltham, MA, USA). In case III, cancer cells were collected from histologically different components in each tumor by laser-capture microdissection. Panel sequencing was performed for each component, and the mutation profiles were compared.
DNA was extracted using a QIAamp DNA FFPE Tissue Kit (Qiagen, Hilden, Germany). FFPE DNA quality was evaluated using primers for the ribonuclease P (RNase P) locus [39]. A peripheral blood sample was collected from each patient just prior to surgery. The buffy coat was isolated following centrifugation, and DNA was extracted from the buffy coat using a QIAamp DNA Blood Mini Kit with a QIAcube system (Qiagen).
Targeted Deep Sequencing and Data Analysis
A previous report showed that indel mutations are frequently identified in surfactant protein genes (SFTPA1, SFTPB, and SFTPC) in lung adenocarcinoma, the albumin gene in liver cancer, gastric lipase gene in stomach carcinoma, and thyroglobulin gene in thyroid carcinoma [5]. Based on these results, we designed a custom panel to target the noncoding regions of these six genes. The target region covers 17.08 kilo base pairs, and 172 amplicons were included in this panel (Table S3). Using this panel, we constructed a library and performed targeted sequencing, as described previously [40][41][42]. In brief, sequencing libraries were prepared using an Ion AmpliSeq Library Kit (Thermo Fisher Scientific). The barcode and adaptor were ligated, and library samples were purified using Agencourt AMPure XP reagent (Beckman Coulter, Brea, CA, USA). Library concentrations were determined using an Ion Library Quantitation Kit (Thermo Fisher Scientific). Emulsion PCR and chip loading were performed on the Ion Chef with the Ion Personal Genome Machine (PGM) Hi-Q View Chef Kit (Thermo Fisher Scientific), and sequencing was performed on the Ion PGM Sequencer (Thermo Fisher Scientific).
The sequence data were processed using standard Ion Torrent Suite Software running on the Torrent Server. Raw signal data were analyzed using Torrent Suite. The pipeline included signal processing, base calling, quality score assignment, read alignment to the human genome 19 reference (hg19), quality control of mapping, and coverage analysis. Following data analysis, annotation of single nucleotide variants, insertions and deletions was performed using an Ion Reporter Server System (Thermo Fisher Scientific), and lymphocyte DNA from peripheral blood was used as a control to detect variants (tumor-normal pair analysis), as described previously [39,43,44].
Sanger Sequencing
PCR was performed using FFPE DNA as a template and primer pairs flanking the insertion and deletion sites. PCR products were purified using the ExoSAP-IT (Thermo Fisher Scientific) according to the manufacturer's instructions. Sequencing was performed with BigDye Terminator v3.1. PCR products were purified with BigDye XTerminator Purification Kit (Thermo Fisher Scientific) and subsequently analyzed by the 3500 Genetic Analyzer (Thermo Fisher Scientific).
Whole-Exome Sequencing
Whole-exome sequencing and multiplex PCR were performed using buffy coat DNA and tumor DNA with an Ion AmpliSeq Exome RDY Kit (Thermo Fisher Scientific). The pooled PCR amplicons were treated with FuPa reagent to partially digest the primer sequences and phosphorylate the amplicons. The amplicons were ligated to adaptors with the diluted barcodes of the Ion Xpress Barcode adapters Kit (Thermo Fisher Scientific).
Adaptor-ligated amplicon libraries were purified using Agencourt AMPure XP reagent (Beckman Coulter). Each library was diluted, and the same amount of each library was pooled for a single sequence reaction. Emulsion PCR and chip loading were performed on the Ion Chef with the Ion PI Hi-Q Chef Kit (Thermo Fisher Scientific). Sequencing was performed using an Ion PI Hi-Q Sequencing Kit on the Ion Proton Sequencer (Thermo Fisher Scientific).
In Silico Analysis
For further inference of the phylogenies and estimation of the evolutionary distances, the neighbor-joining method was implemented to cluster the nonsilent mutations, and a phylogenetic tree was constructed [45]. The "ape" and "phangorn" (R version 3.2.3 in Linux) packages were used for these analyses.
Motif Analysis
Genomic sequences (FASTA files) were extracted from ±50 base pairs upstream and downstream of the mutation sites using the UCSC genome browser. Sequence data were uploaded to MEME (http://meme-suite.org/tools/meme) to determine the enriched motifs near the mutation sites.
Quantification and Statistical Analysis
Continuous variables are presented as the means ± SDs and were compared using unpaired Student's t-test. One-way analysis of variance and the Tukey-Kramer multiple comparison test were used to detect significant differences between groups. Chi-square tests were used to compare the categorical data between groups. Recurrence-free survival was defined as the period from the day of operation to the day of recurrence or the day of final follow-up. Overall survival time was defined as the period from the day of operation to the day of death or that of the last follow-up evaluation. Survival was assessed using the Kaplan-Meier method, and comparisons among the survival curves were conducted using the log-rank test. All statistical analyses were performed using the JMP function in the SAS software package (SAS Institute, Inc., Cary, NC, USA). P values less than 0.05 in the two-tailed analyses were considered to denote statistical significance.
Conclusions
We identified indels in the noncoding region of surfactant-encoding genes in approximately 25% of lung adenocarcinoma, squamous cell carcinoma, pleomorphic carcinoma, and small-cell carcinoma cases. These indels indicate the precise cell of origin of lung cancer. In patients with multiple cancers, differences between the indels can be analyzed to determine whether the tumor is primary or metastatic. Furthermore, in patients with cancers of unknown primary sites, the lung can be identified as the primary site based on the presence of these indels. These findings strengthen the framework for implementation of indel detection in clinical practice as a method to enable identification of the origin of cancer and thus, improve treatment.
Supplementary Materials: The following are available online at http://www.mdpi.com/2072-6694/11/4/552/s1, Figure S1: Validation of noncoding indels by Sanger sequencing, Figure S2: Lung cancer mutation profiles in association with the functional pathways. Table S1: Noncoding indel mutations detected in the samples, Table S2: Clinical characteristics of the five cases with cancers of unknown origin, Table S3: Noncoding regions targeted in the panel. | 8,871.8 | 2019-04-01T00:00:00.000 | [
"Medicine",
"Biology"
] |
Special Issue: Phage–Bacteria Interplay in Health and Disease
Bacteriophages are obligatory parasites propagating in bacterial hosts in a lytic or lysogenic/pseudolysogenic cycle [...].
Bacteriophages are obligatory parasites propagating in bacterial hosts in a lytic or lysogenic/pseudolysogenic cycle. Phages are the most abundant biological particles in the world, being responsible for: (i) dissolved and particulate organic matter circulation via host cell lysis, (ii) regulation of numbers and biodiversity of populations, (iii) horizontal gene transfer (HGT) via transduction, or indirectly via transformation of bacterial DNA released during cell lysis, and, finally, (iv) lysogenic conversion by temperate phages. Therefore, phages greatly affect microbial diversification as an integral part of each ecological niche, including the human body. The tremendous dynamics of phage-host interactions result in the continuous flow of genetic material, which drives the co-evolution of both entities.
Advances in recent years in molecular biology, multi-omics, and bioinformatic approaches have contributed to the deeper insight into and functional analyses of a wide range of phage-bacteria interactions at the individual and population levels, and their consequences on health and disease. The Special Issue of Viruses "Phage-Bacteria Interplay in Health and Disease" focuses primarily on the regulation and functioning of human/mammal microbial ecosystems as the consequence of specific and non-specific virus-bacteria interactions, bacterial defence against phages which can drive the outcome of the disease/infection, phages as human immunomodulators, and the description of innovative experimental techniques characterizing the phage traces in mammals.
A total of 13 manuscripts, including 10 original and 3 review papers, have been published in this Special Issue. The collection contains recent papers that could be roughly classified into three themes comprising the following: (1) survival strategies of bacteria in response to phage infection as well as the impact of phages on bacterial virulence and pathogenicity (theme 1, five papers); (2) influence of lytic and temperate phages on the human microbiome as well as human virome composition (theme 2, three papers); (3) phages as potential antibacterial therapeutics (theme 3, five papers). All papers reflect the impact of phage-bacteria as well as phage-bacteria-host interactions on human health, disease, and economic activities. They also highlight the great importance and relevance of the topic addressed.
Streptococcus pyogenes is a Gram-positive β-hemolytic pathogen that strictly infects humans and can cause superficial skin infections, pharyngitis, toxin-mediated diseases (e.g., streptococcal toxic shock syndrome (STSS)), and invasive diseases of subcutaneous tissues [1]. Bacteria have developed different defence strategies against phage infection ranging from adsorption prevention to a wide panel of intracellular mechanisms [2]. Beerens et al. [1] described several mechanisms utilized by S. pyogenes to protect against Phage A1. Phage A1, as a temperate phage, was able to infect S. pyogenes strains, resulting in complete resistance against subsequent phage infections, most likely by providing superinfection immunity. Furthermore, the lysogenization did not influence the humoral host immune response or bacterial virulence and did not induce ampicillin tolerance to this common antistreptococcal antibiotic. The authors demonstrated that the type II-A CRISPR-Cas system of S. pyogenes acquires new spacers upon phage infection, which are increasingly detectable in the absence of a capsule. Finally, the authors showed that the number of infecting phages is limited through binding to released streptococcal outer membrane vesicles. The authors proposed a multistage interaction model between S. pyogenes and Phage A1 [1].
Outer membrane vesicles (OMVs) of Gram-negative bacteria are important virulence factors as decoys against a variety of antibacterials but are also an element in host-bacteria interplay, and intra-or inter-species bacterial communication [3,4]. In the paper of Augustyniak et al. [5], the authors studied the Pseudomonas aeruginosa antiviral strategy based on outer membrane vesicles (OMVs) against the LPS-specific phages KT28 and LUZ7. To investigate the passive and active role played by OMVs towards these phages, the OMVs derived from the phage-sensitive wild-type PAO1 strain, and an LPS-deficient mutant (∆wbpl PAO1) resistant to both phages, were used. It turned out that naturally formed OMVs efficiently protected P. aeruginosa from phage infection. Next, it was verified whether OMVs derived from the wild-type PAO1 strain were able to sensitize the LPS-deficient mutant (∆wbpl PAO1) to the tested phages. The growth kinetic curves and one-step growth assay revealed no sensitization event [5].
Clostridioides difficile is one of the most common causes of antibiotic-related nosocomial infections with symptoms ranging from mild diarrhea to life-threatening pseudomembranous colitis and/or toxic megacolon [6]. Therefore, one work explored the therapeutic potential of the C. difficile phages, with a particular interest in phage CDHS-1 propagating on the hypervirulent 027 ribotype C. difficile R20291. The study focused on the transcriptomic takeover of phage CDHS-1 during infection, and analyses revealed that the majority of the bacterial genes connected with metabolism and toxin production were downregulated at the early phase of CDHS-1 replication, whereas genes related to DNA synthesis and ATP production were among those upregulated at this stage. The holin, endolysin, and structural genes were upregulated towards the mid-log and late phases of the phage replication. The retrieved phage-resistant clones and lysogens showed relatively low virulence in the larval model of Galleria mellonella compared to the wild-type strain. The data suggest that phage infection both reduces bacterial colonization and negatively impacts bacterial pathogenicity, supporting the therapeutic potential of the phage for human and animal use [6].
Topka-Bielecka et al. [7] described the characterization of phage vB_EfaS-271 specific to Enterococcus faecalis strains. The report indicated that vB_EfaS-271 can significantly decrease the number of viable E. faecalis cells in biofilms formed on catheters and in liquid cultures and revealed no considerable toxicity to mammalian cells, influencing neither their viability nor morphology. The efficiency of phage resistance development was especially significant under conditions of high MOI values; nevertheless, phage vB_EfaS-271 was considered promising for phage therapy [7].
Lichvariková et al. [8] performed genome analyses of the prophage content in Streptococcus agalactiae (GBS) clinical isolates to verify the prevalence of prophages versus the bacterial virulence potential. Based on the whole genome sequencing and PCR methods, the authors identified eight groups of prophages, amongst which the highest prevalence was observed for a prophage from group A (71%) and a satellite prophage from group B (62%). They observed that the prophage distribution did not differ between clinical and screening strains, but it was unevenly distributed in MLST (multilocus sequence typing) sequence types. This study implies that prophages could be beneficial for the host bacterium [8].
Phages have an important role in shaping bacterial communities. Phages also impact human health by infecting bacteria forming human microbiomes in the gut, respiratory tract, skin, or vagina. Happel et al. [9] investigated the prevalence and persistence of (pro)phages and their associations with the vaginal bacterial community composition in the female genital tract of 13 South African adolescents, who received no antibiotics. The shotgun metagenome sequencing of cervicovaginal samples collected longitudinally showed that the most prevalent phage family was Siphoviridae, followed by Myoviridae, Podoviridae, Herelleviridae, and Inoviridae. The results pointed out that some prophages were present in cervicovaginal secretions of multiple participants, suggesting that prophages, and thus bacterial strains, are shared between adolescents. Shaping the biodiversity of bacterial populations, these viruses contribute to local fluctuations in the vaginal microbiome [9].
Bacterial vaginosis (BV) is characterized by a reduction in Lactobacillus (L.) spp. abundance and increased colonization of facultative anaerobes, such as Gardnerella spp. [10]. The paper of Jacobsen et al. [11] related to vaginal microbiota, studying the role of phages in the perturbation of the vaginal bacterial community. Vaginal samples from 48 patients who underwent in vitro fertilization treatment for non-female factor infertility were subjected to metagenomic analysis of purified virus-like particles. It turned out that the vaginal virome was linked with the BV status and bacterial community structure. The viral community structure was strongly correlated with the presence of key beneficial bacterial species (L. crispatus and L. iners) as well as with known pathobionts (Gardnerella spp. and Atopobium vaginae) [11].
Mayne et al. [12] investigated the influence of an anti-salmonella phage preparation (BAFASAL ® ) on the ex vivo human gut microbiome composition and function. Using a novel in vitro assay called RapidAIM as well as 16S rRNA gene sequencing and metaproteomic approaches, the authors documented that the ex vivo human gut microbiota composition and function were unaffected by BAFASAL ® treatment, which proves the GRAS provision (generally recognized as safe) [12].
At present, traditional antimicrobials are becoming ineffective against multidrugresistant bacterial pathogens. Therefore, phages are increasingly beginning to be recognized as an alternative or supportive therapeutic agent [13].
Shimamori et al. [14] investigated the efficacy of the Staphylococcus aureus phage in the treatment of atopic dermatitis (AD), the most common inflammatory skin disease, in an atopic mouse model. As previously documented, phage SaGU1 can infect a broad range of S. aureus in AD patients, whereas it does not kill strains of the symbiotic bacterium S. epidermidis. In this work, the authors showed that administration of SaGU1 to the back skin of mice reduced both S. aureus counts and the disease exacerbation caused by these bacteria. Furthermore, the application of S. epidermidis in combination with SaGU1 inhibited the emergence of phage-resistant S. aureus, indicating that synergistic use of probiotics and phages can be promising and effective in the treatment of S. aureus-associated AD [14].
Since interactions between phages and mammals strongly affect the possible applications of phages, tools to study how phages circulate in the body and can be deposited in tissues are highly desirable. Understanding this need, Kaźmierczak et al. [15] proposed red fluorescent protein (RFP)-labeled E. coli lytic phages as a new tool for the investigation of phage interactions with cells and tissues. The deposition of an RFP-displaying phage in multiple murine organs ex vivo after various routes (intravenous, oral, rectal) of phage administration was verified. The most effective intravenous administration led to effective distribution kinetics with phage presence in the lymph nodes, lungs, and liver after 20 min, whereas in the muscles and spleen/lymph nodes, this occurred 30 min and 1 h after administration, respectively [15].
Iszatt et al. [16] provided a thorough review of therapies against widespread or emerging multidrug-resistant bacterial pathogens in respiratory medicine, the challenges faced in generating preclinical data, in vitro and in vivo respiratory models using phages, and, finally, clinical trials of phage therapy in respiratory infection treatment such as acute cystic fibrosis or chronic lung infections [16].
An interesting review of Al Ishaq et al. [17] addressed the issues concerning the efficacy of phages against WHO priority pathogens. A comprehensive literature search was conducted in the EMBASE, Web of Science, and PubMed databases for articles published from 2010 to 2020. This systematic review critically evaluated and summarized 29 published articles on phages as a treatment option against S. aureus, Klebsiella pneumoniae, P. aeruginosa, and E. faecalis infection models. It also illustrated appropriate phage selection criteria, as well as recommendations for successful therapy. The main conclusions from the analysis of the selected literature were that phage applications (single or in cocktails) are effective and safe, can work synergistically in combination with certain antibiotics, and may induce the emergence of phage resistance [17].
In parallel with attempts to use phages against nosocomial human pathogens, there has been much work conducted on the use of these viruses as alternative methods to control zoonotic and foodborne pathogens. This problem was addressed in a review paper written by Alomari et al. [18]. The authors discussed commercial phage products used in the biocontrol of foodborne pathogens in various foods as well as the role of phages in food protection and sanitation procedures. Central attention was given to phage efficacy in experimental models of infections with foodborne pathogens, including Salmonella spp., E. coli, Campylobacter spp., Vibro spp., and P. aeruginosa, and other pathogens, such as Staphylococcus spp., Streptococcus spp., Klebsiella spp., Acinetobacter spp., and Mycobacterium sp. The varied therapeutic and immunomodulatory activities of phages on humoral and cellular immune response mechanisms were also discussed [18].
Conflicts of Interest:
The authors declare no conflict of interest. | 2,766.4 | 2022-05-01T00:00:00.000 | [
"Medicine",
"Biology"
] |
Identification of Positive Regulators of the Yeast Fps1 Glycerol Channel
The yeast Fps1 protein is an aquaglyceroporin that functions as the major facilitator of glycerol transport in response to changes in extracellular osmolarity. Although the High Osmolarity Glycerol pathway is thought to have a function in at least basal control of Fps1 activity, its mode of regulation is not understood. We describe the identification of a pair of positive regulators of the Fps1 glycerol channel, Rgc1 (Ypr115w) and Rgc2 (Ask10). An rgc1/2Δ mutant experiences cell wall stress that results from osmotic pressure associated with hyper-accumulation of glycerol. Accumulation of glycerol in the rgc1/2Δ mutant results from a defect in Fps1 activity as evidenced by suppression of the defect through Fps1 overexpression, failure to release glycerol upon hypo-osmotic shock, and resistance to arsenite, a toxic metalloid that enters the cell through Fps1. Regulation of Fps1 by Rgc1/2 appears to be indirect; however, evidence is presented supporting the view that Rgc1/2 regulate Fps1 channel activity, rather than its expression, folding, or localization. Rgc2 was phosphorylated in response to stresses that lead to regulation of Fps1. This stress-induced phosphorylation was partially dependent on the Hog1 MAPK. Hog1 was also required for basal phosphorylation of Rgc2, suggesting a mechanism by which Hog1 may regulate Fps1 indirectly.
Introduction
Under conditions of high osmolarity stress, many fungal species, including Saccharomyces cerevisiae, maintain osmotic equilibrium by producing and retaining high concentrations of glycerol as a compatible solute [1,2]. Intracellular glycerol concentration is regulated in S. cerevisiae in part by the plasma membrane aquaglyceroporin, Fps1 [3][4][5]. Increased external osmolarity induces Fps1 closure, whereas decreased osmolarity causes channel opening, both within seconds of the change in external osmolarity [5]. This channel is required for survival of a hypo-osmotic shock when yeast cells have to rapidly export glycerol to prevent bursting [3,5], and is required for controlling turgor pressure during fusion of mating yeast cells [6]. The pathway responsible for regulation of Fps1 in response to changes in osmolarity has not been delineated, but appears to involve the Hog1 (High Osmolarity Glycerol response) MAP kinase [5,7,8]. Hog1 is activated in response to hyper-osmotic stress to mediate the biosynthesis of glycerol and perhaps its retention as well through inhibition of Fps1 channel activity. Although a hog1D mutant displays an elevated rate of glycerol uptake in the absence of osmotic stress, it is not impaired for Fps1 closure in response to hyper-osmotic stress [5], suggesting that Hog1 regulates the basal activity of Fps1.
Fps1 is regulated not only in response to changes in external osmolarity, but also by exposure to acetic acid [9], and in response to trivalent metalloids (e.g. arsenite and antimonite) [10,11]. Both acetic acid and metalloids enter the cell through Fps1 and induce Hog1 activation. Fps1 is down-regulated by acetic acid treatment through ubiquitin-mediated endocytosis, which is triggered by its phosphorylation by Hog1 on Thr231 and Ser537 [9]. By contrast, metalloids down-regulate both the expression of FPS1 and its channel activity [10].
We describe the identification of a pair of paralogous S. cerevisiae proteins, Ask10 and Ypr115w that are positive regulators of glycerol efflux through Fps1. The ASK10 and YPR115w genes encode members of a family of pleckstrin homology (PH) domain proteins in yeast that includes Slm1 and Slm2 [12]. The Ask10 protein shares 41% sequence identity with its paralog Ypr115w. Although PH domains are known to bind phosphatidylinositides [13], the PH domains of Ask10 and Ypr115w are interrupted by long insertions, prompting the suggestion that they bind different ligands [12], or even serve as protein-binding domains [14].
The ASK10 gene was suggested previously to play a role in cell wall biogenesis through its identification in a genetic screen for activators of the Skn7 transcriptional regulator (Activator of SKN7) [15], which has been reported to influence cell wall assembly and cell wall stress signaling [16][17][18][19]. Additionally, Ask10 has been reported to be a component of the Srb/Mediator complex of RNA polymerase II [20], which is required for repression of several stress responsive genes [21,22]. In this context, Ask10 was implicated in oxidative stress-induced destruction of the Srb11 C-type cyclin [20].
There are no reports on the function of YPR115w, or on the consequences of mutations in both Ask10 and Ypr115w. In this study, we describe the behavior of an ask10D ypr115wD mutant, finding that it displays a cell lysis defect that results from hyperaccumulation of glycerol. We find further that a defect in the function of the Fps1 glycerol channel is responsible for the ask10D ypr115wD phenotype. For this reason, we have given the name RGC1 (for Regulator of the Glycerol Channel) to YPR115w and suggest RGC2 as an alternate name for ASK10. Because the fungal kingdom is replete with members of this family of proteins, but they are not represented in animal cells, Rgc1/2 orthologs represent potentially attractive antifungal drug targets.
Results
An rgc1/2D mutant experiences cell wall stress We constructed a double deletion mutant of RGC1 and RGC2 to test its susceptibility to cell wall stress. The double rgc1/2D mutant, but not the single mutants, displayed a temperature-sensitive growth defect (37uC; Figure 1A) accompanied by cell lysis, as judged by the presence of non-refractile ''ghosts.'' This result is in contrast to that reported by Cohen et al. [20], who found that deletion of ASK10 (RGC2) alone conferred a temperature-sensitive phenotype in the same strain background. The growth defect of the rgc1/2D mutant was suppressed by inclusion of sorbitol in the medium for osmotic support ( Figure 1A), indicating that cell lysis is the cause of the terminal mutant phenotype. To determine if the PH domain of Rgc2 was important for its function, we tested two C-terminal truncation mutants of RGC2 for their ability to complement the
Author Summary
When challenged by changes in extracellular osmolarity, many fungal species regulate their intracellular glycerol concentration to modulate their internal osmotic pressure. Maintenance of osmotic homeostasis prevents either cellular collapse under hyper-osmotic stress or cell rupture under hypo-osmotic stress. In baker's yeast, the Fps1 glycerol channel functions as the main vent for glycerol. Proper regulation of Fps1 is critical to the maintenance of osmotic homeostasis. In this study, we identify a pair of proteins (Rgc1 and Rgc2) that function as positive regulators of Fps1 activity. Their absence results in hyperaccumulation of glycerol and consequent cell lysis due to impaired Fps1 channel activity. Additionally, we found that these glycerol channel regulators function between the Hog1 (High Osmolarity Glycerol response) signaling kinase and Fps1, defining a signaling pathway for control of glycerol efflux. Because members of the Rgc1/2 family are found among pathogenic fungal species, but not in humans, they represent potentially attractive targets for antifungal drug development. mutant. Diploid yeast strains were streaked onto YPD plates with or without 10% sorbitol for osmotic support and incubated at 37uC for 3 days. Strains were wild-type (DL3193), rgc2D (DL3181), rgc1D (DL3203), and rgc1/2D (DL3209). (B) The PH domain of Rgc2 is important for its function. Yeast strain DL3209 was transformed with pUT36, pUT36 MET25-rgc2 (1-420)-His 6 (p2808), or pUT36 MET25-rgc2 (1-720)-His 6 (p2809). Transformants were streaked onto YPD plates and incubated at 37uC for 3 days. The schematic shows the PH domain relative to the truncations tested. doi:10.1371/journal.pgen.1000738.g001 rgc1/2D mutant cell lysis defect. The rgc2 (1-720) allele, which is missing the C-terminal 426 residues, but retains the PH domain, complemented the double mutant when over-expressed ( Figure 1B). By contrast, the rgc2 (1-420) allele, which lacks the PH domain, failed to complement the double mutant. Neither allele complemented the mutant when expressed at low level from the chromosome (data not shown). This reveals that the C-terminal 426 residues are not critical to the function of Rgc2, and suggests that the PH domain contributes to its function.
Mutants that display osmotic-remedial cell lysis are typically compromised for cell wall biogenesis. To test this, we measured the rate of cell lysis of the rgc1/2D mutant by digestion of the cell wall with zymolyase, a wall degrading enzyme. Surprisingly, this mutant did not lyse more rapidly than the wild-type strain, but displayed slower than normal lysis kinetics (Figure 2A), suggesting that it produces a fortified cell wall. The single rgc1D and rgc2D mutants were slightly more resistant to zymolyase than was wildtype. A mutant that produces a fortified cell wall, but is nevertheless susceptible to cell lysis upon imposition of a cell wall stress may be interpreted to be under constitutive cell wall stress. We tested this by measuring the transcriptional output of the cell wall integrity (CWI) pathway. The rgc1/2D mutant was strongly activated for transcription of a PRM5-lacZ reporter ( Figure 2B), which is under the control of the Mpk1 MAP kinase and the Rlm1 transcription factor [23]. This mutant also displayed constitutively active Mpk1, as judged by the phosphorylation state of this MAP kinase ( Figure 2C). These results confirm that the rgc1/2D mutant experiences severe cell wall stress, to which it responds by fortifying the cell wall, and also explains its lysis defect in response to additional cell wall stress at high temperature. In further support of this conclusion, we found that the rgc1/2D mutant is sensitized to growth inhibition by caspofungin ( Figure 2D), an antifungal drug that interferes with cell wall biosynthesis by inhibiting b-glucan synthase activity [24]. Caspofungin treatment prevents the fortification of the cell wall that is essential to the survival of this mutant.
Rgc1 and Rgc2 serve a redundant role in the regulation of glycerol efflux through the Fps1 glycerol channel To understand the cause of the cell wall stress in the rgc1/2D mutant, we conducted a dosage suppressor screen for high-copy number plasmids that conferred growth at 37uC. A single class of strong suppressor was identified as the FPS1 gene ( Figure 3A). FPS1 encodes an aquaglyceroporin that is the major facilitator of glycerol uptake and efflux in yeast [3,5]. This plasma membrane channel protein also mediates uptake of toxic metalloids, such as arsenite and antimonite [10,11]. One interpretation of the suppression result is that the rgc1/2D mutant experiences abnormally high turgor pressure from accumulation of glycerol, which yeast cells use as a compatible solute for osmoregulation. Measurement of intracellular glycerol concentration confirmed that the rgc1/2D mutant has a 5.9-fold higher glycerol level than wild-type cells under normal growth conditions, a value that is approximately half that of an fps1D mutant and approximately equal to that of wild-type cells exposed to hyper-osmotic shock ( Figure 3B). To determine if excess intracellular glycerol is responsible for the phenotypic defects of this mutant, we blocked glycerol biosynthesis at the first committed and rate limiting step, glycerol-3-phosphate dehydrogenase (GPD) [25][26][27]. GPD is encoded by the paralogous genes GPD1 and GPD2. Deletion of either GPD1 or GPD2 alone did not suppress the lysis defect of the rgc1/2D mutant, but blocking glycerol biosynthesis completely by deletion of both GPD1 and GPD2 allowed growth at 37uC ( Figure 3C), confirming that glycerol accumulation is responsible for the cell lysis defect. This also provides an explanation for the fortified cell wall of the rgc1/2D mutant as a response to the stress of abnormally high turgor pressure. Consistent with this interpretation, the gpd1/2D mutations relieved the cell wall stress signaling observed in the rgc1/2D mutant ( Figure 2B and 2C). Figure 1A were grown to mid-log phase in YPD at 30uC, washed and resuspended in water to an initial density of A 600 , 0.7 prior to treatment with Zymolyase 20T (150 mg/ml). Cell lysis was assessed by A 600 measurements at the indicated times. (B,C). The rgc1/2D mutant is under constitutive cell wall stress. (B) Wild-type yeast (DL3193), a rgc1/2D mutant (DL3209), and a rgc1/2D gpd1/2D mutant (DL3251) were transformed with a PRM5-lacZ (p1366) reporter plasmid to measure cell wall stress signaling. Transformants were grown to mid-log phase in selective medium at 23uC, followed by cell lysis and measurement of b-galactosidase activity. Each value represents the mean and standard deviation from three independent transformants. (C) Protein extracts from the strains in (B) were separated by SDS-PAGE and processed for immunoblot detection of activated Mpk1 (phospho-Mpk1) and total Mpk1 as a measure of cell wall stress signaling. (D) The rgc1/2D mutant is sensitized to caspofungin. The strains in (B) were grown to mid-log phase in YPD and 10-fold serial dilutions were spotted onto YPD plates with or without caspofungin (5 ng/ml) prior to incubation at 30uC for 3 days. doi:10.1371/journal.pgen.1000738.g002 Finally, the gpd1/2D mutations relieved the caspofungin sensitivity of the rgc1/2D mutant ( Figure 2D).
We considered two possible explanations for the hyperaccumulation of glycerol in the rgc1/2D mutant -the mutant either produces excess glycerol, or it is impaired for glycerol efflux through Fps1. These hypotheses generate different predictions for the impact of the rgc1/2D mutations on the phenotype of an fps1D mutant. If the rgc1/2D mutant produces excess glycerol, this A rgc1/2D mutant (DL3209) was transformed with centromeric, or high-copy plasmids bearing FPS1 (pRS316-FPS1 or pRS202-FPS1, respectively), or vector (pRS316). Transformants were streaked onto a YPD plate and incubated for 3 days at 39uC. (B) Intracellular glycerol concentrations in wild-type (DL3193), rgc1/2D (DL3209), and fps1D (DL3234) strains. Cultures were grown to mid-log phase in YPD, diluted into YPD with or without sorbitol (to 1.8M) to induce hyper-osmotic shock (15 minutes). Each value represents the mean and standard deviation from three independent experiments. (C) The cell lysis defect of the rgc1/2D mutant is suppressed by blocking glycerol biosynthesis. Diploid yeast strains were streaked onto a YPD plate and incubated at 37uC for 3 days. Strains were: rgc1/2D (DL3209), rgc1/2D gpd1D (DL3237), rgc1/2D gpd2D (DL3254) and rgc1/2D gpd1/2D (DL3251). (D) The cell lysis defect of the rgc1/2D mutant is not additive with that of an fps1D mutant. Diploid yeast strains were streaked onto YPD plates and incubated for 3 days at the indicated temperatures. Strains were: wild-type (DL3193), rgc1/2D (DL3209), fps1D (DL3234), and rgc1/2D fps1D (DL3245). (E) The rgc1/2D mutant is blocked for glycerol efflux. Cells were pre-loaded with 14 C-labelled glycerol (MES buffer with 300 mM glycerol), followed by hypo-osmotic shock (into MES buffer) for the indicated times. Strains were wild-type (DL3193), rgc1/2D (DL3209), and fps1D (DL3234). Each value represents the mean and standard deviation from three independent experiments. doi:10.1371/journal.pgen.1000738.g003 should exacerbate the lysis defect of an fps1D mutant, which is blocked for glycerol efflux. By contrast, if the rgc1/2D mutant is blocked for glycerol efflux through Fps1, loss of the glycerol channel should not result in an additive defect. Figure 3D shows that an fps1D mutant displays a temperature-sensitive growth defect that is slightly more severe than that of the rgc1/2D mutant, with a semi-permissive growth temperature of 34.5uC. The fps1D mutant growth defect at elevated temperature is also the result of cell lysis (data not shown). Significantly, the rgc1/2D fps1D triple mutant behaves identically to the fps1D mutant ( Figure 3D), supporting the hypothesis that the rgc1/2D mutant is impaired for glycerol efflux through Fps1. To test this directly, we measured export of glycerol from cells exposed to a hypo-osmotic shock, a condition that would induce glycerol efflux through Fps1. We found that glycerol was released from wild-type cells, but not from the rgc1/2D mutant or the fps1D mutant ( Figure 3E), supporting the conclusion that Rgc1 and Rgc2 regulate glycerol efflux through Fps1. The varied initial content of 14 C-labeled glycerol among these mutants is a consequence of differential glycerol loading, reflecting the importance of Fps1 for glycerol influx as well as efflux. Finally, strong overexpression of RGC2 failed to suppress the temperature-sensitivity of the fps1D mutant (data not shown), thus establishing an epistatic relationship that places RGC1 and RGC2 above FPS1 in a common pathway for glycerol efflux.
To explore the mechanism by which Rgc1/2 regulate Fps1, we first examined the Fps1 protein level in an rgc1/2D mutant. Despite the observed defect in glycerol efflux of the rgc1/2D mutant, this mutant maintains strongly elevated Fps1 protein levels as compared to wild-type (increased approximately 10-fold; Figure 4A), suggesting that it attempts to compensate for impaired Fps1 function by increasing the number of channel proteins. The increase in Fps1 protein is a consequence of elevated glycerol concentration resulting from the rgc1/2D mutation, because the Fps1 level was reduced in an rgc1/2D gpd1/2D mutant ( Figure 4A), which is blocked for glycerol production. The increased steadystate level of Fps1 in the rgc1/2D mutant is not the result of transcriptional induction, because FPS1 was expressed under the control of a heterologous promoter (MET25). This conclusion was supported by the finding that expression from an FPS1-lacZ reporter was not altered in the rgc1/2D mutant ( Figure 4B). An even greater increase in Fps1 protein level in the rgc1/2D compared to wild-type (approximately 20-fold) was observed when FPS1 was expressed from its native promoter on a multi-copy plasmid ( Figure 4C). Evidently, ectopic overexpression of FPS1 suppresses the rgc1/2D lysis defect by assisting the cell in its efforts to enhance glycerol efflux through an impaired channel. Under these conditions the cells retain more than 20-fold higher levels of Fps1 protein than wild-type cells (the comparison in Figure 4C was to wild-type cells also expressing FPS1 from a multi-copy plasmid). Therefore, we conclude that Fps1 channels in the rgc1/2D mutant retain less than 5% of normal activity.
To determine the cause of the increased steady-state level of Fps1 in the rgc1/2D mutant, we conducted a test of Fps1 stability. Fps1 levels were followed in cells in which FPS1 transcription was shut down with the simultaneous inhibition of protein synthesis. We found that Fps1 was stabilized in the rgc1/2D mutant relative to wild-type cells ( Figure S1). Therefore, we conclude that increased intracellular glycerol in the rgc1/2D mutant, which is caused by a deficiency in Fps1 function, induces an increase in the level of weakly functional Fps1 through protein stabilization.
We conclude further that, because the rgc1/2D mutant does not display diminished Fps1 levels, Rgc1/2 positively regulate Fps1 function by a mechanism other than increased protein level. Fps1 migrates as a doublet as a consequence of phosphorylation [11], (p2492), or empty vector. Extracts were prepared from cultures grown in selective medium, protein was separated by SDS-PAGE, and Fps1-FLAG was detected by immunoblot analysis using a mouse monoclonal a-FLAG antibody. Strains were: wildtype (DL3193), rgc1/2D (DL3209), and rgc1/2D gpd1/2D (DL3251). (B) FPS1-lacZ transcription is not altered in the rgc1/2D mutant. An FPS1-lacZ reporter plasmid (p2213) was transformed into a wild-type strain (DL3193) and a rgc1/2D mutant (DL3209). Transformants were grown to mid-log phase in selective medium at 30uC, followed by cell lysis and measurement of b-galactosidase activity. Each value represents the mean and standard deviation from three independent transformants. (C) A greater increase in Fps1 protein levels is seen when FPS1 is expressed from its native promoter. Yeast strains were transformed with a 2-micron plasmid expressing Fps1-Myc under the control of its own promoter (p2184), or empty vector. Extracts were treated as above, and Fps1-Myc was detected by immunoblot analysis using a mouse monoclonal a-Myc antibody. Strains were: wild-type (DL3193) and rgc1/ 2D (DL3209). doi:10.1371/journal.pgen.1000738.g004 although the responsible protein kinase has not been identified. It is interesting to note that the more slowly migrating band (the phosphorylated form) predominates in the rgc1/2D mutant ( Figure 4A).
Both Rgc1 and Rgc2 have been reported to reside in the cytoplasm [28]. If these proteins function as activators of the Fps1 glycerol channel, they might be expected to interact with Fps1 at the plasma membrane. We examined the intracellular localization of Rgc2-GFP 2 in response to hypo-osmotic shock, conditions in which the Fps1 channel must be opened to allow glycerol efflux. Figure 5A shows that under unstressed conditions, Rgc2-GFP 2 displays diffuse cytoplasmic localization, but very rapidly aggregates into punctate spots that appear near the cell surface in response to hypo-osmotic shock. These spots dissipate over a period of approximately 45 seconds ( Figure 5B). Fps1 has been reported to reside in punctate spots at the plasma membrane [5]. Therefore, we asked if Rgc2-GFP 2 co-localizes with Fps1-tdTomato in response to hypo-osmotic shock. Figure 5C shows Figure 5. Localization of Rgc2. (A) Rgc2-GFP 2 re-localizes from uniform cytoplasmic distribution to punctate spots near the cell periphery in response to hypo-osmotic shock. Wild-type diploid yeast cells (DL3193), transformed with a plasmid expressing Rgc2-GFP 2 (p2481), were grown to mid-log phase in SD medium, centrifuged briefly, and resuspended in distilled water to induce hypo-osmotic shock. Shocked cells were mounted for fluorescence microscopy and photographed within 10 seconds of shock. (B) Dissipation of Rgc2-GFP 2 spots after hypo-osmotic shock. Cells were treated as in (A) and photographed at the indicated times after shock. (C) The punctate spots of Rgc2-GFP 2 do not co-localize with those of Fps1-tdTomato. Wild-type cells (DL3193), co-transformed with p2481 and a plasmid expressing Fps1-tdTomato (p2489), were subjected to hypo-osmotic shock for 10 seconds and examined for co-localization of Rgc2 with Fps1. doi:10.1371/journal.pgen.1000738.g005 that these spots do not co-localize. Other efforts to detect physical interaction between Rgc2 and Fps1 (e.g. co-precipitation and twohybrid analyses; data not shown) failed to provide such evidence. Additionally, the number, location, and intensity of Fps1 punctate spots do not appear to be altered in an rgc1/2D mutant ( Figure S2). This last result is difficult to understand considering that the mutant retains much more Fps1. It is possible that the fluorescent protein is preferentially cleaved from the stabilized Fps1 and digested in the vacuole. Nevertheless, the Fps1 we can detect in the rgc1/2D mutant appears to reside in the same location as in wildtype cells. These results, taken in the aggregate, suggest that regulation of Fps1 by Rgc1/2 is at the level of channel activity, rather than channel expression or localization.
Open channel mutants of Fps1 retain their open channel character in the absence of Rgc1/2 Fps1 is a multi-pass plasma membrane protein with cytoplasmic N-terminal and C-terminal extensions that are inhibitory to channel function [5,29,30]. Truncation of these extensions results in constitutively open forms of the Fps1 channel. To explore the dependence of open channel character of Fps1 mutants on Rgc1/ 2 function, we tested their ability to allow xylitol uptake. A gpd1/ 2D mutant is very sensitive to high external osmolarity, because it cannot produce glycerol to re-establish osmotic balance. However, open channel fps1 mutants suppress this defect when hyperosmotic shock is induced by 1M xylitol, which enters the cell only through unregulated Fps1 to restore osmotic balance [30]. Although a gpd1/2D mutant expressing wild-type FPS1 grew very poorly in the presence of xylitol, two Fps1 open channel mutants, one with an N-terminal truncation (fps1-D1, produces Fps1 D12-231 ) [5], the other with a C-terminal truncation (fps1-C 1 produces Fps1 D534-650 ) [30], conferred growth on xylitol to a gpd1/2D mutant even in the absence of RGC1/2 ( Figure 6). This result indicates that the open channel mutants of Fps1 obviate the requirement for Rgc1/2 for Fps1 function, and support the conclusion that Fps1 is properly folded and localized independently of Rgc1/2 function.
Mutations in RGC1 and RGC2 confer resistance to the toxic metalloid arsenite by blocking Fps1 function The toxic metalloids arsenite and antimonite enter yeast cells through the Fps1 channel [10,11]. An fps1D mutant is therefore resistant to toxicity of these metalloids. As a further test of the role of Rgc1 and Rgc2 in the regulation of Fps1, we examined the sensitivity of mutants in these genes to arsenite. Wild-type cells were sensitive to growth inhibition by 5 mM arsenite, but both the rgc1D and rgc2D mutants were resistant to this treatment ( Figure 7A). Moreover, the rgc1/2D double mutant was resistant to 10 mM arsenite, consistent with the additive nature of Rgc1 and Rgc2 function. These results further support the conclusion that Rgc1/2 function is required to open Fps1. Thorsen et al. [11] demonstrated that the Hog1 MAP kinase is activated in response to arsenite treatment and that Hog1 is required for control of basal Fps1 channel activity. A hog1D mutant was shown to display increased arsenite uptake and hyper-sensitivity to arsenite toxicity, both phenotypes being blocked by an fps1D mutation. Therefore, to place Hog1 within the Rgc1/2 -Fps1 pathway, we tested an rgc1/2D hog1D triple mutant for arsenite sensitivity. Like the rgc1/2D mutant, the rgc1/2D hog1D mutant was resistant to arsenite toxicity ( Figure 7B). Suppression of the hog1D arsenite hyper-sensitivity defect by the rgc1/2D mutations indicated that Fps1 is closed in the triple mutant. These results suggest that Hog1 promotes Fps1 closure by inhibiting the action of Rgc1/2. The order of function of these pathway components was supported by the observation that the cell lysis defect of the rgc1/2D mutant was not suppressed by the hog1D mutation (data not shown).
Rgc2 is phosphorylated in response to various stresses
Because epistasis analysis revealed that Hog1 acts upstream of Rgc1 and Rgc2 to oppose their function, we asked if Rgc2 becomes phosphorylated in response to stresses that lead to the opening or closing of the Fps1 channel. Cells expressing C-terminally Histagged Rgc2 were subjected to hypo-osmotic shock, hyper-osmotic shock (with sorbitol), or arsenite treatment. Rgc2 displayed mobility shifts on SDS-PAGE in response to all three of these stresses ( Figure 8A), presumably reflecting post-translational modifications. The treatments that result in Fps1 closure (arsenite and hyperosmotic shock) induced the greatest shifts, but hypo-osmotic shock, which induces Fps1 opening, also caused a detectable band-shift. In fact, multiple bands were detectable even in Rgc2 from unstressed cells. To determine if these mobility shifts were dependent upon Hog1, we examined Rgc2 mobility in a hog1D mutant. The absence of Hog1 did not prevent the stress-induced Rgc2 band-shifts, but in all cases reduced the extent of shift ( Figure 8A). Rgc2 from unstressed cells also displayed increased mobility in a hog1D mutant ( Figure 8B), suggesting that Rgc2 sustains a basal level of Hog1dependent phosphorylation.
This experiment also revealed the existence of additional modifications in response to these stresses that are Hog1independent. To determine if these additional modifications were phosphorylations, we subjected Rgc2 isolated from stressed cells to protein phosphatase treatment. For all three stresses, phosphatase treatment collapsed the Rgc2 band to the same level as phosphatase treated, unstressed Rgc2 ( Figure 8C). We conclude that although basal phosphorylation of Rgc2 is Hog1-dependent, other protein kinases are responsible for the hyper-phosphorylation observed in response to Fps1-regulating stresses.
It has been demonstrated that in the absence of Hog1, hyperosmotic stress activates the Fus3 and Kss1 MAP kinases through inappropriate cross-talk [31]. Therefore, to determine if the Rgc2 band-shift observed in response to high osmolarity in the absence of Hog1 was due to such cross-talk, we tested a hog1D ste11D alleles. An rgc1/2D mutant that was also blocked for glycerol production (gpd1/2D; DL3246) was co-transformed with multi-copy plasmids bearing wild-type or the indicated open channel alleles of FPS1 and a centromeric plasmid bearing RGC1 (p2627), or a vector control (pRS313). Transformants were grown to mid-log phase in selective medium and 10-fold serial dilutions were spotted onto YPD plates with or without 1M xylitol prior to incubation at 30uC for 3 days or 2 days, respectively. doi:10.1371/journal.pgen.1000738.g006 double mutant, which is blocked for activation of Fus3 and Kss1. The mobility shift observed for Rgc2 in this mutant was indistinguishable from that of the hog1D mutant ( Figure S3), indicating that these MAP kinases are not responsible for the hyper-osmotic stress-induced phosphorylation.
Discussion
Glycerol serves as a compatible solute in S. cerevisiae and other yeasts, allowing cells to respond quickly to changes in external osmolarity. A key component in the control of cytoplasmic glycerol concentration is the Fps1 glycerol channel. Although Fps1 is known to close under conditions of hyper-osmotic stress, and open in response to hypo-osmotic shock [3,5], the mechanism by which Fps1 function is modulated is not understood. In this study, we describe a regulatory pathway for the control of this glycerol channel.
Glycerol channel regulatory proteins
We identified a pair of paralogous genes, RGC1 (Regulator of the Glycerol Channel; YPR115w) and RGC2 (ASK10), that function as positive regulators of Fps1. The studies described reveal that loss of function of both RGC1/2 results in cell wall stress that is caused by excess turgor pressure associated with elevated intracellular glycerol concentration. The increase in glycerol is the consequence of impaired Fps1 function. We found that the increased turgor pressure experienced by the rgc1/2D mutant provokes the cell to activate the CWI signaling pathway and to fortify the cell wall. Nevertheless, imposing additional cell wall stress on this mutant induced cell lysis, a defect that was suppressed by blocking glycerol synthesis. In this regard, it is interesting to note that blocking the function of the glycerol channel activators also sensitized cells to caspofungin, an antifungal agent that acts by inhibiting cell wall biosynthesis [24]. Evidently, preventing the cells from responding to their internally imposed cell wall stress is lethal. Therefore, Rgc1/2 might be suitable antifungal targets for combination therapy with caspofungin.
The mechanism by which Rgc1/2 regulate Fps1 remains unclear. Although there is some evidence that Rgc2 (Ask10) can act as a transcriptional regulator (see below), we did not find that Rgc1/2 control Fps1 transcription. We were not able to detect direct interaction between Rgc2 and the Fps1 channel. However, the findings that Fps1 localizes to the plasma membrane in the presence or absence of Rgc1/2 and that constitutive mutants of Fps1 retain their open channel character independently of Rgc1/2 suggests that these proteins regulate Fps1 through its activity, rather than at an earlier step, such as protein folding, or proper localization. Rgc1/2 control of Fps1 folding or localization would be expected to impact the function of open channel mutants as well as the wild-type.
The role of Hog1 in the regulation of Fps1
Fps1 is unusual in its possession of extensions at both its cytoplasmic N-terminus and C-terminus that play a role in regulating Fps1 channel activity [29,30]. These extensions have been suggested to function as flaps that restrict the flow of glycerol through the channel. However, the mechanism by which they respond to changes in extracellular osmolarity remains largely unknown.
The HOG pathway is activated in response to hyper-osmotic stress [8]. Hog1, the stress-activated MAP kinase at the base of this pathway plays a poorly-defined role in the regulation of Fps1. A hog1D mutant exhibits a glycerol uptake rate that is approximately 3-fold-higher than that of wild-type cells [5,11]. However, this mutant is not impaired for Fps1 closure in response to hyperosmotic stress [5], suggesting that Hog1 regulates the basal activity of Fps1 (i.e. in the absence of osmostress), but not the osmotic stress-induced closure. Basal inhibition of Fps1 by Hog1 may result from phosphorylation at Thr231, which resides within the Nterminal extension, because Hog1 can phosphorylate this site in vitro [11], and mutation of Thr231 to Ala results in constitutive Fps1 activity [11,29].
In addition to glycerol, the toxic metalloid arsenite enters the cell through the Fps1 glycerol channel [10]. Loss of Fps1 function confers resistance to arsenite, whereas loss of Hog1 function results in an increase in the rate of arsenite uptake through Fps1 and consequent hyper-sensitivity to the metalloid [11]. We found that null mutations in RGC1/2 also conferred resistance to arsenite, consistent with the conclusion that Rgc1 and Rgc2 are important for Fps1 channel activity. The rgc1/2D mutations suppressed the arsenite hyper-sensitivity of a hog1D mutation. In fact, loss of RGC1/2 function was completely epistatic to the hog1D mutation with regard to arsenite sensitivity, suggesting that Hog1 exerts its negative effect on Fps1 channel function by inhibiting Rgc1 and Rgc2.
We found that Rgc2 undergoes phosphorylation-induced bandshifts in response to various Fps1-regulatory stresses (i.e. hypo-and hyper-osmotic shock, and arsenite stress). These phosphorylations were partially dependent on Hog1, as intermediate shifts were observed in a hog1D mutant. Rgc2 also appears to undergo basal phosphorylation that is Hog1-dependent. The PhosphoPep database (part of the Saccharomyces Genome Database) [32] identifies 5 phosphorylation sites on Rgc1 and 10 in Rgc2 from unstressed cells. However, only one of these sites in Rgc2 (Thr808), and none in Rgc1 reside at potential Hog1 phosphorylation motifs (S/TP), suggesting that the observed Hog1-basal phosphorylation of Rgc2 is largely, or entirely indirect.
It is also possible that Hog1 inhibits basal Fps1 activity both directly, through phosphorylation of Thr231, and indirectly through phosphorylation of Rgc1/2. In any case, it is clear that other protein kinases contribute to the regulation of Rgc2 (and probably Rgc1), and consequently Fps1, in response to various stresses. These results establish a regulatory pathway from Hog1 to Rgc1/2 to Fps1, in which Rgc1 and Rgc2 are positive regulators of Fps1 channel activity and Hog1 inhibits Fps1 through inhibition of Rgc1/2. Although the interaction between these proteins and Hog1 may be direct, the phosphorylation sites on Rgc1 and Rgc2 remain to be identified.
Other functions of Rgc2 (Ask10)
It is possible that Rgc1/2 are multifunctional proteins. Overexpression of Ask10 was reported to enhance growth of a strain in which histidine production was under the control of (lexA op )-HIS3 reporter driven by a LexA-Skn7 fusion [15]. However, ASK10 overexpression failed to drive a similarly regulated (lexA op )-lacZ reporter. This was in contrast to the behavior of MID2, another gene identified in this screen that activated both reporters [18], raising the possibility that Ask10 does not activate Skn7-mediated transcription.
A second report, by Cohen et al. [20], suggested that Ask10 participates in the oxidative stress-induced destruction of Srb11, a C-type cyclin that is part of the Mediator complex of RNA polymerase II. These investigators identified Ask10 in a twohybrid screen for Srb11-interacting proteins. They further demonstrated that, like Srb11 and its cyclin-dependent kinase (Srb10), Ask10 is a component of the RNA polymerase II holoenzyme. We do not know how the function of Rgc1/2 as regulators of Fps1 might relate to their reported roles in stressactivated transcription.
Rgc1 and Rgc2 are large proteins (120kD and 127kDa, respectively), and our immunoblot analysis of Rgc2 suggests that its regulation in response to different stresses that regulate Fps1 is complex. The unstressed and stressed forms of Rgc2 all migrate as several distinct bands. We have shown that these bands represent a variety of phosphorylated states of Rgc2. Although identities of many of the phosphorylation sites are not known, numerous Rgc1 Wild-type (DL3187) or hog1D (DL3158) cells, transformed either with a plasmid that expresses Rgc2-His 6 (p2501), or vector control (V, pUT36), were treated with stresses that cause Fps1 opening (hypo-osmotic shock; H 2 O), or closure (hyper-osmotic shock, or arsenite). Hypoosmotic shock and hyper-osmotic (1.8M sorbitol) shock were for 1 minute, and arsenite (As) treatment was for 1 hour. Protein extracts were prepared and separated by SDS-PAGE for immunoblot detection of Rgc2-His 6 . (B) The unstressed samples from (A) were run side-by-side to illustrate the Hog1-dependent band-shift of Rgc2-His 6 . (C) Rgc2 band-shifts are caused by phosphorylation. Rgc2-His 6 was immuneprecipitated from extracts of wild-type (DL3187) cells treated as above, and subjected to calf intestinal phosphatase (CIP) treatment in the presence or absence of phosphatase inhibitor (Na 3 VO 4 ). Immuneprecipitates were processed for immunoblot detection of Rgc2-His 6 . doi:10.1371/journal.pgen.1000738.g008 and Rgc2 phosphorylation sites have been identified in response to DNA damage stress. Albuquerque et al. [33] identified 17 phosphorylation sites in Rgc1 and 20 in Rgc2 in response to treatment with the DNA alkylating agent, MMS. Additionally, as noted above, numerous basal phosphorylation sites in Rgc1 and Rgc2 are reported the PhosphoPep database [32]. Only a few of these sites overlap with those found in MMS-treated cells.
Finally, Cohen et al. [20] found that Rgc2 (Ask10) is phosphorylated in response to oxidative stress induced by hydrogen peroxide. These authors reported that the redundant MAPK kinases of the Cell Wall Integrity (CWI) signaling pathway (Mkk1 and Mkk2) were responsible for this modification. Oddly, however, none of the four MAP kinases in yeast were found to be involved [20]. We revisited this result, finding that none of the kinases within the CWI MAPK cascade (including Mkk1/2) were required for the oxidative stress-induced phosphorylation of Rgc2 ( Figure S4).
Rgc1/2 may function to integrate multiple stress signals, only some of which are known to control Fps1 channel activity. The regulation of Rgc1/2 by phosphorylation in response to different stresses appears to be complex. Moreover, these proteins may have additional functions that have yet to be identified.
Strains, growth conditions, and transformations
The S. cerevisiae strains used in this study are listed in Table 1. Yeast cultures were grown in YPD (1% Bacto yeast extract, 2% Bacto Peptone, 2% glucose) or SD (0.67% Yeast nitrogen base, 2% glucose) supplemented with the appropriate nutrients to select for plasmids. Yeast strains bearing multiple deleted genes were constructed by genetic crosses, followed by PCR-based detection of the deleted alleles. Diploid strains were used for most experiments, because the cell lysis phenotypes were more pronounced in diploids than in haploids, and also because diploids have a reduced tendency to acquire suppressor mutations.
Suppressor screen
Three different genomic clones of FPS1 were isolated from a high-copy genomic library in pRS202 (gift of P. Hieter) as suppressors of the temperature-sensitivity of a rgc1/2D mutant. The screen was conducted in the rgc1/2D mutant (DL3209) by plating transformations directly at 37uC. Plasmids were isolated from colonies arising after 3 days. A total of approximately 10,000 transformants were subjected to selection (as judged by lowtemperature plating). This was calculated, based on an average insert size of 6 kb, to be approximately 5 genome-equivalents. Deletion analysis of one of these plasmids (p2165) confirmed that FPS1 was responsible for the suppression activity.
Plasmids
Two reporter plasmids for different transcriptional outputs were used in this study. One reporter, PRM5 (2994 to +1)-lacZ (p1366) responds to the cell wall stress transcription factor, Rlm1 [23]. The other, FPS1 (2933 to 257)-CYC1-lacZ (p2213), was constructed by PCR amplification of the 59 non-coding region of FPS1 using primers with Xho1 (upstream primer) and Sph1 (downstream primer) sites for cloning into the Xho1 and Sph1 sites of pLG178 (p904) [34]. This placed the regulatory sequences for FPS1 upstream of the basal CYC1 promoter linked to lacZ.
The FPS1 gene, fused with a C-terminal Flag epitope, was expressed under the control of the MET25 promoter. The FPS1 coding sequence amplified from genomic DNA (EG123) with an XbaI site immediately 59 to the initiation codon and a HindIII site immediately 39 to the final codon and inserted into pRS426-MET25 P -FLAG (p2186) so as to fuse the C-terminus with the Flag coding sequence, yielding MET25 P -FPS1-FLAG (p2492). The YEpmyc181-FPS1 plasmid (p2184) was the gift of S. Hohmann). The FPS1 gene was tagged at its C-terminus with tdTomato (red fluorescence) [36] and expressed under the control of its own promoter in two steps. First, the tdTomato coding sequence was subcloned from pRSET-B [tdTomato] (gift of R. Tsien) into pRS316 at the BamHI and EcoRI sites, yielding p2487. Next, the FPS1 gene was amplified (omitting the endogenous stop codon) from genomic DNA (EG123) and inserted into p2487 using NotI and SpeI sites designed into the primers. This fused the FPS1 reading frame with tdTomato, yielding pRS316-FPS1-tdTomato (p2489).
The RGC2 gene was tagged at its C-terminus with 6xHis and expressed under the control of the MET25 promoter. The RGC2 coding sequence was amplified by PCR from genomic yeast DNA using primers that included XbaI and XhoI sites and cloned behind the MET25 promoter in pUT36 (p2415) [37] to yield pUT36-MET25 P -RGC2-HIS 6 (p2501). His-tagged C-terminal truncations of Rgc2 were also expressed under the control the MET25 promoter. The first 1260 base pairs (amino acids 1-420) or 2160 base pairs (amino acids 1-720) of RGC2 were amplified from genomic DNA (wild-type strain EG123) by PCR using a forward primer that contained an XbaI site immediately 59 to the start codon and reverse primers that introduced a 6xHis tag followed by a stop codon and an XhoI site. The two regions were inserted into pUT36, resulting in pUT36-MET25 P -rgc2(1-420)-His 6 (p2808) and pUT36-MET25 P -rgc2(1-720)-His 6 (p2809).
The RGC2 coding sequence was tagged at its C-terminus with two tandem copies of GFP and expressed under the control of the MET25 promoter in three steps. In the first step, the RGC2 promoter and coding sequence (omitting the endogenous stop codon) was amplified by PCR and inserted into the Not1 and Sma1 sites of pRS315[GPF] (p1164) [38] to yield pRS315-RGC2-GFP (p2478). In the second step, RGC2-GFP was amplified by PCR from p2478 and inserted in the same way into pRS315[GFP], to yield RGC2-GFP 2 (p2479). In the final step, the RGC2-GFP 2 coding sequence only was amplified by PCR and inserted into pRS414-MET25 P (p976) using Spe1 and EcoRV sites designed into the primers. This yielded pRS414-MET25 P -RGC2-GFP 2 (p2481).
The RGC1 gene with 800 bp of upstream sequence was amplified by PCR from genomic EG123 DNA and using a forward primer that introduced a NotI site and a reverse primer that introduced a SalI site and cloned into centromeric vector pRS313 [35], yielding pRS313-RGC1 (p2627). FPS1 and RGC1/2 constructs were validated by DNA sequence analysis and all were tested for functionality of these proteins by complementation of the cell lysis defects associated with an fps1D mutant or an rgc1/2D mutant, respectively.
Measurements of Zymolyase sensitivity, cell wall stress reporter assays, intracellular glycerol concentrations, and glycerol efflux Zymolyase sensitivity was carried out as described previously [39]. Promoter-lacZ expression experiments for determination of cell wall stress were carried out as described previously [40], with methods for b-galactosidase assays described in Zhao et al. [41]. Intracellular glycerol concentrations were measured in whole cells grown in YPD and centrifuged briefly to remove the culture supernatant. Enzymatic assays for glycerol were carried out using a kit from Boehringer Mannheim and normalized to A 600 of the initial culture. Efflux measurements of 14 C-glycerol were carried out as described by Tamas et al. [5]. Briefly, cells from log-phase cultures (30 ml) grown in YPD were washed in ice-cold MES buffer (10 mM MES, pH 6.0), resuspended in 1 ml ice-cold labeling buffer solution (10 mM MES buffer + 300 mM [ 14 C]glycerol) and incubated for 1 hour at 30uC to load cells with labeled glycerol. Cells were then diluted 10-fold in ice-cold MES buffer to induce hypo-osmotic shock. Aliquots of cells were filtered onto Whatman GFB 25 mm discs at various time points, and washed with MES buffer. Radioactivity of dried filters was measured by a scintillation counter.
For detection of Fps1-Flag, protein samples (4 mg) were separated by SDS-PAGE (7.5% gels) followed by immunoblot analysis using mouse monoclonal a-FLAG antibody (M2; Sigma) at a dilution of 1:10,000. For detection of Fps1-Myc, protein samples (25 mg) were separated by SDS-PAGE (7.5% gels) followed by immunoblot analysis using mouse monoclonal a-Myc antibody (9E10; BabCo) at a dilution of 1:10,000. For detection of Rgc2-His 6 , protein samples (16 mg) were separated by SDS-PAGE (7.5% gels) followed by immunoblot analysis using mouse monoclonal a-tetra-HIS antibody (Qiagen) at a dilution of 1:5000. Secondary antibodies (goat antimouse; Amersham) were used at a dilution of 1:5000. For protein phosphatase treatment of Rgc2-His 6 , Nickel NTA agarose (Qiagen) was used to precipitate Rgc2-His 6 from protein extracts (100 mg) prior to treatment with calf intestinal phosphatase (CIP; Promega) with, or without phosphatase inhibitor (10 mM Na 3 VO 4 ) for 1 hour at 37uC. Precipitates were processed for immunoblot detection of Rgc2-His 6 .
Fluorescence microscopic detection of Rgc2-GFP 2 and Fps1-tdTomato Diploid cells transformed with plasmids that express Rgc2-GFP 2 with out without Fps1-tdTomato were grown in selective medium and visualized by fluorescence microscopy using a Zeiss Axioplan II with a 100x objective and fitted with a GFP and RFP filter. For hypo-osmotic shock experiments, log-phase cultures (1 ml) were centrifuged briefly to pellet cells, which were resuspended in 0.5 ml distilled water for 20 seconds to impose hypo-osmotic shock, followed by the addition of 0.5 ml 20 mM NaN 3 , 20 mM NaF, 20 mM Tris buffer to block further membrane transport [42] and set on ice for 20 seconds. Samples were centrifuged briefly to concentrate cells and mounted for microscopy. The membrane transport inhibitors were omitted from the time-course experiment. Figure S1 Fps1 is stabilized in an rgc1/2D mutant, accounting for the higher protein levels in the mutant compared to WT. A His-tagged Fps1 construct (Open Biosystems ORF collection) was transformed into WT and rgc1/2D diploid cells (DL3193 and DL3209, respectively). Transformants were grown to mid-log phase in synthetic complete medium containing 2% raffinose, and Fps1 expression was induced with 4% galactose for 2 hours. Cells were washed in PBS and resuspended in synthetic complete medium containing 2% raffinose, 2% glucose, and 100 ug/mL cycloheximide. Samples were taken at the noted timepoints. Protein levels were normalized by Bradford assay. Found at: doi:10.1371/journal.pgen.1000738.s001 (1.06 MB TIF) Figure S2 Fps1-tdTomato localizes to punctate spots at the plasma membrane in the presence or absence of Rgc1/2. Fps1-tdTomato under the control of the endogenous Fps1 promoter (p2489) was transformed into WT and rgc1/2D diploid cells (DL3193 and DL3209, respectively) and visualized by fluorescence microscopy using a Zeiss Axioplan II with a 1006 objective fitted with an RFP filter. There is no obvious change in the localization, number, or intensity of the Fps1 punctae in thergc1/2D mutant, as compared to WT. Found at: doi:10.1371/journal.pgen.1000738.s002 (6.41 MB TIF) Figure S3 The Hog1-independent Rgc2 phosphorylation induced by hyper-osmotic stress is not the result of crosstalk from the mating pathway. The genomic copy of STE11 was deleted from a hog1D strain (DL3158) using a PCR-amplified Hph (encoding hygromycin B resistance) cassette with 50 nucleotides of STE11 non-coding sequence at each end. The deletion was confirmed by colony PCR at both ends of the replacement cassette. The resulting hog1D::KanMX ste11D::Hph strain (DL3947) and DL3158 were transformed with a plasmid that expresses Gca2-His 6 (p2501). Transformants were grown to mid-log phase and exposed to hyper-osmotic (1.8M sorbitol) shock for 1 minute. Protein extracts were prepared and separated by SDS-PAGE for immunoblot detection of Gca2-His 6 . Found at: doi:10.1371/journal.pgen.1000738.s003 (1.58 MB TIF) Figure S4 Phosphorylation of Rgc2 in response to oxidative stress occurs independently of the cell wall integrity MAP kinase pathway. The indicated strains in the BY4741 genetic background (Research Genetics) were transformed with a plasmid expressing Ask10-HA (pAK3, gift of R. Strich). Transformants were grown to mid-log phase and treated for 30 min with 0.4 mM H 2 O 2 , as described previously (Cohen et al., 2003). Extracts were prepared and separated by SDS-PAGE for immunoblot detection of Ask10-HA. Found at: doi:10.1371/journal.pgen.1000738.s004 (2.41 MB TIF) | 10,816.4 | 2009-11-01T00:00:00.000 | [
"Biology",
"Chemistry"
] |
Sol-gel synthesis, structure, and dielectric properties of La0.67LixTi1-xAlxO3 solid solutions
La0.67LixTi1-xAlxO3 were synthesized using the sol-gel Pechini route. Ceramic samples were sintered in the temperature range of 1240–1300 °C in the air atmosphere. It was found that in the concentration range of 0.05 ≤ x < 0.15 there is a morphotropic phase boundary region with rhombohedral and tetragonal syngonies. In the concentration range of 0.15 ≤ x ≤ 0.3, a single-phase solid solution with rhombohedral R 3‾ c syngony is formed. As the value of x increases, the average grain size of La0.67LixTi1-xAlxO3 ceramics increases from 5.23 μm (x = 0.05) to 8.76 μm (x = 0.3). All materials of the La0.67LixTi1-xAlxO3 system at 0.05 ≤ x ≤ 0.3 have colossal values of dielectric constant ε′ > 104 at frequencies up to 1 kHz. La0.67LixTi1-xAlxO3 (x = 0.2) solid solution with rhombohedral syngony has the highest value of dielectric constant and the lowest value of the dielectric losses.
Introduction
Dielectric materials with colossal dielectric constant with low loss are a rapidly developing research interest in the field of artificially structured metamaterials and offer additional investigations [1][2][3]. Materials with a high dielectric constant (ε > 1000) are also developed on lithium-containing perovskites and can be used in microelectronics to solve problems of miniaturization of electronic circuits [4]. Materials with a high effective dielectric constant which is provided by the relaxation of mobile lithium ions are of considerable scientific and practical interest. To improve the electrical characteristics, the simultaneous substitution of La and Ti ions by Li and Al ions in the La 2/3 Li x Ti 1-x Al x O 3 system was investigated by the authors of [5,6]. It was found that depending on the sintering conditions La 2/3 Li x Ti 1-x Al x O 3 perovskites can crystallize in orthorhombic or rhombohedral syngony. Material with a high-temperature orthorhombic phase is formed after sintering in the air atmosphere at 1300 • C, followed by quenching. Solid solutions with rhombohedral syngony are formed after sintering in the temperature range 1270-1320 • C with subsequent slow cooling (200 • /h). La 2/3 Li x Ti 1-x Al x O 3 materials with orthorhombic syngony form solid solutions in the concentration range х = 0.15-0.30 and show a high dielectric constant [6], however, there are no studies of the crystal structure and dielectric properties in the literature in the concentration ranges x less than 0.15 and at x more than 0.3. For materials with rhombohedral syngony, the regions of the existence of solid solutions have not been determined, and the nature of the influence of substitute ions on the electrical and physical properties has not been clarified.
The conventional method for preparing powders used in ceramic materials production involves roasting a mixture of metal oxides and carbonates in specific proportions [7]. However, the process of grinding the mixture to obtain a finely dispersed state introduces pollutants from abrasive materials that can impair the dielectric properties of the final product. A fully reacted and homogeneous product necessitates a uniform distribution of each substance in the solid-state reaction, which is a diffusion-controlled process. The mechanically ground mixture requires prolonged calcination at high temperatures under precise atmospheric control, which results in the loss of volatile components such as lithium from the solid solution. Additionally, achieving good density requires a very high sintering temperature. To reduce the sintering temperature, a promising approach is the use of a mild, wet chemical technique [8], which produces finer powder morphologies than those obtained by solid-state methods. A complex polymerization process, such as the modified sol-gel Pechini method [9], is an attractive way to obtain oxide powders with high phase purity. In this synthetic procedure, precursor metal ions in the solution are chelated to form metal complexes, which are then polymerized to form a gel.
Therefore, this work aimed to study the crystal structure and dielectric properties of La 0.67 Li x Ti 1-x Al x O 3 solid solutions, which crystallize in rhombohedral syngony synthesized using the sol-gel Pechini method.
Materials and methods
Stoichiometric amounts of LiNO 3 (Alfa Assar 99%), La(NO 3 ) 3 ⋅6H 2 O (Alfa Assar 99.9%), Ti[OCH(CH 3 ) 2 ] 4 (Aldrich 97%), Al (NO 3 ) 3 ⋅9H 2 O (Aldrich 98%), (CH 2 ) 2 (OH) 2 (Aldrich 99.8%), and C 6 H 8 O 7 (Aldrich 99.5%) were used as initial reagents for the synthesis of solid solutions of La 0.67 Li x Ti 1-x Al x O 3 by the sol-gel Pechini method. The total concentration of metal nitrates in the water solution was 0.2 mol/L, with the total weight of metal nitrates ranging from 66.7 to 81.1 g per liter of solution. To prepare the mixture, the nitrate salts of metals (Li, La, Al) and citric acid (CA) were dissolved in distilled water. Meanwhile, titanium isopropoxide Ti[OCH (CH 3 ) 2 ] 4 was added to ethylene glycol (EG) under constant stirring. Subsequently, the mixture of citric acid and nitrate salts was added to the titanium solution at a molar ratio of citric acid to metal nitrate of 3:1. The molar ratio of citric acid to ethylene glycol was 1:5, and the amount of titanium isopropoxide was determined based on the product stoichiometry. The homogeneous solution was heated at 100 • C for 12 h to form a resin, which was further heated at 80 • C for 12 h to obtain a dried gel. The dried gel was then calcined at 400 • C for 6 h to obtain the ash, followed by calcination in air for 4 h at 1100 • C to obtain the final product.
The single-phase products were characterized by X-ray powder diffraction using a DRON-4-07 diffractometer (Cu Kα radiation; 40 kV, 20 mA). The unit cell parameters of the samples were determined using FullProf software according to the Le Bail procedure [10]. Powders after heat treatment were ground and compressed into tablets under the pressure of 500 kg/cm 2 (50 MPa). The materials were sintered in the temperature range of 1240-1300 • C depending on the Li and Al contents, the production of dense ceramics required different sintering temperatures. The tablets were sintered for 6 h and cooled to room temperature at a cooling rate of 200 • /h. The grain sizes of La 0.67 Li x Ti 1-x Al x O 3 (0.05 ≤ x ≤ 0.3) ceramic samples were determined using a scanning electron microscope SEC miniSEM SNE 4500 MB equipped with EDAX Element PV6500/00 F spectrometer. Using the imageJ [11] calculations by the method of the equivalent circle diameter were performed [12]. Sampling was performed in three different regions based on at least 50 grains in each region. Sintered cylindrical samples with a diameter of 8 mm and a thickness of 2 mm with metal electrodes were used to measure the dielectric properties. Impedance spectroscopy measurements were conducted using a 1260 Impedance/Gain phase Analyzer (Solartron Analytical). The material was formed at temperatures above 1100 • C, which is 100 • lower compared to the solid-state reaction method [6]. The defect structure of lanthanum titanate La 0.67 TiO 3 is characterized by tetragonal syngony [13]. Upon the introduction of lithium and aluminum ions into lanthanum titanate into sublattices A and B of perovskite ABO 3 , respectively, a gradual change in the syngony of the solid solution was observed (Fig. 2a). T. Plutenko et al. the formation of additional phases, additional peaks appear on the XRPD patterns, and a broadening of the peaks was observed. In the range of concentrations 0.15 ≤ x ≤ 0.3, a single-phase solid solution was formed (Fig. 3), which is characterized by a rhombohedral R 3 c syngony. Fig. 3 shows the calculated unit cell volumes. The volume value for the single-phase material La 0.67 TiO 3 was taken from the literature [14,15]. The dependence of the unit cell volume in the concentration region 0.05 ≤ x ≤ 0.3 is linear and obeys Wegard's law indicating the formation of a continuous series of solid solutions. The unit cell volume with increasing x reduces due to the decrease in the average ionic radius in the titanium sublattice, whereas in the range of concentrations 0.3 < x ≤ 0.4, the non-single-phase materials were formed.
Results and discussion
Yokoyama et al. [15] showed that there is an ordered distribution of lanthanum ions and vacancies in the sublattice A of perovskite-type ABO 3 (Fig. 4a) in the tetragonal (P4/mmm) lanthanum titanate La 0.67 TiO 3 . In the La 0.67 Li x Ti 1-x Al x O 3 crystallites with rhombohedral R 3 c syngony, a statistical distribution of lanthanum, lithium, and vacancies in the sublattice A is observed (Fig. 4b). It should be noted that lithium ions with a small ionic radius are located not inside the oxygen cuboctahedron, but are shifted in the direction of the plane formed by the four oxygen (Fig. 4b).
Sintering of ceramic materials that are synthesized by sol-gel synthesis occurs by 30-50 • less than during synthesis by the solidstate method [6]. The morphology of ceramic samples La 0.67 Li x Ti 1-x Al x O 3 where x = 0.05 (Fig. 5a), 0.1 (Figs. 5b), 0.2 (Fig. 5c), 0.3 ( Fig. 5d) was shown. With increasing x, the average grain size increases from 5.23 μm (x = 0.05) to 8.76 μm (x = 0.3). This is due to an increase in the sintering temperature of ceramics with increasing content of Li and Al.
During sintering under the influence of temperature, there is a consolidation and strengthening of ceramics, which is accompanied by a decrease in porosity. At the elimination of pores and defects of a lattice at sintering, there is a migration of intergrain borders. As the temperature increases, the boundary between grains gradually decreases, and larger grains are formed.
Lanthanum lithium titanate is a complex oxide material that is known for its interesting electrical properties. It demonstrates colossal dielectric constant and also the grains of the material have a high conductivity, which is attributed to the presence of vacancies in the crystal lattice. These vacancies provide mobile charge Li + ions that can diffuse through the crystal lattice of lanthanum lithium titanates, resulting in high overall ionic conductivity of the material [5,6,16]. Fig. 6a shows that there are two semicircles and a straight line in the Cole-Cole plots of La 0.67 Li x Ti 1-x Al x O 3 materials. Therefore, there are three main polarization mechanisms overall and two relaxation mechanisms, particularly in the frequency range of 10 − 2 to 10 7 Hz. The straight line is part of a large semicircle (Fig. 6b) and may be assigned to the electrode polarization and described by the Warburg element model with the semi-infinite diffusion layer [17]. The nature of relaxation mechanisms can be revealed by studying the dielectric properties of materials.
The frequency dependences of the dielectric constant and the dielectric loss tangent for the La 0.67 Li x Ti 1-x Al x O 3 are shown in Fig. 7a and (Fig. 7b). The dependences demonstrate 5 characteristic regions of dielectric constant and loss tangent (Fig. 7c). The region I (frequency range from 0.03 Hz to ~ 2 Hz) corresponds to the low-frequency Cole-Cole relaxation semicircle. Such relaxation frequencies are characteristic of migratory polarization [18]. The migratory polarization is provided by the presence of a large number of mobile lithium ions. Lithium ions move over long distances, up to several grain sizes. They overcome a potential barrier at grain boundaries to move between positions in different elementary cells. Migratory polarization turns off completely at the frequency of around 1-2 Hz, which is confirmed by the peak on the loss tangent curve.
The second high-frequency semicircle in Cole-Cole plots is associated with relaxation at frequencies around 10 3 -10 5 Hz, the region III in Fig. 7. It may be caused by the ion relaxation polarization [19]. Ion-relaxation polarization is associated with the movement of Li + ions within the unit cell. In this case, there is no potential barrier to their movement, and the dielectric constant of the material remains constant when an electric field is applied. And it also relaxes in region III from 10 3 Hz to 10 5 Hz (the second peak on the tangent loss curve).
The elastic ion displacement polarization is dominant in the region from 10 5 Hz (region IV, Fig. 7c). It is known that in perovskite La 0.67 Li x Ti 1-x Al x O 3 solid solutions lanthanum ions have a coordination number of 12 and occupy a position in the center of the cuboctahedron (Fig. 4b). The lithium ions in the La 0.67 Li x Ti 1-x Al x O 3 perovskite structure are characterized by a coordination number of 4 and have square-plane coordination. Lithium ions are not located in the center of the cuboctahedron but are shifted in the direction of four oxygen (Fig. 4b). It should be noted that the movement of lithium ions can promote both ionic conductivity and polarization. To increase the polarizability of the material, it is necessary to limit the movement of lithium ions in structural channels by the introduction of ions with a large ionic radius, such as lanthanum ions. The dielectric constant depends on the number of charge carriers involved in relaxation polarization and the distance at which they can be displaced. The high values of the dielectric constant in La 0.67 Li 0.2 Ti 0.8 Al 0.2 O 3 can be explained by the significant amount of lithium ions involved in relaxation, vacancies, and favorable steric conditions. As the lithium concentration increases to x ≥ 0.2, the volume of the unit cell decreases, which leads to a decrease in the lithium ions' mobility and, accordingly, to a reduction in the dielectric constant.
The [20]. The materials of the La 0.5 Li 0.4 Na 0.1 TiO 3 system exhibit dielectric constant values in the range of 40100-12000 (1-10 4 Hz, tan δ min = 0.39) [20]. Therefore, it was shown that La 0.67 Li x Ti 1-x Al x O 3 materials containing aluminum exhibit higher values of dielectric constant at the wide frequency range compared with other La 0.5 Li 0.5-x Na x TiO 3 -based materials.
Conclusions
In this work, novel Li-conducting solid solutions La 0.67 Li x Ti 1-x Al x O 3 with rhombohedral structure were prepared by the sol-gel Pechini technique. It was shown that the use of the sol-gel Pechini synthesis method makes it possible to reduce the calcination temperature of ceramics by 100 • and the sintering temperature by 30-50 • , depending on the concentration x, in comparison with the solid-state reaction technique. The influence of aluminum and lithium on the crystal lattice parameters in a wide concentration range was shown. A single-phase solid solution with rhombohedral syngony exists in a concentration range of 0.15 ≤ x ≤ 0.3. In the concentration range of 0.05 ≤ x < 0.15, the coexistence of rhombohedral and tetragonal syngonies was established. The volume of the unit cell decreases with increasing x, and the average grain size increases. The study of the dielectric constant and the tangent of the dielectric losses showed that the materials La 0.67 Li x Ti 1-x Al x O 3 have high values of the dielectric constant ε ′ > 10 4 in the frequency range of 0.01 ≤ f ≤ 10 3 Hz. The obtained materials can be used in miniaturized electronic systems to solve problems of miniaturization. | 3,623.2 | 2023-04-01T00:00:00.000 | [
"Materials Science"
] |
Crystallisation of Wild-Type and Variant Forms of a Recombinant Plant Enzyme β-d-Glucan Glucohydrolase from Barley (Hordeum vulgare L.) and Preliminary X-ray Analysis
Wild-type and variant crystals of a recombinant enzyme β-d-glucan glucohydrolase from barley (Hordeum vulgare L.) were obtained by macroseeding and cross-seeding with microcrystals obtained from native plant protein. Crystals grew to dimensions of up to 500 × 250 × 375 μm at 277 K in the hanging-drops by vapour-diffusion. Further, the conditions are described that yielded the wild-type crystals with dimensions of 80 × 40 × 60 μm by self-nucleation vapour-diffusion in sitting-drops at 281 K. The wild-type and recombinant crystals prepared by seeding techniques achived full size within 5–14 days, while the wild-type crystals grown by self-nucleation appeared after 30 days and reached their maximum size after another two months. Both the wild-type and recombinant variant crystals, the latter altered in the key catalytic and substrate-binding residues Glu220, Trp434 and Arg158/Glu161 belonged to the P43212 tetragonal space group, i.e., the space group of the native microcrystals was retained in the newly grown recombinant crystals. The crystals diffracted beyond 1.57–1.95 Å and the cell dimensions were between a = b = 99.2–100.8 Å and c = 183.2–183.6 Å. With one molecule in the asymmetric unit, the calculated Matthews coefficients were between 3.4–3.5 Å3·Da−1 and the solvent contents varied between 63.4% and 64.5%. The macroseeding and cross-seeding techniques are advantageous, where a limited amount of variant proteins precludes screening of crystallisation conditions, or where variant proteins could not be crystallized.
We have focused our attention in the past upon the biochemical and structural characterization of β-D-glucan glucohydrolases from higher plants, in particular on barley β-D-glucan glucohydrolase, isoenzyme ExoI (designated as HvExoI). This enzyme was crystallized from a native plant source obtained from barley seedlings [5], although the procedure for isolation of a crystallisable quality of HvExoI is both time consuming and technically challenging [6]. Over the past ten years several structures (Protein Data Bank references 1EX1, 1IEQ, 1IEV, 1IEW, 1IEX, 1J8V, 1LQ2, 1X38, 1X39) have been solved from the native HvExoI crystals with substrate analogues and mechanism-based inhibitors to explain the enzyme's catalytic mechanism and substrate specificity [2,[7][8][9][10]. However, a few facets of catalytic and substrate binding mechanisms remain to be explained. To this end we are interested in the specific roles of amino acid residues in the vicinity of the catalytic pair and how specific structural determinants at the entrance of the catalytic pocket control spatial dispositions of isomeric oligosaccharides entering the catalytic site. Further, we have been intrigued by so-called substrate-product trafficking events at the mouth of the catalytic site [2,7]. Here, the glucose product of the hydrolytic reaction, which is released from the non-reducing termini of substrates, remains bound to the enzyme's active site. However, when a new substrate molecule approaches the enzyme, the glucose product diffuses away from the pocket and the incoming substrate enters the active site [4]. Both events are linked and a precise mechanism, how they proceed, is not known. We presume that the incoming substrate binds in the vicinity of the active site and could, by some delicate mechanism, instigate a product for new substrate interchange. We believe that this substrate/product interchange event represents an ideal model system to study, how products and incoming substrates interact in and/or near enzymes' catalytic sites in general.
Recently, we have reported the high level expression of recombinant HvExoI (designated as rHvExoI) from a codon-optimized HvExoI cDNA in protease-deficient Pichia pastoris under low temperature conditions [11]. We expect that rHvExoI could be used as a suitable enzyme model to study the roles of amino acid residues in catalysis and substrate specificity of this enzyme. To this end, we prepared variants of wild-type rHvExoI, altered (into Ala) in the key catalytic and substrate binding residues Glu220, Trp434 and Arg158/Glu161 by site-directed mutagenesis [12]. From the available structural data [2,[7][8][9][10] we would expect that Glu220, Trp434 and Arg158 are surface exposed, while Glu161 is buried.
In the current work, we describe the techniques and conditions for preparation of the wild-type and variant rHvExoI crystals that showed excellent diffraction parameters. These crystals were prepared by the macroseeding and cross-seeding techniques with microcrystals obtained from a native plant protein. Seeding techniques have previously been used successfully in bio-macromolecular crystallography [13]. The advantage of these techniques is that they use crystals that provide a preformed, regular surface, onto which new molecules may be added in a regular fashion, generally at a lower degree of supersaturation than is required for nucelation [13].
Protein Expression and Purification
Protein expression in P. pastoris at a temperature of 293 K, deglycosylation and purification yielded near-homogenous recombinant rHvExoI ( Figure 1) with a molecular mass of 67,169 Da [11]. It is of note that rHvExoI contained at its NH 2 -terminus an 8x-His-tag and additional three Ala residues flanking the 8x-His-tag (AHHHHHHHHAA). The Ala residues resulted from the ligation-based cloning process, while the 8x-His-tag was added for protein purification purposes [11]. This 11-residue tag was not removed from the rHvExoI protein that was subjected to crystallisation trials. Expressed rHvExoI was catalytically competent with the catalytic efficiency value k cat . K M -1 = 14 mM -1 . s -1 towards 4-nitrophenyl β-D-glucoside. This second-order rate constant was similar to that reported for native fully N-glycosylated HvExoI [14] and a recombinant N-deglycosylated form [11]. Further, the biophysical properties of rHvExoI such as pH optimum and thermostability were also similar to those reported for native or recombinant HvExoI [11,14].
Protein Crystallisation
The concentrated rHvExoI was subjected to four types of crystallisation trials (Figures 2 and 3). We firstly set-up the microbatch under paraffin oil trials at 277 K and 287 K with the goal to screen approximately 130 independent conditions, including those that were previously found to be successful with a native plant enzyme [5]. These conditions (1.7 M ammonium sulfate, 75 mM HEPES-NaOH buffer, pH 7, containing 7.5 mM sodium acetate and 1.2% (w/v) PEG 400) previously produced crystals of native plant HvExoI that belonged to the primitive tetragonal space group P4 3 2 1 2 and yielded high-resolution diffraction patterns [2,5,7]. Nevertheless, despite intensive effort, no diffraction-quality crystals grew, and after approximately 14 days only the formation of a highly intricate interlaced web of thin needles of approximately 40-60 µm in their longest dimensions was observed. Figure 2A and its inset show the appearance of these needles that grew from 1.6 M magnesium sulfate at pH 6.5 and 277 K.
Our second approach to growing the diffraction quality crystals led us to set-up close to 400 trials at the Bio21 Collaborative Crystallisation Centre at 281 K and 293 K by a sitting-drop vapour-diffusion method. After approximately 21 days at 281 K, we could observe formation of short thin needle-shaped crystals that either remained dispersed throughout the droplets ( Figure 2B) or formed well-organised round balls ( Figure 2C). However, after about a month, in some of the droplets with needles ( Figures 2B and 2C) truncated bi-pyramidal crystals formed, which reached dimensions of 80 40 60 µm after about 97 days ( Figure 2B). It was of note that these crystals were only observed at 281 K in droplets with 1.6 to 2.2 M ammonium sulfate, containing 10 mM malate-MES-Tris buffer, pH 5. These conditions were similar to the conditions that we found previously for native HvExoI [5], except that here the pH value of 5 was more acidic then that used previously (pH 7), and that the protein concentration was almost twice as high (12.5 mg . mL -1 versus 6.8 mg . ml -1 ). We expected that these truncated bi-pyramidal crystals could belong to the tetragonal P4 3 2 1 2 space group found for the native protein crystals [5], although at this stage we were not able to collect their diffraction patterns. Notably, in an identical screen at a higher temperature of 293 K the bi-pyramidal crystals were not formed, so it seemed that the temperature was a critical factor for crystal formation of rHvExoI. Thirdly, we also attempted to grow crystals by self-nucleation at 277 K by hanging-drop vapour diffusion and using the conditions developed for native HvExoI [5]. However, we could not observe crystal formation within 180 days and rHvExoI mostly precipitated or the drops remained clear. As no diffraction-quality crystals were obtained with the three crystallisation approaches described above, we turned our attention to seeding at 277 K using a hanging-drop vapour-diffusion method that was used successfully for preparation of large well-diffracting crystals of native HvExoI [7][8][9][10]. We first examined, if we could use microcrystals obtained from native HvExoI to seed the wild-type recombinant rHvExoI protein, despite the differences between the two proteins. These differences included the 11 additional residues of the affinity tag at the NH 2 -terminus, as described above. Further, the rHvExoI protein was N-deglycosylated by endoglycosidase H, such that only one N-linked N-acetyl-β-D-glucosaminyl residue [12] remained attached to each of the three N-glycosylation sites Asn221, Asn498 and Asn600 [2,11]. Approximately 48 h after rHvExoI was macroseeded with the native microcrystals of the sizes between 10 5 7.5 µm and 20 10 15 µm, the original native microcrystals started growing in size. The fully grown crystals of wild-type rHvExoI reached dimensions that varied between 100 50 75 µm ( Figure 3B) and 500 250 375 µm after 5 to 7 days and these crystals had a similar bi-pyramidal morphology as the native microcrystals ( Figures 3A). Having succeeded in growing wild-type crystals, using native microcrystal seeds, we prepared large recombinant crystals of three rHvExoI variants, specifically Glu220Ala ( Figure 3C), Trp434Ala and of the double mutant Arg158Ala/Glu161Ala, also using native seed crystals. The newly grown variant crystals reached sizes of 100 50 75 µm ( Figure 3C) to 500 250 375 µm and showed a similar bi-pyramidal morphology as the native microcrystals. The variant crystals grew slightly slower and reached their maximum dimensions after 10-14 days.
X-ray Diffraction
Single wild-type and variant rHvExoI crystals were cryo-protected and subjected to diffraction at the MX1 beamline of the Australian Synchrotron. All of the X-ray diffraction data sets were virtually complete beyond 1.57-1.95 Å (Figure 4; Table 1). The HKL2000 indexing and systematic absences calculated that the space groups of the wild-type and variant rHvExoI crystals were consistent with a primitive tetragonal space group P4 3 2 1 2 ( Figure 4 and Table 1), and as expected, these space group characteristics were similar to their native counterparts [2,7]. In line with these observations was our previous finding that the native HvExoI microcrystals of the sizes 20 10 15 µm diffracted beyond 2.80 Å on an in-house rotating anode X-ray source and belonged to a primitive tetragonal space group P4 3 2 1 2 [15]. Thus, our data are in agreement with other reports, where the space group characteristics of macroseeds and fully grown crystals were identical [16][17][18], or that as a bonus, the resolution of the newly grown crystals has improved [18]. On the contrary, other authors have reported that during seeding trials mutant crystals often crystallized in different space groups than their macroseeds [19]. The best diffraction data, to 1.57 Å were collected from the wild-type crystals, followed by the Arg158Ala/Glu161Ala, Glu220Ala and Trp434Ala variants that diffracted to 1.65 Å, 1.90 Å and 1.95 Å, respectively ( Figure 4, Table 1). The lattice dimensions of wild-type and variant crystals varied between a = b = 99.2-100.8 Å and c = 183.2-183.6 Å, and there appeared to be one molecule in the asymmetric units, according to the Matthews coefficient calculation [20]. The Matthews coefficients of recombinant crystals were between 3.4-3.5 Å 3 . Da -1 with solvent contents of 63.4% to 64.5%. The R merge values of 5.6% to 10.1% were obtained with <I/σ/(I)> of 37.0 to 71.2, whereas the multiplicity of the individual datasets was well above 20 and varied between 26 to 29 (Table 1). It was of note that the completeness for the highest resolution shells of the wild-type and Glu220Ala datasets was lower, despite the high multiplicity and crystal symmetry, because the data were integrated into the corners of the detector. Also, the mean <I/σ/(I)> values for these datasets indicated that they actually diffracted to higher resolution than that stated in Table 2. It was not surprising that the most favourable diffraction statistics was obtained with the wild-type crystals that were seeded with the wild-type native macroseeds ( Figure 4 and Table 1).
Expression and Purification of Wild-Type and Variant Forms of rHvExoI
Wild-type (GenBank accession No. GU441535) and variant codon-optimized cDNAs, encoding a mature barley β-D-glucan exohydrolase I (HvExoI) inserted in pPICZαBNH 8 expression vectors, were expressed in P. pastoris, strain SMD1168H and purified by ion exchange, immobilized metal affinity chromatography (IMAC), N-deglycosylation by endoglycosidase H and a second round of IMAC, as described previously [11]. The variant forms included Glu220Ala, Trp434Ala and a double mutant Arg158Ala/Glu161Ala, for which the constructions of the cDNA fusions will be described elsewhere [12]. At the final purification step before crystallisation, the N-deglycosylated rHvExoI wild-type and variant enzymes were eluted from a BioGel-P100 size-exclusion column with 50 mM sodium acetate buffer, pH 5.25 containing 200 mM NaCl and 1 mM dithiothreitol at a liner flow rate of 0.5 cm . h -1 . The protein purities of the rHvExoI fractions were analyzed by SDS-PAGE, using 12.5% w/v polyacrylamide and bis-polyacrylamide gels and standard techniques [6]. The protein concentration was estimated with a Bio-Rad protein assay kit (Bio-Rad Laboratories, Gladesville, New South Wales, Australia) using bovine serum albumin (Sigma Chemical Company, St. Louis, MO, USA) as a standard. The protein standards 'Precision Plus Protein Standards' used for SDS-PAGE were from Bio-Rad Laboratories.
Enzyme Assays
The activities of pooled and concentrated (using 10 kDa cut-off centrifugal filter units (Millipore, Bedford, MA, USA) wild-type and variant enzymes were assayed against 4-nitrophenyl β-D-glucopyranoside (Sigma) in 50 mM sodium acetate buffer, pH 5.25.
Crystallisation of Wild-Type and Variant Forms of rHvExoI
Near-homogenous N-deglycosylated wild-type and variant rHvExoI proteins were concentrated to 12.5 mg . mL -1 in 20 mM sodium acetate pH 5.25 and filtered through a 0.22 µm filter (Millipore). Screening of crystallisation conditions was performed by four experimental approaches. Firstly, initial crystallisation conditions were screened using a microbatch under paraffin oil technique. Here, 1 µL of precipitant solutions and 1 µL of the solution containing 12.5 mg . mL -1 of rHvExoI were added into 10 µL of 100% Paraffin oil (Hampton Research, Aliso Viejo, CA, USA) that was previously dispensed in microbatch 72 well Greiner (Terasaki style) plates (Hampton Research). The formulations of Crystal Screen 2, Crystal Screen Lite and Grid Screen Ammonium Sulfate (Hampton Research) were used as precipitants and the crystals grew at 277 K or 287 K in a vibration-free crystallographic cabinet (Molecular Dimensions, Suffolk, UK). Secondly, crystallisation trials were set-up robotically (Phoenix Nano-Dispenser, Art Robbins Instruments, Sunnyvale, CA, USA) in sitting drops, in which 300 nL droplets of rHvExoI were mixed with the same volumes of precipitants and crystal growth proceeded at 281 K and 293 K at the Bio21 Collaborative Crystallisation Centre (CSIRO, Parkville, Australia) [21]. The precipitants from the PSS_1_Com5 and PS gradient-mid range formulation screens were used, whereas both screens were prepared in-house at the Bio21 Centre (http://www.csiro.au/c3/Facility/c3_centre_robotic_crystal.htm), following the recommendation from Emerald BioSystems (Bainbridge Island, WA, USA) for the first screen and those reported by Newman [22] for the second screen. The PSS_1_Com5 screen uses the inorganic precipitants such as sulfates, chlorides, citrates and phosphates, but also 2-methyl-2,4-pentanediol, glycerol and polyethyleneglycols (PEGs) in the pH ranges of 5-8.7. On the other hand, the PS gradient-mid range formulation relies on ammonium sulfate and sodium malonate as precipitants in a 10 mM malate-MES-Tris buffer system in the pH ranges of 4.5-9 [22]. Thirdly, attempts were made to grow crystals under the conditions developed for native HvExoI at 277 K using a hanging-drop vapour diffusion method [5]. Lastly, and most importantly, the rHvExoI crystals were grown in hanging drops at 277 K that were seeded with the native HvExoI microcrystals prepared as described previously [5]. The sizes of the microcrystals for the latter conditions varied between 10 5 7.5 µm and 20 10 15 µm. The hanging drops were prepared at 277 K as follows. The volume of 4 to 6 µL of rHvExoI at 12.5 mg . mL -1 was added to 4 µL of the precipitant solution A (100 mM HEPES-NaOH buffer pH 7, 2.4% (w/v) PEG 400, 1.6 M ammonium sulfate) on 22-mm siliconized circular glass cover slips (Hampton Research). A few microcrystals of native HvExoI were transferred into the hanging drop with a cat whisker. Here, the whisker gently touched the surface of a macroseed stock of native HvExoI and subsequently the whisker was swiftly immersed into a new rHvExoI drop. The cover slips with the seeded hanging drops were placed over 1 mL of reservoir solutions (1.7 M ammonium sulfate in 50 mM HEPES-NaOH buffer, pH 7) contained in the 24 well Linbro plates (Hampton Research), and the wells were sealed with vacuum grease (Dow Corning Corporation, Midland, MI, USA). Crystals from the seeded drops appeared within 5-14 days and were suitable for X-ray data collection. The crystals were photographed through a Leica Laser Microdissection microscope (Leica, North Ryde, Australia) equipped with fluorescence and differential interference contrast.
X-ray Data Collection and Processing
Single enzyme crystals with the longest dimensions of 100 to 500 μm were cryo-protected in 20% (v/v) glycerol concentration in solution A (as specified above in Section 3.3.) [10] and flash cooled in the cold N 2 stream at the beamline MX1 of the Australian Synchrotron. X-ray diffraction data sets were collected at 0.5° oscillations (1 sec exposures) through 360° on the ADSC Quantum 210r Detector [23]. The data were processed with the HKL2000 suite of programs [24].
Conclusions
In summary, excellent X-ray diffraction data were obtained from the recombinant wild-type and variant rHvExoI crystals grown by seeding from a native plant source protein in hanging-drops by vapour-diffusion. The recombinant crystals grew relatively fast and within 5-14 days reached dimensions of up to 500 250 375 µm. The fully grown recombinant crystals retained the space group characteristics of their native macroseeds and diffracted beyond 1.57 Å to 1.95 Å. As reported for other proteins, this technique could be valuable, where a limited amount of variant proteins is available precluding crystallisation trials, or where variant protein forms could not be crystallized. We project that cross-seeding using native protein as a source of microcrystals could be successfully used for generation of large recombinant wild-type and variant crystals that could potentially yield high resolution diffraction patterns. Lastly, the diffraction data collected from the wild-type and variant rHvExoI crystals reported here could be used successfully for structure solution. The structural data are currently being prepared for publication [12]. | 4,411.4 | 2010-07-19T00:00:00.000 | [
"Biology",
"Chemistry",
"Materials Science"
] |
Conspicuous corruption: Evidence at a country level
People can exhibit their status by the consumption of particular goods or experiential purchases; this is known as “conspicuous consumption”; the practice is widespread and explains the market characteristics of a whole class of goods, Veblen goods, demand for which increase in tandem with their price. The value of such positional goods lies in their distribution among the population—the rarer they are, the more desirable they become. At the same time, higher income, often associated with higher status, has been studied in its relation to unethical behavior. Here we present research that shows how a particular Veblen good, illicit behavior, and wealth, combine to produce the display of illegality as a status symbol. We gathered evidence at a large, country-level, scale of a particular form of consumption of an illictly acquired good for status purposes. We show that in Greece, a developed middle-income country, where authorities cannot issue custom vanity license plates, people acquire distinguishing plate numbers that act as vanity plate surrogates. We found that such license plates are more common in cars with bigger engines and in luxury brands, and are therefore associated with higher value vehicles. This cannot be explained under the lawful procedures for allocating license plates and must therefore be the result of illegal activities, such as graft. This suggests a pattern of “conspicuous corruption”, where individuals break the law and use their gains as status symbols, knowing that the symbols hint at rule-breaking, as long as the unlawful practice cannot be incontestably established.
market and vanity plates are illegal goods, not "normal" luxury items.Is it the luxury car or the vanity plate that is the Veblen good, or is it both?Is a vanity plate a Veblen good if it does not also appear on a luxury car?Second, a vanity license plate seems like a rather cheap Veblen good, and without more knowledge about how the Greek population perceives vanity plates it is hard to understand the true value of vanity plates in Greek society.We would really need to know more about the pricing of vanity plates to truly understand them as Veblen goods: what is the going rate for such a plate?
Reply: We show that it is highly unlikely that they are obtained legally; however, after their acquisition, they are not illegal.A car owner cannot be arrested for driving a car with a vanity plate, unless there is evidence that it was obtained illicitly.The first question raised under this point is whether a vanity plate by itself would count as a Veblen good; i.e., would it be considered a luxury item if it was displayed on a non-luxury car?Of course a vanity plate will not turn a middle-of-the-road model to a luxury vehicle.However, it might have a small effect: researchers found that in The Netherlands, a new license plate format, with absolutely no intrinsic value, increased a car's price by about 4% [3].We have modified the beginning of the Discussion section accordingly, to allow for more nuance in our definitions.Regarding the second question raised under the point, the going rate is a few hundred of Euros, as we state in the beginning of the Discussion section.We have also made a few additional points on the value of the illicitly acquired vanity plates in the (new) Conclusions section.
Reviewer Point P 2.4 -The last question I ask under P 2.3 points to a real gap in this article, but one which may be too large to actually address in the article (in which case, perhaps the authors could point to this as a research gap, and/or do more work themselves in future work): this is more understanding of the Greek context and what is considered to be luxury in the context.At a very basic level, it would be useful to know how the licensing process works.Could it be, for instance, that there are legal loopholes that allow, for instance, purchasers of new cars to request any license they want, and that is why we see the association between car type and vanity plates?On a related point: while I like the concept of "conspicuous corruption", doesn't this only work if everyone knows that vanity plates are widely understood to be an ill-gotten good?Is it in fact the case that Greek people generally understand vanity plates to be acquired through corrupt means?Also-the authors refer to a Wikipedia list to ascertain what is a luxury vehicle, but isn't such a list dependent on context?For instance, the author argue that a Smart car would be considered a luxury vehicle in Greece, but this would not necessarily be the case in other places where Smart Cars are more common and even looked down upon.Another issue is understanding the value of vanity plates-does the Greek population generally consider vanity plates to be a luxury good?Third, more qualitative evidence about how the black market in vanity plates in Greece works would be useful to bolster the author's claims that they are, in fact, considered luxury goods.On page 6, the authors talk about "rumors" regarding the price of vanity plates, but surely they could also conduct some interviews or find newspaper articles to support this claim?
Reply: We added some explanation of how the racket works in the beginning of the Discussion section.We have no proof that the Greek people in general understand that vanity plates are acquired through corrupt means (although we strongly suspect so).This points at the possibility that the value associated with a vanity plate is not only based on its scarcity, but is also works as a social marker that the owner "knows the ropes", or even is "above the rules".Smart cars are not considered luxury cars in Greece, but they are a status symbol for the design-conscious.We have clarified that, and it certainly is contextdependent.We have added the observation in the Discussion section.Regarding the last point, we added a short description of how the system works, giving a reference to a newsparer article (in Greek) [4] in the beginning of the Discussion section.We also describe briefly how the racket apparently works in the context of the licensing system.
Reviewer Point P 2.5 -Data: what is the timeframe of the data?Details are provided as to when the data was acquired and the number of observations, but not the range of years and geographical locations covered.
Reply:
The dataset covers all registered cars in Greece up to 2017-03-31; we added the clarification in the dataset description.
Reviewer Point P 2.6 -It would be useful to provide some real-world examples of cars when discussing engine size.What kind of luxury car would be found in the larger vs. smaller engine size categories discussed on page 4? How do we know these larger engine sizes are not trucks, i.e. working vehicles?
Reply: The record for each car contains an attribute corresponding to the vehicle type and vehicle use.We have kept only vehicles that are registered as "private" (working vehicles are usually registered as "public" in Greece) and whose type is "passenger vehicle" or "mixed use".We have added the clarification in the dataset description in the text.
Reviewer 3
First, I would like to thank you for the opportunity to review this paper.In general.I believe the authors have investigated a good research topic, entitled, "Conspicuous Corruption: Evidence at a Country Level."The research area lies in my area of interest.I have published articles related to this topic in leading journals.I have enjoyed reading and evaluating this article as it matches my research interests.
This article describes its objective to explore, analyze and evaluate ideas and perceptions of "Conspicuous Corruption".The study describes that general public with wealth can show their status by consuming a particular product or experience Purchase; this is known as "apparent consumption": this practice is widespread and explained the market characteristics of the entire category of goods, Veblen goods, demand increases with its price.Commodities' value lies in their distribution among populations-the rarer they are, the more desirable they become.At the same time, higher incomes tend to be associated with higher status levels, which has been studied in its relationship to unethical behavior.Here, we introduce research Show how status symbols, immoral behavior, and wealth come together displays illegal as a status symbol.We collect evidence at a large national-level the scale of a particular form of consumption of unlawful benefits for status purposes.
The study has focused on a critical issue of society.However, I have some suggestions for the authors to enhance this work quality.I am recommending your research for publication.It is a good topic; however, you need to work on my suggestions to reach scientific merit.Make changes one by one as suggested.
Reviewer Point P 3.1 -Title: Revise the title and cover it with a theme reflecting the central idea of the study.Your title does not display the real sense of the main study.
Reply: We respectfully disagree with the change in title; we believe that the title should reflect the main finding of our study, which indeed is the phenomenon we term "conspicuous corruption" and for which we do gather evidence at a whole country level.
Reviewer Point P 3.2 -Introduction section: The introduction is not strong.Expand your introduction to about 800 words.Discuss research gaps identified from the literature.In my opinion, here two points could very interesting in this study.(1) How can social media play a leading role in educating people about this bad habit?(2) How corporate social responsibility (CSR) can make people sensible to perform their good social duties and contribute to society.
I strongly suggest you build your study with the idea.Your research will become excellent as you have already explored a great idea.The whole world is facing such issues in society; however, it is becoming common in some developing countries.These rich people can spend this wealth for the social good to become immortal.I am suggesting outstanding studies published in leading journals.Please read these studies, improve your introduction, and cite these articles to enhance your work quality.
Regarding the suggested work, our work aims at exposing a phenomenon that predates social media, so the references to media coverage is not relevant.It also predates COVID-19, so that reference is not relevant.Moreover, it has no relation to urban planning, or indeed to any geography-related issues, as the dataset comprises vehicle registration throughout Greece.
Reviewer Point P 3.3 -Literature section: The literature section needs improvement.I suggest the authors to look into the suggested studies to improve literature section.Build your idea how innovative strategies can bring change in the government organizations to change public.The authors add the latest citations to the literature and method sections to enhance the study's quality.Cite these studies in the literature to enhance the quality of your work.Reply: We struggle to see the relevance of the suggested publications with our work.In particular our work is not related to: • COVID-19 and global mental health, • HIV mortality, nor Regarding the suggestion "how innovative strategies can bring change in the government organizations to change public", the goal of our research is not strategy, but the identification and exploration of a particular form of corruption that impacts both the public and the private sector.
Reviewer Point P 3.4 -Methods and results: I suggest adding demographic table by covering education level, age, income level and regions.See the suggested study and explore if religiosity level can motivate people to contribute to the society.You can add graphical presentation of your findings.See these studies to improve your work and cite them in the methods and results sections.
Reviewer Point P 3.5 -Discussion section: Make a separate heading for discussion section, build it on 1000 words, and improve this section.It is short in your study.It should be around one page and a half.Make it strong.See the recommended studies and improve your sections.
we make it clear that we are talking about one particular kind of goods: "We examine whether vehicle owners engage in rule-breaking in order to acquire a particular form of a positional good: a vanity plate for their vehicle." Reviewer Point P 4.2 -Corruption, illegality, and unethicality have been used interchangeably throughout the manuscript.Every term has its meaning which may defer from others in the light of the manuscript hypothesis.In this regard, the manuscript uses some references related to unethical behavior with wealth as a support to his propositions about law-breaking activities.I suggest that authors should review the use for more coherence.
Reply: Following your suggestion, we have gone through the manuscript carefully: • We now use the term "unethical" only relating to results of work in the literature.
• We use the term "corruption" only as in "conspicuous corruption", except from our discussion of corruption in general in the Discussion section (where we start that part of the discussion by "In terms of corruption in general", so the distinction should be clear).
Reviewer Point P 4.3 -The manuscript should have elaborate more in the materials section about the regulations of the acquirement of plate numbers.For instance, the legality of ownership transfer of plates, which is available in many countries worldwide, may affect the whole hypothesis of the manuscript.
Reply: These are good points.License numbers are not transferable.We have added details on the acquisition process in the Materials section and details on how the process can be subverted in the Discussion section.
Reviewer Point P 4.4 -On page 2, the manuscript states that "we examine whether vehicle owners engage in rule-breaking in order to acquire a particular form of a positional good".I did not this examination.Moreover, the manuscript states on page 6 "Conspicuous corruption works because it cannot be proved that the law has been broken".
Reply: It is correct that "engage in rule-breaking" does not reflect accurately what is happening; after all, as we now explain in the Materials and the Discussion sections, license numbers are often acquired by car dealerships, so it is not the owners themselves who carry out the rule-breaking, but the sellers, as a (paid) service to their customers.However, that does not absolve the owners, as they do have to pay for the vanity plate.So it is more accurate to change the sentence to "We examine whether vehicle owners are involved in rule-breaking in order to acquire a particular form of a positional good: a vanity plate for their vehicle."Concerning the proof that the law has been broken, we have rephrased it to "Conspicuous corruption works because it cannot be proved that the law has been broken in a particular instance after the fact; a license plate is by itself legal, even though it may have been illegaly acquired." Reviewer Point P 4.5 -On page 5, the study cites Wikipedia for a piece of information.I do not think this is an authoritative reference.
Reply: Our use of Wikipedia does not involve taking an article as an authoritative reference for a particular subject, but using its category of "Luxury vehicles" to sieve the luxury cars; see https: //en.wikipedia.org/wiki/Wikipedia:Categorization.In order to make sure that the category is not off the mark, we cross-checked with the Euro Car Segments, which are in use in Europe for categorizing vehicles.In particular, we examined the "F: luxury cars" segment, by considering the sales in these segments for 2020, as reported by the Hellenic Association of Motor Vehicle Importers-Representatives. We found that all the F-segment cars sold in Greece in 2020 belonged indeed into the Wikipedia "Luxury vehicles" category, apart from Tesla and Ford Explorer cars.As Ford Explorer is not a brand (it is a brand and a model); therefore we only added Tesla in the examined luxury vehicles.This did not alter the statistical results.
Reviewer Point P 4.6 -On pages 5-6, the authors state that "After some investigation, it appears that the market for vanity plates in Greece is an open secret, the cost for obtaining a desirable number running to a few hundred Euros."These facts should be proved by statistics or citations.
Reply: An internal audit conducted by the competent ministry has uncovered several irregularities that demonstrate the modus oprandi for handing out vanity plates.We have asked for the audit report through a freedom of information request, which was however rejected, due to the report's confidentiality.However, the report has leaked, and we were thus able to add a reference to it from a newspaper article (in Greek, our translation of the most relevant part) in the Discussion section. | 3,794 | 2021-09-01T00:00:00.000 | [
"Political Science",
"Economics"
] |
AIM AND SCOPE
All manuscripts should be structured in four subsections: Purpose, Methods, Results, and Conclusions. Length of abstract should be less than or equal to 300 words. A list of keywords, with a maximum of 6 items, is necessary at the end of the abstract. They should be from main heading terms of MeSH (https://www.nlm.nih.gov/mesh/MBrowser.html) and written in small alphabetic letters with the first letter capitalized. Each word should be arranged in alphabetical order, separated by a semicolon, and marked with a period at the end. Introduction It should address the purpose of the article concisely and include background reports that are relevant to the purpose of the paper. Materials and Methods This section should include sufficient details of the design, subjects, and methods of the article in order along with the data analysis methods and control of bias in the study. Methodology section of an experimental study needs to include sufficient details that it can be further replicated by others. When reporting experiments with human subjects, the authors should declare whether they received approval from the Institutional Review Board for the study. When reporting experiments with animal subjects, the authors should indicate whether the handling of the animals was supervised by the Institutional Board for the Care and Use of Laboratory Animals. Include demographic data in the materials and methods section if applicable. Materials and devices should be accompanied by model name, company name, city, and country of manufacturer. Subsection titles can be used. Precisely describe the methods of statistical analysis and programs so that readers can reproduce the same results if the original data are available. Results Results should be written in a logical sequence, presenting major findings first. Do not repeat all the data shown in the tables or illustrations in the text but emphasize or summarize only the most important observations. Results can be sectioned by subsection titles. Citation of tables and figures should be provided as Table 1 and Figure 1. Discussion There should be an emphasis on new and important aspects of the study. Do not repeat the results in detail or other information that is given in the introduction or the results section. Discuss according to the purpose of the study but avoid unqualified statements that are not adequately supported by the data. Limitation and further requirements may be described. Conclusion must be stated briefly in the last paragraph of the discussion section. Conflict of interest The corresponding author of an article is asked to inform the Editor of the authors' potential conflicts of interest possibly influencing their interpretation of data. A potential conflict of interest should be disclosed in the manuscript even when the authors are confident that their judgments have not been influenced in preparing the manuscript. Such conflicts may be financial support or private connections to pharmaceutical companies, political pressure from interest groups, or academic problems (e.g., employment/affiliation, grants or funding, consultancies, stockownership or options, royalties, or patents filed, received, or pending). Acknowledgements Persons or institutes that contributed to the papers but not enough to be coauthors may be introduced. Financial support including foundations, institutions, pharmaceutical and device manufacturers, private companies, and intramural departmental sources should be described along with other types of support, if any. References References should be clearly related to documents and should not exceed 40. They should be numbered consecutively in the order in which they are first mentioned in the text. Each reference should be cited as [1], [1, 4], or [1-3], at the end of the related phrases in the text. The abbreviated journal title should be used according to the List of Journals Indexed for NLM catalog (https://www.ncbi.nlm.nih.gov/nlmcatalog?db=journals) and the List of KoreaMed Journals (http:// www.koreamed.org/JournalBrowser.php). If there are six or less authors in a reference, then all the names of the authors should be listed. If the number of authors is more than six, list the initial six authors and then abbreviate the rest of the authors with 'et al'. Provide the start and final page numbers of the cited reference. Abstracts of conferences are not allowed to be included in the references. Unless otherwise described here, it follows the NLM Style Guide for Authors, Editors, and Publishers (http://www.nlm.nih.gov/citingmedicine).
PUBLICATION TYPES AND LANGUAGE
JPIS encompasses a wide range of publication types including clinical and experimental research articles, sophisticated reviews, letters to the editor, and editorials, covering a variety of interests in the field of periodontal or implant science. Manuscripts written in British or American English with consistency from any researcher across the world will be welcomed if they are within the aim & scope of this journal.
RESEARCH AND PUBLICATION ETHICS
All of the manuscripts should be prepared in strict observation of research and publication ethics guidelines recommended by the Council of Science Editors (http://www.councilscienceeditors.org), International Committee of Medical Journal Editors (ICMJE, http://www.icmje.org), World Association of Medical Editors (WAME, http://www.wame.org), and the Korean Association Medical Journal Editors (http:// www.kamje.or.kr/intro.php?body=eng_index).
Conflict-of-interest statement
A conflict of interest may exist when an author has financial or personal relationships or affiliations that could bias the author's decisions of the manuscript. Authors are expected to provide detailed information about all relevant financial conflicts, particularly those present during the process of research and publication, as well as other financial interests (such as patent applications in preparation) that represent potential financial gain in the future. All disclosures of any potential conflicts of interest including specific financial interests, relationships, and affiliations (other than those affiliations listed in the title page of the manuscript) relevant to the subject of the manuscript will be reported by the corresponding author on behalf of each co-author, if any, as part of the submission process. Likewise, authors without conflicts of interest will be requested to state so as part of the submission process. If authors are uncertain about what constitutes relevant financial interests or relationships, they should contact the editorial office.
Statement of informed consent
Copies of written informed consents and Institutional Review Board (IRB) approval for clinical research should be kept. If necessary, the editor or reviewers may request copies of these documents to resolve questions about IRB approval and study conduct.
Statement of human and animal rights
Clinical research should be performed in accordance with the Ethical Principles for Medical Research Involving Human Subjects, outlined in the Declaration of Helsinki (http://www. wma.net/en/30publications/10policies/b3/index.html). Clinical studies that do not comply with it will not be considered for publication. For human subjects, personal information such as patients' names, individual registration numbers, date of birth, or other private matters should not be disclosed. For animal subjects, research should be conducted in accordance with the National or Institutional Guideline for the Care and Use of Laboratory Animals and these facts must be declared in the manuscript. Copies of the protocol approved by IRB or Animal Ethical Committee (AEC) should be available for review if necessary.
Originality and duplicate publication
All submitted manuscripts should be original and not be considered by other scientific journals for publication at the same time. Any part of the accepted manuscript should not be duplicated in any other scientific journals without the permission of the Editorial Board. If duplicate publication related to the papers of this journal is detected, the authors will be announced in the journal and be obligated to pay the penalty, while their institutes will be informed about the misconduct. For the policies on research and publication ethics that are not stated in these instructions, the guidelines by the Committee on Publication Ethics (http://publicationethics.org) could be applied.
AUTHOR CONTRIBUTIONS
Each author should have participated sufficiently in the work to take public responsibility for appropriate portions of the content. One or more authors should take responsibility for the integrity of the work as a whole, from inception to pub-
Instructions to Authors
lished article. According to the guidelines of the International Committee of Medical Journal Editors (ICMJE), authorship credit should be based on the following 4 criteria: 1. substantial contributions to conception or design of the work, or the acquisition, analysis, or interpretation of data for the work; and 2. drafting of the work or revising it critically for important intellectual content; and 3. final approval of the version to be published; and 4. agreement to be accountable for all aspects of the work in ensuring that questions related to the accuracy or integrity of any part of the work are appropriately investigated and resolved.
Each author should be accountable for the parts of the work he or she has done. In addition, each author should be able to identify which coauthors are responsible for specific other parts of the work and should have confidence in the integrity of the contributions of any coauthors. All those designated as authors should meet all 4 criteria for authorship, and all who meet the 4 criteria should be identified as authors.
The contributions of all authors should be described in cover page of the manuscript using the CRediT Taxonomy of author roles. They should be precisely reflected as following 14 categories: Conceptualization, Data curation, Formal analysis, Funding acquisition, Investigation, Methodology, Project administration, Resources, Software, Supervision, Validation, Visualization, Writing -original draft, Writing -review & editing. An individual author may be assigned multiple roles, and a given role may be assigned to multiple authors. All authors must meet at least one of the seven core contributions (Conceptualization, Data curation, Formal analysis, Investigation, Methodology, Software, Validation), as well as at least one of the writing contributions (Writing -original draft preparation, Writing -review & editing). Authors could also satisfy the other remaining contributions; however, these remaining contributions alone would not qualify them for authorship. It is recommended that corresponding authors bear the responsibility for role assignment of all authors who should be given the opportunity to review and confirm their assigned roles.
PEER REVIEW PROCESS
All manuscripts will be reviewed by two or more experts in the corresponding field. The Editorial Board may request authors to revise the manuscripts reflecting the reviewers' opinion. After revising the manuscript, the author should upload the revised files with a reply to each item of the reviewers' opinion. The author's revision should be completed within 14 days after the request. If it is not finished by the due date, it shall be regarded as being withdrawn. To extend the revision period, the authors should contact the Editor. The review process will be finished through the second review system. The Editorial Board will make a final decision on the approval for publication of the submitted manuscripts and can request any further revisions if necessary. Statistical editing may be necessary if the data need professional statistical aid.
COPYRIGHTS AND CREATIVE COMMONS ATTRIBUTION
Copyrights of all published materials are owned by the Korean Academy of Periodontology. They are also followed by the Creative Commons Attribution Non-Commercial License (https://creativecommons.org/licenses/by-nc/4.0). Authors of accepted papers must complete the Copyright Assignment & Warranties Form, which is available on the official website of JPIS (https://jpis.org).
MANUSCRIPT PREPARATION
Manuscripts should be submitted in Microsoft Word files. They should be typed and double-spaced, using font size of 10 with margins of 25 mm on each side and 30 mm for the upper and lower ends on A4-size paper. Organize the articles in the following order: cover page, abstract, body text, acknowledgements, references, tables, and figure legends.
RESEARCH ARTICLES
The structure of research article consists of Cover page, Abstract, Body text (Introduction, Materials and Methods, Results, Discussion), Conflict of interest, Acknowledgements (if necessary), References, Tables, and Figure legends. Each section should be written according to the following rules.
Introduction
It should address the purpose of the article concisely and in-clude background reports that are relevant to the purpose of the paper.
Materials and Methods
This section should include sufficient details of the design, subjects, and methods of the article in order along with the data analysis methods and control of bias in the study. Methodology section of an experimental study needs to include sufficient details that it can be further replicated by others.
When reporting experiments with human subjects, the authors should declare whether they received approval from the Institutional Review Board for the study. When reporting experiments with animal subjects, the authors should indicate whether the handling of the animals was supervised by the Institutional Board for the Care and Use of Laboratory Animals. Include demographic data in the materials and methods section if applicable. Materials and devices should be accompanied by model name, company name, city, and country of manufacturer. Subsection titles can be used. Precisely describe the methods of statistical analysis and programs so that readers can reproduce the same results if the original data are available.
Results
Results should be written in a logical sequence, presenting major findings first. Do not repeat all the data shown in the tables or illustrations in the text but emphasize or summarize only the most important observations. Results can be sectioned by subsection titles. Citation of tables and figures should be provided as Table 1 and Figure 1.
Discussion
There should be an emphasis on new and important aspects of the study. Do not repeat the results in detail or other information that is given in the introduction or the results section. Discuss according to the purpose of the study but avoid unqualified statements that are not adequately supported by the data. Limitation and further requirements may be described. Conclusion must be stated briefly in the last paragraph of the discussion section.
Conflict of interest
The corresponding author of an article is asked to inform the Editor of the authors' potential conflicts of interest possibly influencing their interpretation of data. A potential conflict of interest should be disclosed in the manuscript even when the authors are confident that their judgments have not been influenced in preparing the manuscript. Such conflicts may be financial support or private connections to pharmaceutical companies, political pressure from interest groups, or academic problems (e.g., employment/affiliation, grants or funding, consultancies, stockownership or options, royalties, or patents filed, received, or pending).
Figure legends
All of the figures should be explained separately. Full names of all abbreviated terms should be presented in each figure.
Capitalize the first letter of the first word and place a period at the end of the phrase.
Figures
Figures should be submitted in Tiff or EPS file format. Number figures as Figure 1, Figure 2 … in order of citation. An individual should not be recognizable in the photographs unless a written consent of the subject has been obtained and is provided at the time of submission. Scales should be presented as a bar in the picture instead of a magnification remark in the legend.
The minimum requirements for digital resolution are: • 300 DPI/PPI for picture-only photographs.
• 600 DPI/PPI for photographs containing pictures and line elements, i.e., text labels, thin lines, arrows. • 900 DPI/PPI for black and white images, such as line drawings or graphs.
REVIEWS
Review articles will be solicited. Previously published material should be incorporated into an integrated presentation of the current understanding of a topic. Topics of scientific consensus and of controversy may be dealt with in the reviews. It should have following structures: Cover page, Abstract, Body text (Introduction, Text, Conclusion), Conflict of interest, Acknowledgements (if necessary), References, Tables, and Figure legends. An abstract should summarize the important points of the review article in 300 words without being restricted to any specific format. Length of the Body text should not exceed 5,000 words. References should not exceed 100.
LETTERS TO THE EDITOR
Letters to the Editor should include brief constructive comments that concern previously published papers. They should be divided into Cover page and Text without exceeding 500 words. They should have a maximum of five references. Letters could be edited by the Editorial Board. Responses by the author of the subject paper may be provided in the same issue or next issue of the journal.
GENERAL TEXT STYLE
Generic and brand name of medicine For medicine, use generic names. If a brand name should be used, insert it in parentheses after the generic name.
Statistical expression
Standard deviation and standard error should be described in the format of mean ± SD and mean ± SE, respectively. P-values should be described as P<0.05 or P=0.003.
Units
Scientific units should be followed by the International System of Units (http://www.bipm.org/en/measurement-units).
Unit for volume is 'L', instead of 'l' to avoid the confusion; Unit for blood pressure is mmHg; Temperature is expressed in Celsius and concentration in M, mM, and µM.
Abbreviations
Abbreviations should be avoided as much as possible. When they are used, full expression of the abbreviations in parentheses following the abbreviated word should be given at the first use. Abbreviation can be used if it is listed as MeSH main heading terms and it is approved by the International System of Units.
ERRATA
Errata are published to correct errors of previously issued articles. When errors are made in the printing process, errata will be published without additional cost. The authors, however, will be required to bear the expense when the errors originate from the final proof of corresponding author. To request a correction to a published article, corresponding author should contact the editorial office of JPIS, providing details of the error, including the complete article citation, location of the error and corrected text. JPIS will publish corrections in the next available issue and link the correction to the original article.
SUBMISSION OF MANUSCRIPT
Authors are requested to submit their papers electronically by e-submission system, which can be accessed on the official website of JPIS (https://jpis.org) as well. After creating an account, authors can proceed with the submission process as arranged. Before submission, the instructions described in the JPIS manuscript template files should be carefully reviewed in formatting the papers. Cover letter, electronic copy of manuscript, and figures should be included in the submission file package.
Manuscript Number:
Title: Upon the publication of the article, author jointly and severally grants all rights, title, and interest therein, including any and all copyrights in all forms and media now or hereafter known, to the Journal of Periodontal & Implant Science which is published by the Korean Academy of Periodontology.
Author warrants this article to be original work not published elsewhere and approves it for publication. Author further certifies that substantial contribution was made to accept public accountability for it, that any right or interest in the article has not been assigned to any third party, and that all figures and illustrations included have not been digitally altered and do not misrepresent the actual circumstances reported in any way.
Author declares to have no commercial association (e.g., equity ownership or interest, consultancy, patent and licensing agreement, or institutional and corporate associations) that might be a conflict of interest in relation to the submitted manuscript, except as disclosed in the Conflict of Interest of the article. All sources of funding in support of the work presented in the article are indicated in the Acknowledgements of the manuscript.
Each author must sign this statement to indicate the acceptance of the terms of publication.
Type complete name (first, middle initial, last name) Signature Date
Please print this form, fill it out, and email it back to<EMAIL_ADDRESS>as quickly as possible. | 4,470.2 | 2002-01-01T00:00:00.000 | [
"Medicine",
"Chemistry",
"Biology",
"Philosophy"
] |
Subcellular localization of L-selectin ligand in the endometrium implies a novel function for pinopodes in endometrial receptivity
Background Apical surfaces of human endometrial epithelium and endothelium are key elements for the initiation of molecular interactions to capture the blastocyst or leukocyte, respectively. The L-selectin adhesion system has been strongly proposed to play an important role in the initial steps of trophoblast adhesion and promotion of integrin-dependent processes, ultimately culminating in the establishment of the embryo-maternal interface. On the basis of these facts, we hypothesized a novel role for pinopodes as the first embryo-fetal contact sites to contain the highest subcellular expression of L-selectin ligand suggesting its role in early adhesion as predicted. Thus, the objective of this study was therefore to determine the subcellular pattern of distribution of the L-selectin ligand (MECA-79) in human endometrial apical membrane region during the window of implantation. Methods Endometrial biopsies of secretory phases from fertile females ranging in age between 25 and 42years were studied using several approaches, including scanning electron microscopy (SEM), immunostaining for light microscopy and transmission electron microscopy (TEM), and immunoblotting as well as statistical analysis of the area-related numerical densities of immunoreactive MECA-79-bound nanogolds to detect the expression pattern and the subcellular distribution pattern of L-selectin ligand (MECA-79) in human endometrium during the window of implantation. Results The endometrial biopsies were scored according the dating criteria of Noyes et al. by an experienced histologist. The SEM images of the midluteal phase specimens revealed that fully developed pinopodes were abundant in our samples. HRP-immunostaining and immunofluorescent staining as well as immunoblotting revealed that MECA-79 was expressed in the midluteal phase specimens. The results of immunogold TEM illustrated the expression of MECA-79 in human pinopodes in the midluteal phase and a higher area-relate numerical density in pinopodes compared to that of the uterodome-free areas. Conclusions This is the first demonstration of the subcellular localization of MECA-79 in the human pinopodes which may indicate a novel role for pinopodes to be capable of shear-stress-dependent tethering-type adhesion in the initial phases of human embryo implantation.
Background
In humans, there is a distinct 'window of implantation' during the midluteal phase when the endometrium demonstrates maximal receptivity for embryo implantation [1]. There is convincing data that the uterine luminal epithelium is central in controlling receptivity, and probably acting initially as a barrier to challenge attaching embryo [2]. Several candidate adhesion molecules are expressed in the luminal epithelium of receptive endometrium where they are thought to facilitate embryo apposition/adhesion/ communication to the endometrium [3][4][5]. However, because of difficulties in analyzing these processes in human models, differences among primate species [6,7], the lack of suitable experimental models, and significant variations between rodent and human models of embryo implantation [1], the exact molecular basis of these initial interactions remain to be discovered.
Considering the fact that the human embryo must attach itself to the uterus under conditions of shear stress similar to that of leukocyte transmigration, numerous investigators have proposed that the molecular basis between implantation and leukocyte transmigration should bear some similarities. Several investigators have demonstrated that L-selectin and its oligosaccharide ligands, which constitute L-selectin adhesion system, could be considered as one of the most important candidate pathways to mediate the initial embryo-maternal interactions [8,9]. In support, it was recently demonstrated that human blastocysts express L-selectin on their external surfaces [10] raising the possibility that these molecules may participate in the early stages of human blastocyst attachment. Furthermore, the lack of detection of Lselectin at stages earlier than the embryonic blastocyst stage and L-selectin's intense immunostaining on the trophectoderm during hatching, indicates that this cell surface protein is developmentally regulated [11]. This was correlated with complementary increased expression of its ligand within the luminal epithelium during the mid-secretory phase [10,12]. Immunolocalization studies on normal endometrium have demonstrated that the Lselectin carbohydrate ligand MECA-79, antibody that recognizes L-selectin high-affinity ligands, is upregulated from the day of ovulation to day 6-post ovulation, and by comparison is reduced throughout the follicular phase or in ovulatory cycles [10,12,13]. More interestingly, a significant difference between the expression of L-selectin ligands between fertile and infertile women was reported and the MECA-79 epitopes were shown to be expressed at a higher level in fertile compared to that of infertile patients [14,15]. Other than embryo implantation [10,16], this adhesion system correlates with many physiological and pathological processes including leukocyte infiltration [17,18], lymphocyte homing [19], and tumor metastasis [20,21] indicating the existence of similar pathways between these processes. Since the apical surface of the endometrium contains key elements for the initiation of molecular interactions between human blastocysts and the endometrium, and that the L-selectin ligand adhesion system is believed to play a major role in mediating initial embryonic apposition and adhesion, this prompted us to investigate the subcellular localization of L-selectin ligand at the pinopodes, the most apical surfaces of the receptive endometrium [22], and the first embryo-maternal contact sites. In the present study, we proposed that pinopodes may have a novel function in the unusual cell-cell interactions that take place in the early steps of human embryoendometrial apposition/adhesion similar to that of tethering of blood cells.
Endometrial biopsy specimens
Endometrial biopsies were obtained during secretory phases were collected by curettage from the anterior wall of the uterine cavity of women (ages 25-42) undergoing minor gynecological investigations unrelated to endometrial pathology. All women were fertile with regular menstrual periods (25-35 days) and none of them had used steroidal contraceptives or intrauterine devices for at least 3 months prior to the sampling. All patients gave their informed consent for the collection and investigational use of endometrial tissues. This study was approved by the local Ethical Committee and Southern health Human Research Ethics Committee, (#09317B), Monash Medical Centre, Clayton, Victoria (cell culture experiments) and Shaheed Beheshti Medical Sciences University Ethical Committee, (#88-01-115-6367-3144), Tehran-Iran (all other experiments). Eight patients were tested for our experiments, 3 patients for immunoblotting and 5 patients for all other experiments. Except immunoblotting biopsies, another biopsies from each patient were divided to several small portions to be used for light microscopy, immunohistochemistry, scanning electron microscopy (SEM) and immunogold staining of transmission electron microscopy (TEM) experiments. For endometrial dating, samples were fixed in 10 % neutrally buffered formaldehyde and the paraffin-embedded biopsies were stained with hematoxylin and eosin and evaluated by an experienced observer according to the histopathological criteria of Noyes [23]. Samples used for cell culture and western blot analysis were collected in a 1:1 mixture of DMEM and Ham's F12 medium (DMEM/F12; Trace Biosciences, Sydney, Australia) supplemented with 1 % penicillin, streptomycin, and fungizone (Common Wealth Serum Laboratories, Melbourne, Australia) and Lglutamine (Sigma Diagnostics, St. Louis, MO).
Culture of primary human endometrial epithelial cells and human endometrial epithelial (HES) cell line
Fresh samples were transferred in a 1:1 mixture of DMEM/F12 supplemented with 1 % penicillin, streptomycin, and fungizone and L-glutamine to culture room and washed three times. Human endometrial tissues were digested with collagenase type 3, 0.2 mg/ml for 20 min 2 times and the suspension was filtered through 43 and 11 μm nylon mesh to collect endometrial epithelial fragments, as previously described work [24]. Briefly, the epithelial fragments were collected and re-suspended in a 1:1 mixture of DMEM/Hams F-12 (F12; Thermo Electron Corp., Melbourne, Australia) supplemented with 10 % fetal calf serum (FCS; Invitrogen, Carlsbad, CA), 2 mM L-glutamine (Thermo Electron), and 1 % antibiotic antimycotic solution (Life Technologies, Inc., Auckland, New Zealand) and plated. Endometrial epithelial cells were collected from the filter paper and cells were further purified by selective adherence. Epithelial cells were allowed to grow out from glandular structures for 48 h, then detached with trypsin, and serially replated (three times) in plastic culture dishes for 30 min each time, to allow adherence of contaminating stromal cells. Non-adherent cells were transferred to 24well plates and were allowed to grow out for 48 h. Cells were grown in DMEM/F12/charcoal-stripped fetal calf serum for 48 h until 80 % confluent. This method achieves cultures of 85-90 % epithelial cell purity, as judged by morphological and immunohistochemical criteria [25]. A pan-cytokeratin antibody (Dako) diluted 1:4 in non-immune block after enzymatic antigen retrieval (0.1 % trypsin in 0.1 % CaCl2 for 15 min at 37°C) were used for immunohistochemical staining.
For the extended experiments in which insufficient primary EECs were available, a human endometrial epithelial (HES) cell line were used. The HES cell line [26] was obtained from Dr. Douglas Kniss (Ohio State University, Columbus, OH). Cells were maintained in RPMI 1640 (Thermo Electron) supplemented with 10 % FCS. Confluent cells were transferred into serum reduced (1 % FCS) medium for 24 h before use.
Scanning electron microscopy (SEM)
SEM was performed to evaluate the presence of pinopodes in the endometrial specimens obtained at the midluteal phase of the menstrual cycle. For SEM preparation, endometrial biopsies were fixed for at least 24 h in 2.5 % glutaraldehyde in 0.1 M phosphate buffer (pH 7.4) at 4°C and postfixed using 1 % OsO 4 in 0.1 M phosphate buffer (pH 7.4) for 1 h. The specimens were then dehydrated in a graded series of ethanol (50 %, 70 %, 90 %, 99.5 % and 100 %), critical-point-dried with carbon dioxide using a freeze drying device (JFD-300, JEOL, Tokyo, Japan), mounted, and coated with gold in a sputter coater. Finally, the specimens were observed under a scanning electron microscope (JSM-5600 LV SEM, JEOL).
Immunohistochemistry and immunofluorescent staining for light microscopy
Polymer peroxidase staining (Envision+/HRP; DakoCytomation, Denmark) was performed as described previously [27]. Briefly, using optimal cutting temperature (OCT) compound-embedded samples, cryostatic sections (4 μm thickness) were mounted on positively charged slides, fixed with ice-cold 100 % acetone for 10 minutes and air-dried. After blocking endogenous peroxidase activity by immersing the slides in 0.3 % hydrogen peroxide (H 2 O 2 ) in methanol for 10 minutes at room temperature, nonspecific background was blocked with 5 % BSA for 30 minutes at room temperature. The tissue sections were then incubated overnight at 4°C with an anti-human L-selectin ligand monoclonal antibody (MECA-79; BD Pharmingen) at a concentration of 2 μg/ml and isotype IgG control at the same concentration as the primary antibody. After washing, sections were incubated with an Envision+/HRP anti-mouse secondary IgG for 30 min at room temperature. Peroxidase activity was detected by incubating the specimens for about 10 min at room temperature with 0.5 mg/ml DAB-0.005 % H 2 O 2 -PBS. Finally, nuclear counterstaining was done with hematoxylin. A positive control section of tonsil and a negative (no antibody) control section of endometrium tissue were used to determine the specificity of the antibody.
For immunofluorescent staining, cryostatic sections were fixed with ice-cold 100 % acetone for 10 minutes and air-dried. Nonspecific background was then blocked with 5 % BSA for 30 minutes at room temperature. The tissue sections then were incubated overnight at 4°C with 2 μg/ml of an anti-human L-selectin ligand monoclonal antibody (MECA-79). For negative controls, normal mouse serum IgG was used instead of primary antibody. The tissue sections were then counter-stained with appropriate secondary antibody (FITC-labeled IgG, 2 μg/ml) and incubated for 1-3 h at room temperature. Tissue sections were washed with PBS, rinsed in deionized water and mounted. The tissue sections were then observed using an AX-80 fluorescence microscope (Olympus Optical).
Immunostaining for transmission electron microscopy (TEM)
Immunogold staining for TEM was performed to determine the ultrastructural distribution of L-selectin ligand (MECA-79) according to previous reports [27]. Briefly, specimens were divided into the 2 mm 3 blocks and fixed in 4 % PFA in 0.1 M phosphate buffer (pH 7.4) for at least 24 h at 4°C. After dehydration in a graded series of ethanol (50 %, 70 %, 90 %, 99.5 %, 100 %), they were embedded in Lowicryle white resin (London Resin company Ltd., London, UK). They were cut into ultrathin sections, which were then washed in PBS and pretreated with 5 % BSA for 10 min at room temperature. After rinsing in PBS, they were incubated overnight at 4°C with a monoclonal anti-human L-selectin ligand antibody (MECA-79, 1.5 μg/ml) or with normal mouse sera (1.5 μg/ml), as negative control. Following washing in PBS (5 times, 5 min each), the ultrathin sections were incubated overnight at 4°C with 12 nm colloidal goldconjugated secondary (Jackson Immuno Research Laboratories Inc., West Grove, PA, USA), diluted with PBS (1:20). The ultrathin sections were then washed in PBS followed by washing in distilled water. The ultrathin sections were stained with uranyle acetate and observed under a transmission electron microscope (JEM-1010; JEOL, Japan).
Morphometric and statistical analyses were performed to determine the expression pattern of MECA-79 during the opening of the implantation window, that is, days 19-20 of a normal menstrual cycle. For morphometric analysis, 400 fields obtained at the midluteal phase (40 fields for each biopsy specimen, each field equaled to 8.04 μm 2 ) were randomly chosen near the cell membrane of either pinopodes or the neighboring uterodomefree areas by an observer who was blind to the identity of the grids. Then, the number of immunogold particles was counted in all selected areas at the same magnification (X15000). After calculating the area-related numerical densities of immunogold particles, statistical analysis was performed comparing pinopodes and the neighboring uterodome-free areas. For the morphometric assessment of the area-related numerical densities of immunogoldconjugated MECA-79, statistical analysis was carried out by taking the mean number of immunogold particles in 40 fields per block of each specimen from 5 patients' endometrial biopsies. The area-related numerical density of immunogold particles was expressed as Mean ± SEM. Statistical significance was evaluated using paired sample t-test and a p < 0.05 was considered statistically significant.
Immunoblotting
Immunoblotting was performed for expression studies of MECA-79. Both endometrial epithelial cell line (HES) and primary human endometrial epithelial cells (hEEC) were used and western blot analyses were performed using standard protocols as previously described [28]. Briefly, equal amounts of protein lysate (10 μg) were separated on 8.5 % SDS/PAA gels and transferred onto polyvinylidene difluoride membranes (Hybond-P; Amersham Pharmacia Biotech, Piscataway, NJ). All membranes were incubated with Ponceau-S (Sigma) to ensure equal protein loading in all lanes. After blocking with 5 % nonfat dry milk in TBS with 0.1 % Tween-20 (Bio-Rad Laboratories, Hercules, CA), membranes were incubated overnight (4°C) with rat monoclonal antibody MECA-79 (200 μg/0.1 ml, 1:500, Santa Cruz, SC 19602 L). After washing with 0.2 % Tween-20/TBS, the membranes were incubated 1 h (room temperature) with secondary antibodies (rabbit anti rat IgG horseradish peroxidase linked, Cell Signaling Technology, Beverly, MA, 1:2500) signals were developed by using ECL Western blotting detection system (Pierce, Rockford, IL, USA) followed by the exposure of the membranes to a Kodak X-AR film (Eastman Kodak co., Rochester, NY, USA) for 1-5 min at room temperature. To analyze nonspecific secondary antibody binding, membranes were stripped and incubated with isotype control rat IgG (Sigma, Chemical Company, St. Louis, MO, 1.7 mg/ml). Page Ruler prestained protein ladder (Fermentas, St. Leon-Rot, Germany) was used as a molecular size marker. This experiment was performed in triplicate using three different samples obtained at the midluteal phase.
Results
SEM images demonstrated that the endometrial luminal epithelium in the midluteal phase of the menstrual cycle showed two different types of cells: ciliated and nonciliated cells. The majority of the luminal epithelial cells were of the latter type ( Figure 1 A and B). The membranous projections on the apical pole of nonciliated cells appeared as fine microvilli and were dome-like. The SEM images of the midluteal phase specimens revealed that fully developed pinopodes were abundant in these samples among few regressing pinopodes (Figure 1 A and B).
Strong immunoreactivity for MECA-79 was seen in the midluteal phase human endometrium (Figure 2A). MECA-79 localized at the luminal and glandular epithelium predominantly at the cell membrane with little cytoplasmic staining observed. By contrast, no MECA- Figure 2B). In the negative controls, no staining was observed ( Figure 2C).
Similarly immunofluorescent staining revealed MECA-79 localized predominantly at luminal epithelium in the midluteal phase human endometrium ( Figure 3A). In the negative controls, no staining was observed ( Figure 3C).
Immunoblotting analysis demonstrated the expression of L-selectin ligand in both epithelial endometrial cells (EEC) and human endometrial epithelial cell line (HES) in protein level (Figure 4), while no expression was seen in negative controls using rat IgG as isotype control.
In the immunogold TEM photomicrographs, MECA-79-conjugated nanogolds were predominantly observed in the pinopodes ( Figure 5A, 5B), implicating a different subcellular area-related expression pattern of MECA-79 in the luminal epithelial cells of the midluteal phase endometrium ( Figure 5B). In the negative controls, no staining was observed ( Figure 5C).
Semi-quantitative statistical analysis revealed that the area-related numerical densities of the MECA-79conjugated nanogolds were 3.9 higher in pinopodes compared to that of pinopode-free neighboring areas ( Figure 6).
Discussion
To the best of our knowledge, this is the first report of the subcellular localization of L-selectin ligand MECA-79 in the human pinopodes suggest a novel role for pinopodes possibly in inducing a shear-stress-dependent tethering-type adhesion in the initial phases of human embryo implantation. It has been reported that pinopodes are integrin-enriched subcellular structures that can be considered as biomarkers of endometrial receptivity [29]. However, the clinical usefulness of pinopodes to delineate a period of endometrial receptivity seems unlikely following recent findings that pinopodes have a prolonged (>5 days) presence in the luteal phase and fail to delineate the brief (24-48 h) window of receptivity [30]. Therefore, the functional importance of pinopodes, bleb-like hormone-dependent structures that appear at the time of implantation and extend beyond the glycocalyx layer of the apical membrane of the endometrial epithelium, remains elusive [31,32]. Endometrial pinopodes resemble morphologically the docking structures of the endothelium [22] that are believed to be key elements for the initiation of molecular interactions to capture the blastocyst or leukocyte, respectively, indicating an active role for adhesive three dimensional docking structures in the extravasation sequence corresponds to the interaction of selectins with their carbohydrate-based ligands [33][34][35]. Thus, an objective of this study was to detect the existence of a member of such systems at pinopodes.
To this end, MECA-79, a monoclonal antibody that blocks L-selectin-dependent lymphocyte attachment and recognizes 6-sulfo sLex, a sulfation dependent determinant on L-selectin ligands [36,37] was used to determine the subcellular distribution pattern of the L-selectin ligand in human endometrial epithelial cells and in pinopodes. The antibody binds the sulfated oligosaccharide epitopes of L-selectin ligands, enabling the quantification of L-selectin expression in represented tissue samples [38,39]. The evaluation of the expression pattern of Lselectin ligand was based on a semi quantitative immunohistochemical score, incorporating morphometric analysis of area-related numerical density of MECA-79-conjugated nanogolds in pinopode and adjacent pinopode-free areas of apical cell membrane of luminal endometrial epithelium. Meca-79 immunostainings demonstrated that MECA-79 localized at the luminal and glandular epithelium predominantly at the cell membrane with little cytoplasmic staining observed ( Figure 2, panel b). By contrast, no MECA-79 immunostaing was visible in the stroma. This is inconsistent with a previous report which showed that in the glandular epithelium the expression of L-selectin ligands was greatest in the midluteal phase [12]. Western blot analysis also showed that L-selectin ligand protein was detected in endometrial epithelial culture of our endometrial epithelial cell line (HES) as well as in primary endometrial epithelial cells. These results demonstrated the presence of L-selectin ligand in the human endometrial epithelial cells, supporting our immunostaining results and were consistent with pervious publications in cultured endometrial epithelial cells [10,15]. Moreover, the results of our TEM immunogold staining demonstrated the expression of MECA-79 at pinopodes of mid-secretory endometrial biopsies. The semi quantitative morphometric analysis revealed that statistically higher area-related numerical density of MECA-79-conjugated nanogolds exists in pinopode compared to that of adjacent pinopode-free areas. This is, to our knowledge, the first report of subcellular and distribution pattern of L-Selectin ligand in human luminal endometrial epithelium. These results can propose a novel role for human endometrial pinopodes similar to that of endothelial docking structures in tethering process which allows the leukocyte to roll on the endothelial cell wall. It seems that the L-selectin adhesion system plays a role in human, but not mouse embryo implantation. It is reasonable that mutant mice deficient in the L-selectin gene show no defect in implantation even though a microarray analysis of mouse blastocysts has showed an elevation of L-selectin transcripts during the maturation stage, when the blastocysts are competent for implantation [40]. Thus, it might be concluded that other selectins or integrin ligands compensate for this deficiency in mice or the role of L-selectin in implantation is restricted to humans. E-, L-, and P-selectin were originally thought to be expressed exclusively by hemangioblast descendents [9] and the discovery that the L-selectin system might function during reproduction was an unexpected finding. Our data together with previous reports may reveal that a clear parallelism between the different steps in human embryo-endometrial apposition/adhesion and leukocyteendothelium rolling/adhesion can be established both at the molecular and morphological levels. Such homotypic adhesive interaction using the L-selectin adhesion system has been previously suggested by the other groups for placental cytotrophoblast [41,42]. They have a remarkable ability to modulate their adhesion molecule repertoire as they move through cell columns and acquire the ability to invade the uterine wall and the blood vessels that traverse this region. Of course, a large force is required to physically immobilize a free-floating cell to a flat surface. Given the enormous difference in size between a human blastocyst (diameter, 115~265 mm) and lymphocyte (diameter, 10 mm), it is difficult to imagine that a blastocyst could be immobilized to endometrial epithelia solely through L-selectin, given the somewhat weak selectin-carbohydrate interactions [43,44]. It seems reasonable to speculate that a human blastocyst rolls over the glycocalyx of the endometrial epithelium through weak interactions with L-selectin, similar to the movement of lymphocytes over endothelial cells that is mediated by L-selectin. L-selectin-mediated rolling may allow cross-talk between the blastocyst and maternal epithelia, leading to stronger cell adhesion by direct binding between the components embedded in the plasma membranes on the fetal and maternal sides. Considering the report that showed pinopode formation is accompanied by loosening of endometrial inter epithelial cell contacts strengthens our hypothesis that the expression of L-selectin ligand in pinopodes and the activation of L-selectin ligand-mediated rolling might facilitate stronger blastocyst attachment and penetration to the lateral membrane of endometrial epithelial cells. This is consistent with a previous suggested model for human embryo adhesion phases, termed as early and late adhesion events [45]. Moreover, previous studies showed that mucin-1 (Muc-1), a cell-surface glycoprotein expressed on pinopodes, carries both sLex and MECA-79 epitopes [46,47], although another study indicates that MUC1 is expressed on ciliated cells [48]. As the presence of L-selectin ligand is not restricted to the ciliated cells [10,12,13,15], it seems that MUC1 is one of the carriers of L-selectin ligand in human endometrium [45]. MUC1 is a large, transmembrane mucin glycoprotein abundantly expressed at the apical surface of uterine epithelia in all species examined to date. Loss of MUC1 at the time of embryo implantation occurs in many species; however, this does not appear to be the case in Figure 6 Statistical analysis of the area-related numerical densities of immunogold conjugated L-Selectin ligand in human midsecretory phase endometrial biopsies. The statistical analyses of the number of immunogold particles revealed that the distribution of L-Selectin ligand in these specimens was significantly (p < 0.001) higher in the pinopodes of the mid-secretory phase specimen compared to pinopode-free areas. ***: p < 0.001. humans, suggesting that the human endometrium actively prevents the embryo from adhering except at the very spot of implantation. Selectins are proposed to have an important role in this phase to ensure suitable rolling of the blastocyst to ensure that the blastocyst will settle in the proper position and in the correct orientation.
Conclusions
In conclusion, this study highlights the potential importance of pinopodes in the early steps of human embryoendometrial apposition/adhesion and identities a possible novel role for pinopodes in human implantation. It provide evidence for the concept that trophoblast/ endometrium may use the L-selectin adhesion system to carry out a type of tethering adhesion that facilitates homotypic rather than heterotypic interactions demonstrating a relative abundance of L-selectin ligands presented in endometrial pinopodes. | 5,637.8 | 2012-06-15T00:00:00.000 | [
"Biology"
] |